From 0cc971d77a08211950272c34cbe66ab8de0fe6ef Mon Sep 17 00:00:00 2001
From: Ali Pirani <alipirani88@gmail.com>
Date: Tue, 16 Oct 2018 10:36:49 -0400
Subject: [PATCH 1/9] img directory

---
 barplot.png    | Bin 442748 -> 0 bytes
 barplot_DP.png | Bin 452495 -> 0 bytes
 pipeline.png   | Bin 229170 -> 0 bytes
 3 files changed, 0 insertions(+), 0 deletions(-)
 delete mode 100644 barplot.png
 delete mode 100644 barplot_DP.png
 delete mode 100644 pipeline.png

diff --git a/barplot.png b/barplot.png
deleted file mode 100644
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From a2c34cd89399b2bd280770b8a8f376f4e5833bd3 Mon Sep 17 00:00:00 2001
From: Ali Pirani <alipirani88@gmail.com>
Date: Tue, 16 Oct 2018 14:12:14 -0400
Subject: [PATCH 2/9] Adding Directory Organization Structure

---
 modules/stages.py                            |  16 ++++-----
 modules/stages.pyc                           | Bin 10124 -> 9402 bytes
 modules/variant_diagnostics/core_pipeline.py |   6 ++--
 pipeline.py                                  |  15 +++++++-
 variant_call.py                              |  36 ++++++++++++++-----
 5 files changed, 53 insertions(+), 20 deletions(-)

diff --git a/modules/stages.py b/modules/stages.py
index f4a2b76..4b43be3 100644
--- a/modules/stages.py
+++ b/modules/stages.py
@@ -143,14 +143,14 @@ def filter2_variants(final_raw_vcf, out_path, analysis, ref_index, logger, Confi
     gatk_filter2_final_vcf_contamination_file = gatk_filter2_contamination(final_raw_vcf, out_path, analysis, reference, logger, Config, Avg_dp)
     gatk_filter2_final_vcf_file_no_proximate_snp = remove_proximate_snps(gatk_filter2_final_vcf_file, out_path, analysis, reference, logger, Config)
     keep_logging('The vcf file with no proximate snp: {}'.format(gatk_filter2_final_vcf_file_no_proximate_snp), 'The vcf file with no proximate snp: {}'.format(gatk_filter2_final_vcf_file_no_proximate_snp), logger, 'debug')
-    gatk_vcf2fasta_filter2_file = gatk_vcf2fasta_filter2(gatk_filter2_final_vcf_file, out_path, analysis, reference, logger, Config)
-    gatk_vcf2fasta_filter2_file_no_proximate = gatk_vcf2fasta_filter2(gatk_filter2_final_vcf_file_no_proximate_snp, out_path, analysis, reference, logger, Config)
-    vcftools_vcf2fasta_filter2_file = vcftools_vcf2fasta_filter2(gatk_filter2_final_vcf_file, out_path, analysis, reference, logger, Config)
-    vcftools_vcf2fasta_filter2_file_no_proximate = vcftools_vcf2fasta_filter2(gatk_filter2_final_vcf_file_no_proximate_snp, out_path, analysis, reference, logger, Config)
-    keep_logging('The final Consensus Fasta file: {}'.format(gatk_vcf2fasta_filter2_file), 'The final Consensus Fasta file: {}'.format(gatk_vcf2fasta_filter2_file), logger, 'debug')
-    keep_logging('The final Consensus Fasta file with no proximate: {}'.format(gatk_vcf2fasta_filter2_file_no_proximate), 'The final Consensus Fasta file with no proximate: {}'.format(gatk_vcf2fasta_filter2_file_no_proximate), logger, 'debug')
-    keep_logging('The final Consensus Fasta file from VCF-consensus: {}'.format(vcftools_vcf2fasta_filter2_file), 'The final Consensus Fasta file from VCF-consensus: {}'.format(vcftools_vcf2fasta_filter2_file), logger, 'debug')
-    keep_logging('The final Consensus Fasta file from VCF-consensus with no proximate: {}'.format(vcftools_vcf2fasta_filter2_file_no_proximate), 'The final Consensus Fasta file from VCF-consensus with no proximate: {}'.format(vcftools_vcf2fasta_filter2_file_no_proximate), logger, 'debug')
+    #gatk_vcf2fasta_filter2_file = gatk_vcf2fasta_filter2(gatk_filter2_final_vcf_file, out_path, analysis, reference, logger, Config)
+    #gatk_vcf2fasta_filter2_file_no_proximate = gatk_vcf2fasta_filter2(gatk_filter2_final_vcf_file_no_proximate_snp, out_path, analysis, reference, logger, Config)
+    #vcftools_vcf2fasta_filter2_file = vcftools_vcf2fasta_filter2(gatk_filter2_final_vcf_file, out_path, analysis, reference, logger, Config)
+    #vcftools_vcf2fasta_filter2_file_no_proximate = vcftools_vcf2fasta_filter2(gatk_filter2_final_vcf_file_no_proximate_snp, out_path, analysis, reference, logger, Config)
+    #keep_logging('The final Consensus Fasta file: {}'.format(gatk_vcf2fasta_filter2_file), 'The final Consensus Fasta file: {}'.format(gatk_vcf2fasta_filter2_file), logger, 'debug')
+    #keep_logging('The final Consensus Fasta file with no proximate: {}'.format(gatk_vcf2fasta_filter2_file_no_proximate), 'The final Consensus Fasta file with no proximate: {}'.format(gatk_vcf2fasta_filter2_file_no_proximate), logger, 'debug')
+    #keep_logging('The final Consensus Fasta file from VCF-consensus: {}'.format(vcftools_vcf2fasta_filter2_file), 'The final Consensus Fasta file from VCF-consensus: {}'.format(vcftools_vcf2fasta_filter2_file), logger, 'debug')
+    #keep_logging('The final Consensus Fasta file from VCF-consensus with no proximate: {}'.format(vcftools_vcf2fasta_filter2_file_no_proximate), 'The final Consensus Fasta file from VCF-consensus with no proximate: {}'.format(vcftools_vcf2fasta_filter2_file_no_proximate), logger, 'debug')
 
 def filter2_indels(final_raw_indel_vcf, out_path, analysis, ref_index, logger, Config, Avg_dp):
     reference = ConfigSectionMap(ref_index, Config)['ref_path'] + "/" + ConfigSectionMap(ref_index, Config)['ref_name']
diff --git a/modules/stages.pyc b/modules/stages.pyc
index d560233588141c7ad0b64005240eafd4aa31dfd5..f9975478a228d678cb026a9a5c5e90d5381fb9de 100644
GIT binary patch
delta 149
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fJ`2Ro1rY@xq6$RRf`}F%p}{b@Mk;f%qq;W$in1Z2

delta 473
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NL^OkluE~rlI|088Wsv{?

diff --git a/modules/variant_diagnostics/core_pipeline.py b/modules/variant_diagnostics/core_pipeline.py
index 2a44261..bf5a3d9 100644
--- a/modules/variant_diagnostics/core_pipeline.py
+++ b/modules/variant_diagnostics/core_pipeline.py
@@ -3059,9 +3059,9 @@ def someOtherFunc(data, key):
         make_sure_path_exists(consensus_ref_allele_unmapped_variant_dir)
         reference_base = os.path.basename(args.reference).split('.')[0]
         # Move results to the results directory
-        move_data_matrix_results = "cp -r %s/*.csv %s/*.txt %s/temp* %s/All* %s/Only* %s/*.R %s/R_scripts/generate_diagnostics_plots.R %s/" % (args.filter2_only_snp_vcf_dir, args.filter2_only_snp_vcf_dir, args.filter2_only_snp_vcf_dir, args.filter2_only_snp_vcf_dir, args.filter2_only_snp_vcf_dir, args.filter2_only_snp_vcf_dir, os.path.dirname(os.path.abspath(__file__)), data_matrix_dir)
+        move_data_matrix_results = "cp -r %s/unique_positions_file %s/unique_indel_positions_file %s/*.csv %s/*.txt %s/temp_* %s/All* %s/Only* %s/*.R %s/R_scripts/generate_diagnostics_plots.R %s/" % (args.filter2_only_snp_vcf_dir, args.filter2_only_snp_vcf_dir, args.filter2_only_snp_vcf_dir, args.filter2_only_snp_vcf_dir, args.filter2_only_snp_vcf_dir, args.filter2_only_snp_vcf_dir, args.filter2_only_snp_vcf_dir, args.filter2_only_snp_vcf_dir, os.path.dirname(os.path.abspath(__file__)), data_matrix_dir)
         #move_core_vcf_fasta_results = "cp %s/*_core.vcf.gz %s/*.fa %s/*_variants.fa %s/" % (args.filter2_only_snp_vcf_dir, args.filter2_only_snp_vcf_dir, args.filter2_only_snp_vcf_dir, core_vcf_fasta_dir)
-        move_core_vcf_fasta_results = "mv %s/*_core.vcf.gz %s/*.fa %s/" % (args.filter2_only_snp_vcf_dir, args.filter2_only_snp_vcf_dir, core_vcf_fasta_dir)
+        move_core_vcf_fasta_results = "mv %s/*_core.vcf.gz* %s/*_ANN* %s/*.fa %s/" % (args.filter2_only_snp_vcf_dir, args.filter2_only_snp_vcf_dir, args.filter2_only_snp_vcf_dir, core_vcf_fasta_dir)
         move_consensus_var_fasta_results = "mv %s/*_variants.fa %s/" % (core_vcf_fasta_dir, consensus_var_dir)
         move_consensus_ref_var_fasta_results = "mv %s/*.fa %s/" % (core_vcf_fasta_dir, consensus_ref_var_dir)
         move_core_vcf = "mv %s/*_core.vcf.gz %s/" % (core_vcf_fasta_dir, core_vcf_dir)
@@ -3121,7 +3121,7 @@ def someOtherFunc(data, key):
         make_sure_path_exists(logs_dir)
         call("mv *.log.txt %s" % logs_dir, logger)
         call("mv summary.txt detail.txt Functional_class_filter_positions.txt inexact_repeat_region_positions.txt phage_region_positions.txt repeat_region_positions.txt %s" % functional_ann_dir, logger)
-        call("mv temp_* All* Only* SNP_matrix_* Indel* extract_DP_positions.txt header.txt %s" % matrices_dir, logger)
+        call("mv temp_* All* Only* SNP_matrix_* Indel* extract_DP_positions.txt header.txt unique_indel_positions_file unique_positions_file %s" % matrices_dir, logger)
         call("mv annotated_no_proximate_snp_* %s/snpEff_results/" % data_matrix_dir, logger)
         call("mv bargraph* generate_diagnostics_plots.R %s" % plots_dir, logger)
         call("cp %s/temp_Only_filtered_positions_for_closely_matrix_FQ.txt %s/" % (matrices_dir, plots_dir), logger)
diff --git a/pipeline.py b/pipeline.py
index 4dc4899..1d1d111 100755
--- a/pipeline.py
+++ b/pipeline.py
@@ -38,7 +38,7 @@ def parser():
                                                                      '2.   clean,align,post-align,varcall,filter,stats : This will also run all steps starting from cleaning to variant calling. \nYou can also run part of the pipeline by giving "align,post-align,varcall,filter,stats" which will skip the cleaning part.\nThe order is required to be sequential. Also, while skipping any of the step make sure you have results already present in your output folder.\n'
                                                                      '3.   coverage_depth_stats: Run Only Depth of Coverage Stats module after cleaning and read mapping steps')
     optional.add_argument('-cluster', action='store', dest='cluster', help='Run pipeline on cluster/parallel-local/local. Make Sure to check if the [CLUSTER] section in config file is set up correctly.')
-    #optional.add_argument('-noclean', action='store', dest="noclean", help='Do not clean up intermediate files. Default: OFF')
+    optional.add_argument('-clean', action="store_true", help='clean up intermediate files. Default: OFF')
     return parser
 
 # Main Pipeline method
@@ -434,6 +434,18 @@ def picard_seqdict(dict_name, reference):
         keep_logging('Error in Picard Sequence Dictionary creation step. Exiting.', 'Error in Picard Sequence Dictionary creation step. Exiting.', logger, 'exception')
         sys.exit(1)
 
+def cleanup(args, logger):
+    if args.clean:
+        keep_logging('Removing Intermediate Temporary files', 'Removing Intermediate Temporary files', logger, 'info')
+        os.chdir(args.output_folder)
+        os.system("rm %s/*.fq.gz %s/*.sam %s/*_aln.bam %s/*_marked.bam %s/*_marked.bai %s/*_unmapped.bed" % (args.output_folder, args.output_folder, args.output_folder, args.output_folder, args.output_folder, args.output_folder))
+    make_sure_path_exists("%s/%s_stats_results" % (args.output_folder, args.analysis_name))
+    os.system("mv %s/*depth_of_coverage* %s/*_stats %s/*_markduplicates_metrics %s/*_values.txt %s/*_INFO.txt %s/%s_stats_results" % (args.output_folder, args.output_folder, args.output_folder, args.output_folder, args.output_folder, args.output_folder, args.analysis_name))
+    make_sure_path_exists("%s/%s_logs" % (args.output_folder, args.analysis_name))
+    os.system("mv %s/*.log.txt %s/%s_logs" % (args.output_folder, args.output_folder, args.analysis_name))
+    make_sure_path_exists("%s/%s_vcf_results" % (args.output_folder, args.analysis_name))
+    os.system("mv %s/*.vcf* %s/%s_vcf_results" % (args.output_folder, args.output_folder, args.analysis_name))
+
 # Start of Main Method/Pipeline
 if __name__ == '__main__':
     start_time = datetime.now().strftime('%Y-%m-%d %H:%M:%S')
@@ -456,6 +468,7 @@ def picard_seqdict(dict_name, reference):
     Config = ConfigParser.ConfigParser()
     Config.read(config_file)
     pipeline(args, logger)
+    cleanup(args, logger)
     keep_logging('End: Pipeline', 'End: Pipeline', logger, 'info')
     time_taken = datetime.now() - start_time_2
     keep_logging('Total Time taken: {}'.format(time_taken), 'Total Time taken: {}'.format(time_taken), logger, 'info')
diff --git a/variant_call.py b/variant_call.py
index ea74f0f..a7a5d5d 100644
--- a/variant_call.py
+++ b/variant_call.py
@@ -39,7 +39,7 @@ def parser():
     optional.add_argument('-suffix', action='store', dest="suffix", help='Fastq reads suffix such as fastq, fastq.gz, fq.gz, fq; Default: fastq.gz', required=False)
     optional.add_argument('-filenames', action='store', dest="filenames", help='fastq filenames with one single-end filename per line. \nIf the type is set to PE, it will detect the second paired-end filename with the suffix from first filename. \nUseful for running variant calling pipeline on selected files in a reads directory or extracting core snps for selected samples in input reads directory. \nOtherwise the pipeline will consider all the samples available in reads directory.', required=False)
     optional.add_argument('-cluster', action='store', dest='cluster', help='Run variant calling pipeline in one of the four modes. Default: local. Suggested mode for core snp is cluster that will run all the steps in parallel with the available cores. Make sure to provide a large memory node for this option\nThe possible modes are: cluster/parallel-cluster/parallel-local/local\ncluster: Runs all the jobs on a single large cluster. This will mimic the local run but rather on a large compute node.\nparallel-cluster: Submit variant call jobs for each sample in parallel on compute nodes. This mode is no available for core snp extraction step.\nparallel-local: Run variant call jobs for each sample in parallel locally.\nlocal: Run variant call jobs locally.\nMake Sure to check if the [scheduler] section in config file is set up correctly for your cluster.')
-    optional.add_argument('-clean', action='store', dest="clean", help='clean up intermediate files. Default: OFF')
+    optional.add_argument('-clean', action="store_true", help='clean up intermediate files. Default: OFF')
     optional.add_argument('-extract_unmapped', action='store', dest="extract_unmapped", help='Extract unmapped reads, assemble it and detect AMR genes using ariba')
     optional.add_argument('-datadir', action='store', dest="datadir", help='Path to snpEff data directory')
     optional.add_argument('-snpeff_db', action='store', dest="snpeff_db", help='Name of pre-build snpEff database to use for Annotation')
@@ -164,9 +164,20 @@ def create_varcall_jobs(filenames_array, type, output_folder, reference, steps,
             if not steps:
                 steps == "All"
             if type == "SE":
-                command = "/nfs/esnitkin/bin_group/anaconda2/bin/python %s/pipeline.py -PE1 %s -o %s/%s -analysis %s -index %s -type SE -config %s -steps %s" % (os.path.dirname(os.path.abspath(__file__)), first_file, output_folder, first_part, first_part, reference, config_file, steps)
+                if args.clean:
+                    command = "/nfs/esnitkin/bin_group/anaconda2/bin/python %s/pipeline.py -PE1 %s -o %s/%s -analysis %s -index %s -type SE -config %s -steps %s -clean" % (
+                    os.path.dirname(os.path.abspath(__file__)), first_file, output_folder, first_part, first_part,
+                    reference, config_file, steps)
+                else:
+                    command = "/nfs/esnitkin/bin_group/anaconda2/bin/python %s/pipeline.py -PE1 %s -o %s/%s -analysis %s -index %s -type SE -config %s -steps %s" % (os.path.dirname(os.path.abspath(__file__)), first_file, output_folder, first_part, first_part, reference, config_file, steps)
+
             else:
-                command = "/nfs/esnitkin/bin_group/anaconda2/bin/python %s/pipeline.py -PE1 %s -PE2 %s -o %s/%s -analysis %s -index %s -type PE -config %s -steps %s" % (os.path.dirname(os.path.abspath(__file__)), first_file, second_file, output_folder, first_part, first_part, reference, config_file, steps)
+                if args.clean:
+                    command = "/nfs/esnitkin/bin_group/anaconda2/bin/python %s/pipeline.py -PE1 %s -PE2 %s -o %s/%s -analysis %s -index %s -type PE -config %s -steps %s -clean" % (
+                    os.path.dirname(os.path.abspath(__file__)), first_file, second_file, output_folder, first_part,
+                    first_part, reference, config_file, steps)
+                else:
+                    command = "/nfs/esnitkin/bin_group/anaconda2/bin/python %s/pipeline.py -PE1 %s -PE2 %s -o %s/%s -analysis %s -index %s -type PE -config %s -steps %s" % (os.path.dirname(os.path.abspath(__file__)), first_file, second_file, output_folder, first_part, first_part, reference, config_file, steps)
 
             with open(job_name, 'w') as out:
                 job_title = "#PBS -N %s" % first_part
@@ -491,29 +502,35 @@ def run_tree_analysis(core_temp_dir, reference, analysis_name, log_unique_time,
     start_time = datetime.now().strftime('%Y-%m-%d %H:%M:%S')
     start_time_2 = datetime.now()
 
+    # Pass arguments to args object
     args = parser().parse_args()
 
     global config_file
     global log_unique_time
+    global Config
+    global files_to_delete
+    global logger
+
     if args.output_folder != '':
         args.output_folder += '/'
     make_sure_path_exists(args.output_folder)
+
     log_unique_time = datetime.now().strftime('%Y_%m_%d_%H_%M_%S')
+
     if args.config:
         config_file = args.config
     else:
         config_file = os.path.dirname(os.path.abspath(__file__)) + "/config"
-    global logger
+
+
     logs_folder = args.output_folder + "/Logs"
     make_sure_path_exists(logs_folder)
     # logger = generate_logger(logs_folder, args.analysis_name, log_unique_time)
-    global Config
-    global files_to_delete
+
     files_to_delete = []
     Config = ConfigParser.ConfigParser()
     Config.read(config_file)
 
-
     # Run pipeline steps
     if "core" not in args.steps and "core_prep" not in args.steps and "report" not in args.steps and "tree" not in args.steps:
         vc_logs_folder = logs_folder + "/variant_calling"
@@ -545,7 +562,10 @@ def run_tree_analysis(core_temp_dir, reference, analysis_name, log_unique_time,
 
         make_sure_path_exists(core_temp_dir)
         keep_logging('Copying vcf files to %s' % core_temp_dir, 'Copying vcf files to %s' % core_temp_dir, logger, 'info')
-        cp_command = "cp %s/*/*_filter2_indel_final.vcf %s/*/*_aln_mpileup_raw.vcf %s/*/*_raw.vcf_5bp_indel_removed.vcf* %s/*/*filter2_final.vcf.gz %s/*/*vcf_no_proximate_snp.vcf* %s/*/*array %s/*/*unmapped.bed_positions %s" % (args.output_folder, args.output_folder, args.output_folder, args.output_folder, args.output_folder, args.output_folder, args.output_folder, core_temp_dir)
+        cp_command = "cp %s/*/*_vcf_results/*_filter2_indel_final.vcf %s/*/*_vcf_results/*_aln_mpileup_raw.vcf %s/*/*_vcf_results/*_raw.vcf_5bp_indel_removed.vcf* %s/*/*_vcf_results/*filter2_final.vcf* %s/*/*_vcf_results/*vcf_no_proximate_snp.vcf* %s/*/*_vcf_results/*array %s/*/*_vcf_results/*unmapped.bed_positions %s" % (args.output_folder, args.output_folder, args.output_folder, args.output_folder, args.output_folder, args.output_folder, args.output_folder, core_temp_dir)
+        # cp_command = "cp %s/*/*_filter2_indel_final.vcf %s/*/*_aln_mpileup_raw.vcf %s/*/*_raw.vcf_5bp_indel_removed.vcf* %s/*/*filter2_final.vcf* %s/*/*vcf_no_proximate_snp.vcf* %s/*/*array %s/*/*unmapped.bed_positions %s" % (
+        # args.output_folder, args.output_folder, args.output_folder, args.output_folder, args.output_folder,
+        # args.output_folder, args.output_folder, core_temp_dir)
         call(cp_command, logger)
         list_of_gzipped_files = glob.glob("%s/*.gz" % core_temp_dir)
         keep_logging('Decompressing gzipped files in %s' % core_temp_dir, 'Decompressing gzipped files in %s' % core_temp_dir, logger, 'info')

From 46c869efc463d2ba9ff8071477d276efbdc0f291 Mon Sep 17 00:00:00 2001
From: Ali Pirani <alipirani88@gmail.com>
Date: Wed, 24 Oct 2018 05:34:17 -0400
Subject: [PATCH 3/9] Merging core_prep, core, report and tree steps

---
 modules/core_prep_sanity_checks.py           |  34 +-
 modules/core_prep_sanity_checks.pyc          | Bin 3934 -> 4050 bytes
 modules/phage_detection.py                   |  23 +-
 modules/phage_detection.pyc                  | Bin 5203 -> 5607 bytes
 modules/variant_diagnostics/core_pipeline.py |  64 ++-
 pipeline.py                                  |   4 +-
 variant_call.py                              | 507 ++++++++++++++++---
 7 files changed, 505 insertions(+), 127 deletions(-)

diff --git a/modules/core_prep_sanity_checks.py b/modules/core_prep_sanity_checks.py
index 8bc2231..d8685b0 100644
--- a/modules/core_prep_sanity_checks.py
+++ b/modules/core_prep_sanity_checks.py
@@ -45,12 +45,36 @@ def make_sure_files_exists(vcf_file_array, Config, logger):
         ori_indel_file = files.replace("filter2_final.vcf_no_proximate_snp.vcf",
                                        "filter2_indel_final.vcf")
 
-        if os.path.isfile(ori_unmapped_file) and os.path.isfile(ori_proximate_file) and os.path.isfile(
-                ori_variant_position_file) and os.path.isfile(ori_5bp_mpileup_file) and os.path.isfile(
-                ori_mpileup_file) and os.path.isfile(ori_filter_file) and os.path.isfile(ori_indel_file):
-            continue
+        # if os.path.isfile(ori_unmapped_file) and os.path.isfile(ori_proximate_file) and os.path.isfile(
+        #         ori_variant_position_file) and os.path.isfile(ori_5bp_mpileup_file) and os.path.isfile(
+        #         ori_mpileup_file) and os.path.isfile(ori_filter_file) and os.path.isfile(ori_indel_file):
+        #     continue
+        # else:
+        #     not_found_files.append(files)
+
+        if not os.path.isfile(ori_unmapped_file):
+            not_found_files.append(ori_unmapped_file)
+
+        elif not os.path.isfile(ori_proximate_file):
+            not_found_files.append(ori_proximate_file)
+
+        elif not os.path.isfile(ori_variant_position_file):
+            not_found_files.append(ori_variant_position_file)
+
+        elif not os.path.isfile(ori_5bp_mpileup_file):
+            not_found_files.append(ori_5bp_mpileup_file)
+
+        elif not os.path.isfile(ori_mpileup_file):
+            not_found_files.append(ori_mpileup_file)
+
+        elif not os.path.isfile(ori_filter_file):
+            not_found_files.append(ori_filter_file)
+
+        elif not os.path.isfile(ori_indel_file):
+            not_found_files.append(ori_indel_file)
         else:
-            not_found_files.append(files)
+            continue
+
     if len(not_found_files) > 0:
         for i in not_found_files:
             keep_logging('Error finding variant calling output files for: %s' % os.path.basename(i.replace('_filter2_final.vcf_no_proximate_snp.vcf', '')),
diff --git a/modules/core_prep_sanity_checks.pyc b/modules/core_prep_sanity_checks.pyc
index 706b34cfec31038e23f4caf3e323ae5bb0cfb6e9..f3887976bda0c6035c8ebac0126f7ebb50751414 100644
GIT binary patch
delta 382
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zhLxe2k%6(0m!X7_A&ZG2i<zN@4J1^26{Z5rMODELR`DIC0?b8K!2wnw$q2Ot%tffE
z2U)`jR$>iP0_Gx=fK+gSRm8$nfVrqDxWOuTVGaRvK`J09yo41b1N2P_2SYXsL(xCR
zib#;iWF@9x#`&AenD|&YJs5z1jg66a@<cWXWkya$PEH|40VZ6SooVwHw$IFrDU(-l
W-DgbQ+`-+z#2B)flP`pk(Ha2z-A6b8

delta 259
zcmca4e@~8``7<w9W8waZ>^FrMF)}cuGceRLGgQbj)-W)*#EMS*Jh8q=l(B@7A&ZG2
zi<zN@jiH&50Y!uzLxclEgcC!A3qyn(DpJVH07Ny+3|TA;H7pFx5{wLtK!NZQR*)dj
z_7o0=Y!-&1d6TP|q8RNrUt{89;WS|Y0yZ{A-pL=?B={LQ89AAB8C4i{8QGWw88>UN
de`aR%nJmM7pV4>oAMOSwMw`vGd?AdC$^a(GGg<%u

diff --git a/modules/phage_detection.py b/modules/phage_detection.py
index 2a10997..cbf5b6b 100644
--- a/modules/phage_detection.py
+++ b/modules/phage_detection.py
@@ -99,7 +99,28 @@ def parse_phaster(reference_genome, outdir, logger, Config):
         f_open = open("%s/phage_region_positions.txt" % outdir, 'w+')
         for pos in phage_positions:
             f_open.write(str(pos) + "\n")
-    else:
+
+
+
+    if os.path.isfile("%s/summary.txt" % os.path.dirname(reference_genome)):
+        keep_logging('Extracting Phage region information from %s/summary.txt' % os.path.dirname(reference_genome), 'Extracting Phage region information from %s/summary.txt' % os.path.dirname(reference_genome), logger, 'info')
+        get_phage_regions = "sed -n -e '/REGION/,$p' %s/summary.txt | awk 'NR>2' | awk -F' ' '{print $5}'" % os.path.dirname(reference_genome)
+        proc = subprocess.Popen([get_phage_regions], stdout=subprocess.PIPE, shell=True)
+        (out, err) = proc.communicate()
+        out = (out.strip()).split('\n')
+        #print out
+        phage_positions = []
+        for i in out:
+            i_range = i.split('-')
+            end_range = int(i_range[1]) + 1
+            phage_positions.extend(list(range(int(i_range[0]), end_range)))
+
+        f_open = open("%s/phage_region_positions.txt" % outdir, 'w+')
+        for pos in phage_positions:
+            f_open.write(str(pos) + "\n")
+
+
+    if not os.path.isfile("%s/phage_region_positions.txt" % outdir):
         keep_logging('Phaster output file %s/summary.txt not found. Phaster job is still running or Phaster get json results were empty.' % outdir,
                      'Phaster output file %s/summary.txt not found. Phaster job is still running or Phaster get json results were empty.' % outdir, logger, 'exception')
         exit()
diff --git a/modules/phage_detection.pyc b/modules/phage_detection.pyc
index 7c27eaaa7b159dbdba44494ba5ae9f1b0f916f7a..444b334bcd263258bd2a4a1f34167296bec95b3b 100644
GIT binary patch
delta 334
zcmcbt@m!mo`7<xqp4j6X*-KfOqS-gsvBt78YD~VvrJl~fP{P2F#mJDw!jK{cV@opB
zFfcSTGKc|j(KWUbZiW<b3^^=9HB1aCoD9t@42&rfsOl$6a;=tdWeYFiU`UZ;r~w+C
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zp+uUYMgZ(~FlVz3_b(PknaSn?*SXjk7#LDAi}Dh4H}eQCW@Owkd4o`o3X2k>F{2ox
qBBKzaC=(kaFC#yr2%{F0Fpwq3EXK&iD9Fe)*-5yB(P{E_;W+^LQb98S

delta 108
zcmaE^eOZH@`7<w9zJAF@_EJ`+kF1;PSYufky(a7OD6=K9hUY0UOwQqvk(Oj=W?*0}
z;burtVknVfs1aajW@Hcpb2cyI`NhI0J$a$v_026p3mF+_O;!`>VPoQA6l7$dd`+Z;
K(Q&f3=o|na-W-<z

diff --git a/modules/variant_diagnostics/core_pipeline.py b/modules/variant_diagnostics/core_pipeline.py
index bf5a3d9..1dd2a96 100644
--- a/modules/variant_diagnostics/core_pipeline.py
+++ b/modules/variant_diagnostics/core_pipeline.py
@@ -2857,7 +2857,6 @@ def someOtherFunc(data, key):
     global logger
     analysis_name_log = "step_" + str(args.steps)
     logger = generate_logger(args.filter2_only_snp_vcf_dir, analysis_name_log, log_unique_time)
-    keep_logging('test log', 'test log', logger, 'info')
     keep_logging('\nThe Script started at: %s' % start_time, '\nThe Script started at: %s' % start_time, logger, 'info')
     print_details = "This step will parse final vcf files(*_no_proximate_snp.vcf) generated at the end of Variant Calling Pipeline. At the end of this step, the following results will be generated and placed in output directory:\n\n" \
           "1. Final Core SNP Positions list(Variant positions that were not filtered out in any of the samples and passed all the filters)\n" \
@@ -2915,12 +2914,14 @@ def someOtherFunc(data, key):
         files_for_tabix = glob.glob("%s/*.vcf" % args.filter2_only_snp_vcf_dir)
         tabix(files_for_tabix, "vcf", logger, Config)
 
-        if ConfigSectionMap("functional_filters", Config)['apply_functional_filters'] == "yes":
-            keep_logging('Functional class filter is set to yes. Preparing Functional class filters\n', 'Functional class filter is set to yes. Preparing Functional class filters\n', logger,
-                         'info')
-            if ConfigSectionMap("functional_filters", Config)['find_phage_region'] == "yes":
-                # Submit Phaster jobs to find ProPhage region in reference genome.
-                run_phaster(args.reference, args.filter2_only_snp_vcf_dir, logger, Config)
+        # If Phaster Summary file doesn't exist in reference genome folder
+        if not os.path.isfile("%s/summary.txt" % os.path.dirname(args.reference)):
+            if ConfigSectionMap("functional_filters", Config)['apply_functional_filters'] == "yes":
+                keep_logging('Functional class filter is set to yes. Preparing Functional class filters\n', 'Functional class filter is set to yes. Preparing Functional class filters\n', logger,
+                             'info')
+                if ConfigSectionMap("functional_filters", Config)['find_phage_region'] == "yes":
+                    # Submit Phaster jobs to find ProPhage region in reference genome.
+                    run_phaster(args.reference, args.filter2_only_snp_vcf_dir, logger, Config)
 
         # Get the cluster option; create and run jobs based on given parameter. The jobs will parse all the intermediate vcf file to extract information such as if any unique variant position was unmapped in a sample, if it was filtered out dur to DP,MQ, FQ, proximity to indel, proximity to other SNPs and other variant filter parameters set in config file.
         tmp_dir = "/tmp/temp_%s/" % log_unique_time
@@ -3141,26 +3142,24 @@ def someOtherFunc(data, key):
         #make_sure_path_exists(tree_dir)
 
 
-        prepare_ref_var_consensus_input = "%s/gubbins/%s_%s_ref_var_consensus.fa" % (args.results_dir, (os.path.basename(os.path.normpath(args.results_dir))).replace('_core_results', ''), reference_base)
-        prepare_var_consensus_input = "%s/gubbins/%s_%s_var_consensus.fa" % (args.results_dir, (os.path.basename(os.path.normpath(args.results_dir))).replace('_core_results', ''), reference_base)
-        prepare_allele_var_consensus_input = "%s/gubbins/%s_%s_allele_var_consensus.fa" % (
+        prepare_ref_var_consensus_input = "%s/gubbins/%s_%s_genome_aln_w_ref_allele_gubbins.fa" % (args.results_dir, (os.path.basename(os.path.normpath(args.results_dir))).replace('_core_results', ''), reference_base)
+        prepare_var_consensus_input = "%s/gubbins/%s_%s_core_var_aln.fa" % (args.results_dir, (os.path.basename(os.path.normpath(args.results_dir))).replace('_core_results', ''), reference_base)
+        prepare_allele_var_consensus_input = "%s/gubbins/%s_%s_noncore_plus_core_variants_aln.fa" % (
         args.results_dir, (os.path.basename(os.path.normpath(args.results_dir))).replace('_core_results', ''),
         reference_base)
-        prepare_ref_allele_var_consensus_input = "%s/gubbins/%s_%s_ref_allele_var_consensus.fa" % (
-            args.results_dir, (os.path.basename(os.path.normpath(args.results_dir))).replace('_core_results', ''),
-            reference_base)
-        prepare_ref_allele_unmapped_consensus_input = "%s/gubbins/%s_%s_ref_allele_unmapped_consensus.fa" % (args.results_dir, (os.path.basename(os.path.normpath(args.results_dir))).replace('_core_results', ''), reference_base)
+        #prepare_ref_allele_var_consensus_input = "%s/gubbins/%s_%s_ref_allele_var_consensus.fa" % (args.results_dir, (os.path.basename(os.path.normpath(args.results_dir))).replace('_core_results', ''),reference_base)
+        prepare_ref_allele_unmapped_consensus_input = "%s/gubbins/%s_%s_genome_aln_w_alt_allele_unmapped_gubbins.fa" % (args.results_dir, (os.path.basename(os.path.normpath(args.results_dir))).replace('_core_results', ''), reference_base)
+
         prepare_ref_var_consensus_input_cmd = "cat %s/core_snp_consensus/consensus_ref_variant_positions/*.fa > %s" % (args.results_dir, prepare_ref_var_consensus_input)
         prepare_var_consensus_input_cmd = "cat %s/core_snp_consensus/consensus_variant_positions/*_variants.fa > %s" % (args.results_dir, prepare_var_consensus_input)
         prepare_allele_var_consensus_input_cmd = "cat %s/core_snp_consensus/consensus_allele_variant_positions/*_allele_variants.fa > %s" % (
         args.results_dir, prepare_allele_var_consensus_input)
-        prepare_ref_allele_var_consensus_input_cmd = "cat %s/core_snp_consensus/consensus_ref_allele_variant_positions/*.fa > %s" % (
-            args.results_dir, prepare_ref_allele_var_consensus_input)
+        #prepare_ref_allele_var_consensus_input_cmd = "cat %s/core_snp_consensus/consensus_ref_allele_variant_positions/*.fa > %s" % (args.results_dir, prepare_ref_allele_var_consensus_input)
         prepare_ref_allele_unmapped_consensus_input_cmd = "cat %s %s/core_snp_consensus/consensus_ref_allele_unmapped_variant/*.fa > %s" % (args.reference, args.results_dir, prepare_ref_allele_unmapped_consensus_input)
         call("%s" % prepare_ref_var_consensus_input_cmd, logger)
         call("%s" % prepare_var_consensus_input_cmd, logger)
         call("%s" % prepare_allele_var_consensus_input_cmd, logger)
-        call("%s" % prepare_ref_allele_var_consensus_input_cmd, logger)
+        #call("%s" % prepare_ref_allele_var_consensus_input_cmd, logger)
         call("%s" % prepare_ref_allele_unmapped_consensus_input_cmd, logger)
         # os.system(prepare_ref_var_consensus_input_cmd)
         # os.system(prepare_var_consensus_input_cmd)
@@ -3176,10 +3175,10 @@ def someOtherFunc(data, key):
 
     if "4" in args.steps:
         """ 
-        tree step 
+        Gubbins/Raxml step
         """
 
-        keep_logging('Step 4: Generate FastTree and RAxML trees for core consensus fasta files.', 'Step 4: Generate FastTree and RAxML trees for core consensus fasta files.', logger, 'info')
+        keep_logging('Step 4: Run Gubbins on core alignments and generate iqtree/RaxML trees.', 'Step 4: Run Gubbins on core alignments and generate iqtree/RaxML trees.', logger, 'info')
 
         #parse_phaster(args.reference)
         reference_base = os.path.basename(args.reference).split('.')[0]
@@ -3190,29 +3189,24 @@ def someOtherFunc(data, key):
         #make_sure_path_exists(tree_dir)
 
 
-        prepare_ref_var_consensus_input = "%s/gubbins/%s_%s_ref_var_consensus.fa" % (args.results_dir, (os.path.basename(os.path.normpath(args.results_dir))).replace('_core_results', ''), reference_base)
-        prepare_var_consensus_input = "%s/gubbins/%s_%s_var_consensus.fa" % (args.results_dir, (os.path.basename(os.path.normpath(args.results_dir))).replace('_core_results', ''), reference_base)
-        prepare_allele_var_consensus_input = "%s/gubbins/%s_%s_allele_var_consensus.fa" % (
-        args.results_dir, (os.path.basename(os.path.normpath(args.results_dir))).replace('_core_results', ''),
-        reference_base)
-        prepare_ref_allele_var_consensus_input = "%s/gubbins/%s_%s_ref_allele_var_consensus.fa" % (
-            args.results_dir, (os.path.basename(os.path.normpath(args.results_dir))).replace('_core_results', ''),
-            reference_base)
-        prepare_ref_allele_unmapped_consensus_input = "%s/gubbins/%s_%s_ref_allele_unmapped_consensus.fa" % (
+        prepare_ref_var_consensus_input = "%s/gubbins/%s_%s_genome_aln_w_ref_allele_gubbins.fa" % (args.results_dir, (os.path.basename(os.path.normpath(args.results_dir))).replace('_core_results', ''), reference_base)
+        prepare_var_consensus_input = "%s/gubbins/%s_%s_core_var_aln.fa" % (args.results_dir, (os.path.basename(os.path.normpath(args.results_dir))).replace('_core_results', ''), reference_base)
+        prepare_allele_var_consensus_input = "%s/gubbins/%s_%s_noncore_plus_core_variants_aln.fa" % (
         args.results_dir, (os.path.basename(os.path.normpath(args.results_dir))).replace('_core_results', ''),
         reference_base)
+        #prepare_ref_allele_var_consensus_input = "%s/gubbins/%s_%s_ref_allele_var_consensus.fa" % (args.results_dir, (os.path.basename(os.path.normpath(args.results_dir))).replace('_core_results', ''),reference_base)
+        prepare_ref_allele_unmapped_consensus_input = "%s/gubbins/%s_%s_genome_aln_w_alt_allele_unmapped_gubbins.fa" % (args.results_dir, (os.path.basename(os.path.normpath(args.results_dir))).replace('_core_results', ''), reference_base)
+
         prepare_ref_var_consensus_input_cmd = "cat %s/core_snp_consensus/consensus_ref_variant_positions/*.fa > %s" % (args.results_dir, prepare_ref_var_consensus_input)
         prepare_var_consensus_input_cmd = "cat %s/core_snp_consensus/consensus_variant_positions/*_variants.fa > %s" % (args.results_dir, prepare_var_consensus_input)
         prepare_allele_var_consensus_input_cmd = "cat %s/core_snp_consensus/consensus_allele_variant_positions/*_allele_variants.fa > %s" % (
         args.results_dir, prepare_allele_var_consensus_input)
-        prepare_ref_allele_var_consensus_input_cmd = "cat %s/core_snp_consensus/consensus_ref_allele_variant_positions/*.fa > %s" % (
-            args.results_dir, prepare_ref_allele_var_consensus_input)
-        prepare_ref_allele_unmapped_consensus_input_cmd = "cat %s %s/core_snp_consensus/consensus_ref_allele_unmapped_variant/*.fa > %s" % (
-        args.reference, args.results_dir, prepare_ref_allele_unmapped_consensus_input)
+        #prepare_ref_allele_var_consensus_input_cmd = "cat %s/core_snp_consensus/consensus_ref_allele_variant_positions/*.fa > %s" % (args.results_dir, prepare_ref_allele_var_consensus_input)
+        prepare_ref_allele_unmapped_consensus_input_cmd = "cat %s %s/core_snp_consensus/consensus_ref_allele_unmapped_variant/*.fa > %s" % (args.reference, args.results_dir, prepare_ref_allele_unmapped_consensus_input)
         call("%s" % prepare_ref_var_consensus_input_cmd, logger)
         call("%s" % prepare_var_consensus_input_cmd, logger)
         call("%s" % prepare_allele_var_consensus_input_cmd, logger)
-        call("%s" % prepare_ref_allele_var_consensus_input_cmd, logger)
+        #call("%s" % prepare_ref_allele_var_consensus_input_cmd, logger)
         call("%s" % prepare_ref_allele_unmapped_consensus_input_cmd, logger)
         # os.system(prepare_ref_var_consensus_input_cmd)
         # os.system(prepare_var_consensus_input_cmd)
@@ -3230,12 +3224,12 @@ def someOtherFunc(data, key):
 
         if args.gubbins and args.gubbins == "yes":
             call("%s/scripts/gubbins_iqtree_raxml.sh %s 1" % (os.path.dirname(os.path.abspath(__file__)), prepare_ref_var_consensus_input), logger)
-            #call("%s/scripts/gubbins_iqtree_raxml.sh %s 1" % (os.path.dirname(os.path.abspath(__file__)), prepare_ref_allele_unmapped_consensus_input), logger)
+            call("%s/scripts/gubbins_iqtree_raxml.sh %s 1" % (os.path.dirname(os.path.abspath(__file__)), prepare_ref_allele_unmapped_consensus_input), logger)
             #call("%s/scripts/gubbins_iqtree_raxml.sh %s 1" % (os.path.dirname(os.path.abspath(__file__)), prepare_ref_allele_var_consensus_input), logger)
         else:
+            keep_logging('The gubbins argument is set to No.', 'The gubbins argument is set to No.', logger, 'info')
             print "%s/scripts/gubbins_iqtree_raxml.sh %s 0" % (os.path.dirname(os.path.abspath(__file__)), prepare_ref_var_consensus_input)
             print "%s/scripts/gubbins_iqtree_raxml.sh %s 0" % (os.path.dirname(os.path.abspath(__file__)), prepare_ref_allele_unmapped_consensus_input)
-            print "%s/scripts/gubbins_iqtree_raxml.sh %s 0" % (os.path.dirname(os.path.abspath(__file__)), prepare_ref_allele_var_consensus_input)
 
         call("cp %s %s/Logs/tree/" % (
             log_file_handle, os.path.dirname(os.path.dirname(args.filter2_only_snp_vcf_dir))), logger)
diff --git a/pipeline.py b/pipeline.py
index 1d1d111..f208ebe 100755
--- a/pipeline.py
+++ b/pipeline.py
@@ -438,13 +438,13 @@ def cleanup(args, logger):
     if args.clean:
         keep_logging('Removing Intermediate Temporary files', 'Removing Intermediate Temporary files', logger, 'info')
         os.chdir(args.output_folder)
-        os.system("rm %s/*.fq.gz %s/*.sam %s/*_aln.bam %s/*_marked.bam %s/*_marked.bai %s/*_unmapped.bed" % (args.output_folder, args.output_folder, args.output_folder, args.output_folder, args.output_folder, args.output_folder))
+        os.system("rm %s/*.fq.gz %s/*.sam %s/*_aln.bam %s/*_marked.bam %s/*_marked.bai %s/*_unmapped.bed %s/*_temp_paste_file.txt" % (args.output_folder, args.output_folder, args.output_folder, args.output_folder, args.output_folder, args.output_folder, args.output_folder))
     make_sure_path_exists("%s/%s_stats_results" % (args.output_folder, args.analysis_name))
     os.system("mv %s/*depth_of_coverage* %s/*_stats %s/*_markduplicates_metrics %s/*_values.txt %s/*_INFO.txt %s/%s_stats_results" % (args.output_folder, args.output_folder, args.output_folder, args.output_folder, args.output_folder, args.output_folder, args.analysis_name))
     make_sure_path_exists("%s/%s_logs" % (args.output_folder, args.analysis_name))
     os.system("mv %s/*.log.txt %s/%s_logs" % (args.output_folder, args.output_folder, args.analysis_name))
     make_sure_path_exists("%s/%s_vcf_results" % (args.output_folder, args.analysis_name))
-    os.system("mv %s/*.vcf* %s/%s_vcf_results" % (args.output_folder, args.output_folder, args.analysis_name))
+    os.system("mv %s/header.txt %s/*.vcf* %s/%s_vcf_results" % (args.output_folder, args.output_folder, args.output_folder, args.analysis_name))
 
 # Start of Main Method/Pipeline
 if __name__ == '__main__':
diff --git a/variant_call.py b/variant_call.py
index a7a5d5d..218e401 100644
--- a/variant_call.py
+++ b/variant_call.py
@@ -275,32 +275,40 @@ def run_varcall_jobs(list_of_jobs, cluster, log_unique_time, analysis_name, outp
 
     #cluster mode
     if cluster == "cluster":
-        keep_logging('Running Job in cluster mode', 'Running Job in cluster mode', logger, 'info')
-        cluster_job_dir = output_folder + "/temp_jobs/cluster/"
-        make_sure_path_exists(cluster_job_dir)
-        Pbs_model_lines = "#PBS -M %s\n#PBS -m %s\n#PBS -V\n#PBS -l %s\n#PBS -q %s\n#PBS -A %s\n#PBS -l qos=flux\n"\
-                      % (ConfigSectionMap("scheduler", Config)['email'], ConfigSectionMap("scheduler", Config)['notification'], ConfigSectionMap("scheduler", Config)['resources'], ConfigSectionMap("scheduler", Config)['queue'], ConfigSectionMap("scheduler", Config)['flux_account'])
-        job_name = cluster_job_dir + log_unique_time + "_" + analysis_name + ".pbs"
-        with open(job_name, 'w') as out:
-            job_title = "#PBS -N %s_%s" % (log_unique_time, analysis_name)
-            out.write(job_title+'\n')
-            out.write(Pbs_model_lines+'\n')
-            out.write("#  Change to the directory you submitted from\nif [ -n \"$PBS_O_WORKDIR\" ]; then cd $PBS_O_WORKDIR; fi" + '\n')
-            out.write("echo $PBS_O_WORKDIR" + '\n')
-            out.write("cd %s/temp_jobs" % output_folder + '\n')
-            out.write(command_list+'\n')
-        out.close()
-        keep_logging('Submitting single cluster Job: qsub %s' % job_name, 'Submitting single cluster Job: qsub %s' % job_name, logger, 'info')
-        #call("qsub %s" % job_name, logger)
-        qid = subprocess.check_output("qsub %s" % job_name, shell=True)
-        print qid.split('.')[0]
-        keep_logging('You can check the job status with: qstat -u USERNAME', 'You can check the job status with: qstat -u USERNAME', logger, 'info')
+        # Removing support for single cluster mode and replacing it with parallel-cluster
+        # keep_logging('Running Job in cluster mode', 'Running Job in cluster mode', logger, 'info')
+        # cluster_job_dir = output_folder + "/temp_jobs/cluster/"
+        # make_sure_path_exists(cluster_job_dir)
+        # Pbs_model_lines = "#PBS -M %s\n#PBS -m %s\n#PBS -V\n#PBS -l %s\n#PBS -q %s\n#PBS -A %s\n#PBS -l qos=flux\n"\
+        #               % (ConfigSectionMap("scheduler", Config)['email'], ConfigSectionMap("scheduler", Config)['notification'], ConfigSectionMap("scheduler", Config)['resources'], ConfigSectionMap("scheduler", Config)['queue'], ConfigSectionMap("scheduler", Config)['flux_account'])
+        # job_name = cluster_job_dir + log_unique_time + "_" + analysis_name + ".pbs"
+        # with open(job_name, 'w') as out:
+        #     job_title = "#PBS -N %s_%s" % (log_unique_time, analysis_name)
+        #     out.write(job_title+'\n')
+        #     out.write(Pbs_model_lines+'\n')
+        #     out.write("#  Change to the directory you submitted from\nif [ -n \"$PBS_O_WORKDIR\" ]; then cd $PBS_O_WORKDIR; fi" + '\n')
+        #     out.write("echo $PBS_O_WORKDIR" + '\n')
+        #     out.write("cd %s/temp_jobs" % output_folder + '\n')
+        #     out.write(command_list+'\n')
+        # out.close()
+        # keep_logging('Submitting single cluster Job: qsub %s' % job_name, 'Submitting single cluster Job: qsub %s' % job_name, logger, 'info')
+        # #call("qsub %s" % job_name, logger)
+        # qid = subprocess.check_output("qsub %s" % job_name, shell=True)
+        # print qid.split('.')[0]
+        # keep_logging('You can check the job status with: qstat -u USERNAME', 'You can check the job status with: qstat -u USERNAME', logger, 'info')
+
+        keep_logging('Running Jobs in parallel-cluster mode', 'Running Jobs in parallel-cluster mode', logger, 'info')
+        for job in command_list_qsub:
+            keep_logging('Submitting Job: qsub %s' % job, 'Submitting Job: qsub %s' % job, logger, 'info')
+            call("qsub %s" % job, logger)
+        # keep_logging('You can check the job status with: qstat -u USERNAME',
+        #              'You can check the job status with: qstat -u USERNAME', logger, 'info')
     elif cluster == "parallel-cluster":
         keep_logging('Running Jobs in parallel-cluster mode', 'Running Jobs in parallel-cluster mode', logger, 'info')
         for job in command_list_qsub:
             keep_logging('Submitting Job: qsub %s' % job, 'Submitting Job: qsub %s' % job, logger, 'info')
             call("qsub %s" % job, logger)
-        keep_logging('You can check the job status with: qstat -u USERNAME', 'You can check the job status with: qstat -u USERNAME', logger, 'info')
+        #keep_logging('You can check the job status with: qstat -u USERNAME', 'You can check the job status with: qstat -u USERNAME', logger, 'info')
     elif cluster == "parallel-local":
         keep_logging('Running Jobs in parallel-local mode', 'Running Jobs in parallel-local mode', logger, 'info')
         cluster_job_dir = output_folder + "/temp_jobs/parallel-local/"
@@ -341,33 +349,45 @@ def run_core_prep_analysis(core_temp_dir, reference, analysis_name, log_unique_t
                          ConfigSectionMap("scheduler", Config)['queue'],
                          ConfigSectionMap("scheduler", Config)['flux_account'])
 
-    with open(job_name, 'w') as out:
-        job_title = "#PBS -N %s_%s_core" % (log_unique_time, analysis_name)
-        out.write(job_title+'\n')
-        out.write(Pbs_model_lines+'\n')
-        out.write("#  Change to the directory you submitted from\nif [ -n \"$PBS_O_WORKDIR\" ]; then cd $PBS_O_WORKDIR; fi" + '\n')
-        out.write("echo \"PBS working directory: $PBS_O_WORKDIR\"" + '\n')
-        out.write("cd %s" % core_temp_dir + '\n')
-        out.write(core_prep_pipeline+'\n')
-    out.close()
+    # with open(job_name, 'w') as out:
+    #     job_title = "#PBS -N %s_%s_core" % (log_unique_time, analysis_name)
+    #     out.write(job_title+'\n')
+    #     out.write(Pbs_model_lines+'\n')
+    #     out.write("#  Change to the directory you submitted from\nif [ -n \"$PBS_O_WORKDIR\" ]; then cd $PBS_O_WORKDIR; fi" + '\n')
+    #     out.write("echo \"PBS working directory: $PBS_O_WORKDIR\"" + '\n')
+    #     out.write("cd %s" % core_temp_dir + '\n')
+    #     out.write(core_prep_pipeline+'\n')
+    # out.close()
     if cluster == "local":
         keep_logging('Running local mode: bash %s' % job_name, 'Running local mode: bash %s' % job_name, logger, 'info')
         call("bash %s" % job_name, logger)
     elif cluster == "parallel-local":
-        keep_logging('Running parallel-local mode: bash %s' % job_name, 'Running parallel-local mode: bash %s' % job_name, logger, 'info')
-        call("bash %s" % job_name, logger)
+        keep_logging('Running in parallel-local mode: bash %s' % job_name, 'Running in parallel-local mode: bash %s' % job_name, logger, 'info')
+        #call("bash %s" % job_name, logger)
+        os.system("bash %s" % job_name)
     elif cluster == "cluster":
         #call("qsub %s" % job_name, logger)
-        keep_logging('Submitting single cluster Job: qsub %s' % job_name, 'Submitting single cluster Job: qsub %s' % job_name, logger, 'info')
-        qid = subprocess.check_output("qsub %s" % job_name, shell=True)
-        print qid.split('.')[0]
+        keep_logging('Generating core_prep command: \n%s\n' % core_prep_pipeline, 'Generating core_prep command: \n%s\n' % core_prep_pipeline, logger, 'info')
+        #qid = subprocess.check_output("qsub %s" % job_name, shell=True)
+        #print qid.split('.')[0]
     elif cluster == "parallel-cluster":
         #call("qsub %s" % job_name, logger)
+        with open(job_name, 'w') as out:
+            job_title = "#PBS -N %s_%s_core" % (log_unique_time, analysis_name)
+            out.write(job_title + '\n')
+            out.write(Pbs_model_lines + '\n')
+            out.write(
+                "#  Change to the directory you submitted from\nif [ -n \"$PBS_O_WORKDIR\" ]; then cd $PBS_O_WORKDIR; fi" + '\n')
+            out.write("echo \"PBS working directory: $PBS_O_WORKDIR\"" + '\n')
+            out.write("cd %s" % core_temp_dir + '\n')
+            out.write(core_prep_pipeline + '\n')
+        out.close()
         keep_logging('Submitting parallel-cluster Job: qsub %s' % job_name, 'Submitting parallel-cluster Job: qsub %s' % job_name, logger, 'info')
         qid = subprocess.check_output("qsub %s" % job_name, shell=True)
         print qid.split('.')[0]
-    keep_logging('You can check the job status with: qstat -u USERNAME', 'You can check the job status with: qstat -u USERNAME', logger, 'info')
+    #keep_logging('You can check the job status with: qstat -u USERNAME', 'You can check the job status with: qstat -u USERNAME', logger, 'info')
 
+    return core_prep_pipeline
 def run_core_analysis(core_temp_dir, reference, analysis_name, log_unique_time, cluster, logger, core_results_dir, config_file):
     file_exists(reference)
     if args.debug_mode == "yes":
@@ -390,15 +410,15 @@ def run_core_analysis(core_temp_dir, reference, analysis_name, log_unique_time,
                          ConfigSectionMap("scheduler", Config)['queue'],
                          ConfigSectionMap("scheduler", Config)['flux_account'])
     
-    with open(job_name, 'w') as out:
-        job_title = "#PBS -N %s_%s_core" % (log_unique_time, analysis_name)
-        out.write(job_title+'\n')
-        out.write(Pbs_model_lines+'\n')
-        out.write("#  Change to the directory you submitted from\nif [ -n \"$PBS_O_WORKDIR\" ]; then cd $PBS_O_WORKDIR; fi" + '\n')
-        out.write("echo \"PBS working directory: $PBS_O_WORKDIR\"" + '\n')
-        out.write("cd %s" % core_temp_dir + '\n')
-        out.write(core_pipeline+'\n')
-    out.close()
+    # with open(job_name, 'w') as out:
+    #     job_title = "#PBS -N %s_%s_core" % (log_unique_time, analysis_name)
+    #     out.write(job_title+'\n')
+    #     out.write(Pbs_model_lines+'\n')
+    #     out.write("#  Change to the directory you submitted from\nif [ -n \"$PBS_O_WORKDIR\" ]; then cd $PBS_O_WORKDIR; fi" + '\n')
+    #     out.write("echo \"PBS working directory: $PBS_O_WORKDIR\"" + '\n')
+    #     out.write("cd %s" % core_temp_dir + '\n')
+    #     out.write(core_pipeline+'\n')
+    # out.close()
     if cluster == "local":
         keep_logging('Running local mode: bash %s' % job_name, 'Running local mode: bash %s' % job_name, logger, 'info')
         call("bash %s" % job_name, logger)
@@ -406,15 +426,25 @@ def run_core_analysis(core_temp_dir, reference, analysis_name, log_unique_time,
         call("bash %s" % job_name, logger)
     elif cluster == "cluster":
         #call("qsub %s" % job_name, logger)
-        keep_logging('Submitting single cluster Job: qsub %s' % job_name, 'Submitting single cluster Job: qsub %s' % job_name, logger, 'info')
-        qid = subprocess.check_output("qsub %s" % job_name, shell=True)
-        print qid.split('.')[0]
+        keep_logging('Generating Core Step command: \n%s\n' % core_pipeline, 'Generating Core Step command: \n%s\n' % core_pipeline, logger, 'info')
+        #qid = subprocess.check_output("qsub %s" % job_name, shell=True)
+        #print qid.split('.')[0]
     elif cluster == "parallel-cluster":
         #call("qsub %s" % job_name, logger)
+        with open(job_name, 'w') as out:
+            job_title = "#PBS -N %s_%s_core" % (log_unique_time, analysis_name)
+            out.write(job_title + '\n')
+            out.write(Pbs_model_lines + '\n')
+            out.write(
+                "#  Change to the directory you submitted from\nif [ -n \"$PBS_O_WORKDIR\" ]; then cd $PBS_O_WORKDIR; fi" + '\n')
+            out.write("echo \"PBS working directory: $PBS_O_WORKDIR\"" + '\n')
+            out.write("cd %s" % core_temp_dir + '\n')
+            out.write(core_pipeline + '\n')
         keep_logging('Submitting parallel-cluster Job: qsub %s' % job_name, 'Submitting parallel-cluster Job: qsub %s' % job_name, logger, 'info')
         qid = subprocess.check_output("qsub %s" % job_name, shell=True)
         print qid.split('.')[0]
     #keep_logging('You can check the job status with: qstat -u USERNAME', 'You can check the job status with: qstat -u USERNAME', logger, 'info')
+    return core_pipeline
 
 def run_report_analysis(core_temp_dir, reference, analysis_name, log_unique_time, cluster, logger, core_results_dir, config_file):
     file_exists(reference)
@@ -425,15 +455,15 @@ def run_report_analysis(core_temp_dir, reference, analysis_name, log_unique_time
     job_name = core_temp_dir + "/" + log_unique_time + "_" + analysis_name + ".pbs"
     Pbs_model_lines = "#PBS -M %s\n#PBS -m %s\n#PBS -V\n#PBS -l nodes=1:ppn=4,pmem=4000mb,walltime=92:00:00\n#PBS -q %s\n#PBS -A %s\n#PBS -l qos=flux\n"\
                       % (ConfigSectionMap("scheduler", Config)['email'], ConfigSectionMap("scheduler", Config)['notification'], ConfigSectionMap("scheduler", Config)['queue'], ConfigSectionMap("scheduler", Config)['flux_account'])
-    with open(job_name, 'w') as out:
-        job_title = "#PBS -N %s_%s_core" % (log_unique_time, analysis_name)
-        out.write(job_title+'\n')
-        out.write(Pbs_model_lines+'\n')
-        out.write("#  Change to the directory you submitted from\nif [ -n \"$PBS_O_WORKDIR\" ]; then cd $PBS_O_WORKDIR; fi" + '\n')
-        out.write("echo \"PBS working directory: $PBS_O_WORKDIR\"" + '\n')
-        out.write("cd %s" % core_temp_dir + '\n')
-        out.write(core_pipeline+'\n')
-    out.close()
+    # with open(job_name, 'w') as out:
+    #     job_title = "#PBS -N %s_%s_core" % (log_unique_time, analysis_name)
+    #     out.write(job_title+'\n')
+    #     out.write(Pbs_model_lines+'\n')
+    #     out.write("#  Change to the directory you submitted from\nif [ -n \"$PBS_O_WORKDIR\" ]; then cd $PBS_O_WORKDIR; fi" + '\n')
+    #     out.write("echo \"PBS working directory: $PBS_O_WORKDIR\"" + '\n')
+    #     out.write("cd %s" % core_temp_dir + '\n')
+    #     out.write(core_pipeline+'\n')
+    # out.close()
 
     if cluster == "local":
         keep_logging('Running local mode: bash %s' % job_name, 'Running local mode: bash %s' % job_name, logger, 'info')
@@ -442,15 +472,26 @@ def run_report_analysis(core_temp_dir, reference, analysis_name, log_unique_time
         call("bash %s" % job_name, logger)
     elif cluster == "cluster":
         #call("qsub %s" % job_name, logger)
-        keep_logging('Submitting single cluster Job: qsub %s' % job_name, 'Submitting single cluster Job: qsub %s' % job_name, logger, 'info')
-        qid = subprocess.check_output("bash %s" % job_name, shell=True)
-        print qid.split('.')[0]
+        keep_logging('Generating Report Step command: \n%s\n' % core_pipeline, 'Generating Report Step command: \n%s\n' % core_pipeline, logger, 'info')
+        #qid = subprocess.check_output("bash %s" % job_name, shell=True)
+        #print qid.split('.')[0]
     elif cluster == "parallel-cluster":
         #call("qsub %s" % job_name, logger)
+        with open(job_name, 'w') as out:
+            job_title = "#PBS -N %s_%s_core" % (log_unique_time, analysis_name)
+            out.write(job_title + '\n')
+            out.write(Pbs_model_lines + '\n')
+            out.write(
+                "#  Change to the directory you submitted from\nif [ -n \"$PBS_O_WORKDIR\" ]; then cd $PBS_O_WORKDIR; fi" + '\n')
+            out.write("echo \"PBS working directory: $PBS_O_WORKDIR\"" + '\n')
+            out.write("cd %s" % core_temp_dir + '\n')
+            out.write(core_pipeline + '\n')
+        out.close()
         keep_logging('Submitting parallel-cluster Job: qsub %s' % job_name, 'Submitting parallel-cluster Job: qsub %s' % job_name, logger, 'info')
         qid = subprocess.check_output("qsub %s" % job_name, shell=True)
         print qid.split('.')[0]
     #keep_logging('You can check the job status with: qstat -u USERNAME', 'You can check the job status with: qstat -u USERNAME', logger, 'info')
+    return core_pipeline
 
 def run_tree_analysis(core_temp_dir, reference, analysis_name, log_unique_time, cluster, logger, core_results_dir, config_file):
     if args.debug_mode == "yes":
@@ -468,15 +509,15 @@ def run_tree_analysis(core_temp_dir, reference, analysis_name, log_unique_time,
     job_name = core_temp_dir + "/" + log_unique_time + "_" + analysis_name + ".pbs"
     Pbs_model_lines = "#PBS -M %s\n#PBS -m %s\n#PBS -V\n#PBS -l %s\n#PBS -q %s\n#PBS -A %s\n#PBS -l qos=flux\n"\
                       % (ConfigSectionMap("scheduler", Config)['email'], ConfigSectionMap("scheduler", Config)['notification'], ConfigSectionMap("scheduler", Config)['resources'], ConfigSectionMap("scheduler", Config)['queue'], ConfigSectionMap("scheduler", Config)['flux_account'])
-    with open(job_name, 'w') as out:
-        job_title = "#PBS -N %s_%s_core_tree" % (log_unique_time, analysis_name)
-        out.write(job_title+'\n')
-        out.write(Pbs_model_lines+'\n')
-        out.write("#  Change to the directory you submitted from\nif [ -n \"$PBS_O_WORKDIR\" ]; then cd $PBS_O_WORKDIR; fi" + '\n')
-        out.write("echo \"PBS working directory: $PBS_O_WORKDIR\"" + '\n')
-        out.write("cd %s" % core_temp_dir + '\n')
-        out.write(core_pipeline+'\n')
-    out.close()
+    # with open(job_name, 'w') as out:
+    #     job_title = "#PBS -N %s_%s_core_tree" % (log_unique_time, analysis_name)
+    #     out.write(job_title+'\n')
+    #     out.write(Pbs_model_lines+'\n')
+    #     out.write("#  Change to the directory you submitted from\nif [ -n \"$PBS_O_WORKDIR\" ]; then cd $PBS_O_WORKDIR; fi" + '\n')
+    #     out.write("echo \"PBS working directory: $PBS_O_WORKDIR\"" + '\n')
+    #     out.write("cd %s" % core_temp_dir + '\n')
+    #     out.write(core_pipeline+'\n')
+    # out.close()
 
     if cluster == "local":
         keep_logging('Running local mode: bash %s' % job_name, 'Running local mode: bash %s' % job_name, logger, 'info')
@@ -485,16 +526,26 @@ def run_tree_analysis(core_temp_dir, reference, analysis_name, log_unique_time,
         call("bash %s" % job_name, logger)
     elif cluster == "cluster":
         #call("qsub %s" % job_name, logger)
-        keep_logging('Submitting single cluster Job: qsub %s' % job_name, 'Submitting single cluster Job: qsub %s' % job_name, logger, 'info')
-        qid = subprocess.check_output("qsub %s" % job_name, shell=True)
-        print qid.split('.')[0]
+        keep_logging('Generating Tree Step command: \n%s\n' % core_pipeline, 'Generating Tree Step command: \n%s\n' % core_pipeline, logger, 'info')
+        #qid = subprocess.check_output("qsub %s" % job_name, shell=True)
+        #print qid.split('.')[0]
     elif cluster == "parallel-cluster":
         #call("qsub %s" % job_name, logger)
+        with open(job_name, 'w') as out:
+            job_title = "#PBS -N %s_%s_core_tree" % (log_unique_time, analysis_name)
+            out.write(job_title + '\n')
+            out.write(Pbs_model_lines + '\n')
+            out.write(
+                "#  Change to the directory you submitted from\nif [ -n \"$PBS_O_WORKDIR\" ]; then cd $PBS_O_WORKDIR; fi" + '\n')
+            out.write("echo \"PBS working directory: $PBS_O_WORKDIR\"" + '\n')
+            out.write("cd %s" % core_temp_dir + '\n')
+            out.write(core_pipeline + '\n')
+        out.close()
         keep_logging('Submitting parallel-cluster Job: qsub %s' % job_name, 'Submitting parallel-cluster Job: qsub %s' % job_name, logger, 'info')
         qid = subprocess.check_output("qsub %s" % job_name, shell=True)
         print qid.split('.')[0]
     #keep_logging('You can check the job status with: qstat -u USERNAME', 'You can check the job status with: qstat -u USERNAME', logger, 'info')
-
+    return core_pipeline
 """ Start of Main Method/Pipeline """
 if __name__ == '__main__':
 
@@ -533,6 +584,7 @@ def run_tree_analysis(core_temp_dir, reference, analysis_name, log_unique_time,
 
     # Run pipeline steps
     if "core" not in args.steps and "core_prep" not in args.steps and "report" not in args.steps and "tree" not in args.steps:
+        """ Set Up variant calling logs folder/logger object, cluster mode and copy config files to it"""
         vc_logs_folder = logs_folder + "/variant_calling"
         make_sure_path_exists(vc_logs_folder)
         logger = generate_logger(vc_logs_folder, args.analysis_name, log_unique_time)
@@ -544,6 +596,7 @@ def run_tree_analysis(core_temp_dir, reference, analysis_name, log_unique_time,
 
         keep_logging('START: Variant Calling Pipeline', 'START: Variant Calling Pipeline', logger, 'info')
 
+        """ Main Variant calling Methods: Generate and Run the jobs"""
         list_of_files = get_filenames(args.dir, args.type, args.filenames, args.analysis_name, args.suffix)
         list_of_jobs = create_varcall_jobs(list_of_files, args.type, args.output_folder, args.index, args.steps, config_file, logger)
         run_varcall_jobs(list_of_jobs, cluster_mode, log_unique_time, args.analysis_name, args.output_folder, logger)
@@ -552,37 +605,324 @@ def run_tree_analysis(core_temp_dir, reference, analysis_name, log_unique_time,
         keep_logging('Total Time taken: {}'.format(time_taken), 'Total Time taken: {}'.format(time_taken), logger, 'info')
         keep_logging('End: Variant calling Pipeline', 'End: Variant calling Pipeline', logger, 'info')
 
+    elif "core_All" in args.steps:
+        core_All_cmds = []
+        """ Set Up Core Prep logs folder/logger object, cluster mode and copy config files to it"""
+        core_prep_logs_folder = logs_folder + "/core_prep"
+        make_sure_path_exists(core_prep_logs_folder)
+        core_temp_dir = args.output_folder + "/core_temp_dir/"
+        logger = generate_logger(core_prep_logs_folder, args.analysis_name, log_unique_time)
+        #keep_logging('START: Copying variant calling results to %s and running core_prep step.' % core_temp_dir, 'START: Copying variant calling results to %s and running core_prep step.' % core_temp_dir, logger, 'info')
+        call("cp %s %s/%s_%s_config_copy.txt" % (config_file, core_prep_logs_folder, log_unique_time, args.analysis_name), logger)
+        make_sure_path_exists(core_temp_dir)
+        keep_logging('\nCopying vcf files to %s\n' % core_temp_dir, '\nCopying vcf files to %s\n' % core_temp_dir, logger, 'info')
+        cp_command = "cp %s/*/*_vcf_results/*_filter2_indel_final.vcf %s/*/*_vcf_results/*_aln_mpileup_raw.vcf %s/*/*_vcf_results/*_raw.vcf_5bp_indel_removed.vcf* %s/*/*_vcf_results/*filter2_final.vcf* %s/*/*_vcf_results/*vcf_no_proximate_snp.vcf* %s/*/*_vcf_results/*array %s/*/*unmapped.bed_positions %s" % (args.output_folder, args.output_folder, args.output_folder, args.output_folder, args.output_folder, args.output_folder, args.output_folder, core_temp_dir)
+        # cp_command = "cp %s/*/*_filter2_indel_final.vcf %s/*/*_aln_mpileup_raw.vcf %s/*/*_raw.vcf_5bp_indel_removed.vcf* %s/*/*filter2_final.vcf* %s/*/*vcf_no_proximate_snp.vcf* %s/*/*array %s/*/*unmapped.bed_positions %s" % (
+        # args.output_folder, args.output_folder, args.output_folder, args.output_folder, args.output_folder,
+        # args.output_folder, args.output_folder, core_temp_dir)
+        call(cp_command, logger)
+
+        """ Decompress zipped files in core temp folder"""
+        list_of_gzipped_files = glob.glob("%s/*.gz" % core_temp_dir)
+        keep_logging('Decompressing gzipped files in %s\n' % core_temp_dir, 'Decompressing gzipped files in %s\n' % core_temp_dir, logger, 'info')
+        gzipped_command_list = []
+        for i in list_of_gzipped_files:
+            gzipped_command_list.append("gzip -df %s" % i)
+
+        """ Set the number of cores variable for Parallel-local mode """
+        num_cores = multiprocessing.cpu_count()
+        results = Parallel(n_jobs=num_cores)(delayed(run_command_list)(i) for i in gzipped_command_list)
+
+        """ Generate a custom vcf file list to process for core prep step. If file is not provided, it will consider all the samples in output folder"""
+        """ Perform Sanity check to confirm that variant calling results are present in core temp folder """
+        if args.filenames:
+            list_of_files = get_filenames(args.dir, args.type, args.filenames, args.analysis_name, args.suffix)
+            list_of_vcf_files = generate_custom_vcf_file_list(sorted(list_of_files), logger)
+            keep_logging('\nNumber of final variant call vcf files: %s\n' % len(list_of_vcf_files), '\nNumber of final variant call vcf files: %s\n' % len(list_of_vcf_files), logger, 'info')
+            #keep_logging('Make sure the number of final variant call vcf files looks correct', 'Make sure the number of final variant call vcf files looks correct', logger, 'info')
+            #keep_logging('Running core_prep on these files...', 'Running core_prep on these files...', logger, 'info')
+            with open("%s/vcf_filenames" % core_temp_dir, 'w') as out_fp:
+                for file in list_of_vcf_files:
+                    out_fp.write(os.path.basename(file)+'\n')
+            out_fp.close()
+        else:
+            keep_logging('\nChecking if all the variant calling results exists in %s\n' % core_temp_dir, '\nChecking if all the variant calling results exists in %s\n' % core_temp_dir, logger, 'info')
+            #call("ls -1a %s/*.vcf_no_proximate_snp.vcf > %s/vcf_filenames" % (core_temp_dir, core_temp_dir), logger)
+            try:
+                list_cmd = "ls -1a %s/*.vcf_no_proximate_snp.vcf" % core_temp_dir
+                list_of_files = subprocess.check_output(list_cmd, shell=True)
+
+                keep_logging('Number of final variant call vcf files: %s\n' % len(list_of_files.splitlines()), 'Number of final variant call vcf files: %s\n' % len(list_of_files.splitlines()), logger, 'info')
+                #keep_logging('Make sure the number of final variant call vcf files looks correct', 'Make sure the number of final variant call vcf files looks correct', logger, 'info')
+                #keep_logging('Running core_prep on these files...', 'Running core_prep on these files...', logger, 'info')
+                with open("%s/vcf_filenames" % core_temp_dir, 'w') as out_fp:
+                    for file in list_of_files.splitlines():
+                        out_fp.write(os.path.basename(file)+'\n')
+                out_fp.close()
+            except:
+                keep_logging('Error: The variant calling results were not found in %s. Please check if variant calling step finished properly without any errors. '
+                             'This can be done by checking if all the variant call results folder contains final variant call vcf file: *.vcf_no_proximate_snp.vcf file' % core_temp_dir, 'Error: The variant calling results were not found in %s. Please check if variant calling step finished properly without any errors. '
+                                                                                                                                                                                              'This can be done by checking if all the variant call results folder contains final variant call vcf file: *.vcf_no_proximate_snp.vcf file' % core_temp_dir, logger, 'exception')
+                exit()
+
+
+
+            # list_cmd = "ls -1a %s/*.vcf_no_proximate_snp.vcf" % core_temp_dir
+            # list_of_files = subprocess.check_output(list_cmd, shell=True)
+            # print list_of_files
+            # with open("%s/vcf_filenames" % core_temp_dir, 'w') as out_fp:
+            #     for file in list_of_files.splitlines():
+            #         out_fp.write(os.path.basename(file)+'\n')
+            # out_fp.close()
+        reference = ConfigSectionMap(args.index, Config)['ref_path'] + "/" + ConfigSectionMap(args.index, Config)['ref_name']
+        core_prep_pipeline_cmd = run_core_prep_analysis(core_temp_dir, reference, args.analysis_name, log_unique_time, args.cluster, logger, config_file)
+        core_All_cmds.append(core_prep_pipeline_cmd)
+        time_taken = datetime.now() - start_time_2
+        keep_logging('Core Prep Logs will be recorded in file with extension log.txt in %s\n' % core_prep_logs_folder, 'Core Prep Logs will be recorded in file with extension log.txt in %s\n' % core_prep_logs_folder, logger, 'info')
+        #keep_logging('Total Time taken: {}'.format(time_taken), 'Total Time taken: {}'.format(time_taken), logger, 'info')
+
+        """ Generate Core Variants from core_prep intermediate files """
+        core_logs_folder = logs_folder + "/core"
+        make_sure_path_exists(core_logs_folder)
+        logger = generate_logger(core_logs_folder, args.analysis_name, log_unique_time)
+        #keep_logging('START: Extract core snps and generate diagnostic plots','START: Extract core snps and generate diagnostic plots', logger, 'info')
+        call("cp %s %s/%s_%s_config_copy.txt" % (config_file, core_logs_folder, log_unique_time, args.analysis_name),
+             logger)
+        core_temp_dir = args.output_folder + "/core_temp_dir/"
+        core_results_dir = args.output_folder + "/%s_core_results/" % log_unique_time
+        make_sure_path_exists(core_results_dir)
+
+        # Commented Out: 2018-10-23
+        # if args.filenames:
+        #     list_of_files = get_filenames(args.dir, args.type, args.filenames, args.analysis_name, args.suffix)
+        #     list_of_vcf_files = generate_custom_vcf_file_list(sorted(list_of_files), logger)
+        #     list_of_label_files = []
+        #
+        #     for i in list_of_vcf_files:
+        #         list_of_label_files.append(i + '_positions_label')
+        #     if len(list_of_label_files) == len(list_of_vcf_files):
+        #         for i in list_of_label_files:
+        #             if os.stat("%s/%s" % (core_temp_dir, i)).st_size == 0:
+        #                 keep_logging('The file {} is empty. Please rerun core_prep step again.\n'.format(i),
+        #                              'The file {} is empty. Please rerun core_prep step again.\n'.format(i), logger,
+        #                              'exception')
+        #                 exit()
+        #     else:
+        #         keep_logging('Problem in core_prep results. Rerun the core_prep step\n',
+        #                      'Problem in core_prep results. Rerun the core_prep step\n', logger, 'exception')
+        #         exit()
+        #
+        #     with open("%s/vcf_filenames" % core_temp_dir, 'w') as out_fp:
+        #         for file in list_of_vcf_files:
+        #             out_fp.write(os.path.basename(file) + '\n')
+        #     out_fp.close()
+        # else:
+        #     list_of_label_files = glob.glob("%s/*_no_proximate_snp.vcf_positions_label" % core_temp_dir)
+        #     list_of_vcf_files = glob.glob("%s/*_filter2_final.vcf_no_proximate_snp.vcf" % core_temp_dir)
+        #     # print sorted(list_of_vcf_files)
+        #     if len(list_of_label_files) == len(list_of_vcf_files):
+        #         for i in list_of_label_files:
+        #             if os.stat(i).st_size == 0:
+        #                 keep_logging('The file {} is empty. Please rerun core_prep step again.\n'.format(i),
+        #                              'The file {} is empty. Please rerun core_prep step again.\n'.format(i), logger,
+        #                              'exception')
+        #                 exit()
+        #     else:
+        #         keep_logging('Problem in core_prep results. Rerun the core_prep step\n',
+        #                      'Problem in core_prep results. Rerun the core_prep step\n', logger, 'exception')
+        #         exit()
+        #     with open("%s/vcf_filenames" % core_temp_dir, 'w') as out_fp:
+        #         for file in sorted(list_of_vcf_files):
+        #             out_fp.write(os.path.basename(file) + '\n')
+        #     out_fp.close()
+
+        reference = ConfigSectionMap(args.index, Config)['ref_path'] + "/" + ConfigSectionMap(args.index, Config)[
+            'ref_name']
+
+        # Parse Phaster results file to extract phage region.
+        if ConfigSectionMap("functional_filters", Config)['apply_functional_filters'] == "yes":
+            keep_logging('Preparing Functional class filters\n', 'Preparing Functional class filters\n', logger,
+                         'info')
+            functional_class_filter_positions = "%s/Functional_class_filter_positions.txt" % core_temp_dir
+            f1 = open(functional_class_filter_positions, 'w+')
+            if ConfigSectionMap("functional_filters", Config)['find_phage_region'] == "yes":
+                phage_region_positions = parse_phaster(reference, core_temp_dir, logger, Config)
+                with open(phage_region_positions, 'rU') as fp:
+                    for line in fp:
+                        f1.write(line)
+                fp.close()
+            if ConfigSectionMap("functional_filters", Config)['find_repetitive_region'] == "yes":
+                # Find repeat regions in reference genome
+                repeat_region_positions = nucmer_repeat(reference, core_temp_dir, logger, Config)
+                with open(repeat_region_positions, 'rU') as fp:
+                    for line in fp:
+                        f1.write(line)
+                fp.close()
+            if ConfigSectionMap("functional_filters", Config)['mask_region'] == "yes":
+                # Mask custom region/Positions
+                if ConfigSectionMap("functional_filters", Config)['mask_file']:
+                    mask_file = ConfigSectionMap("functional_filters", Config)['mask_file']
+                    mask_extension = os.path.splitext(mask_file)[1]
+                    if mask_extension == ".bed":
+                        mask_positions_file = mask_regions(mask_file, core_temp_dir, logger, Config)
+                        keep_logging(
+                            'Mask positions in this file %s will be filtered out' % mask_positions_file,
+                            'Mask positions in this file %s will be filtered out' % mask_positions_file,
+                            logger, 'info')
+                    else:
+                        # mask_positions_file = mask_file
+                        os.system("cp %s %s/mask_positions.txt" % (mask_file, core_temp_dir))
+                        mask_positions_file = "%s/mask_positions.txt" % core_temp_dir
+                        keep_logging(
+                            'Mask positions in this file %s will be filtered out' % mask_positions_file,
+                            'Mask positions in this file %s will be filtered out' % mask_positions_file,
+                            logger, 'info')
+                    with open(mask_positions_file, 'rU') as fp:
+                        for line in fp:
+                            f1.write(line)
+                    fp.close()
+            f1.close()
+
+        core_pipeline_cmd = run_core_analysis(core_temp_dir, reference, args.analysis_name, log_unique_time, args.cluster, logger,
+                          core_results_dir, config_file)
+        core_All_cmds.append(core_pipeline_cmd)
+        time_taken = datetime.now() - start_time_2
+        keep_logging('Core Step Logs will be recorded in file with extension log.txt in %s\n' % core_logs_folder,
+                     'Core Step Logs will be recorded in file with extension log.txt in %s\n' % core_logs_folder, logger, 'info')
+        #keep_logging('Total Time taken: {}'.format(time_taken), 'Total Time taken: {}'.format(time_taken), logger,'info')
+
+        """ Generate Reports and organize core results folder """
+        report_logs_folder = logs_folder + "/report"
+        make_sure_path_exists(report_logs_folder)
+        logger = generate_logger(report_logs_folder, args.analysis_name, log_unique_time)
+        #keep_logging('START: Generating alignment and variant calling report','START: Generating alignment and variant calling report', logger, 'info')
+        call("cp %s %s/%s_%s_config_copy.txt" % (config_file, report_logs_folder, log_unique_time, args.analysis_name),
+             logger)
+        core_temp_dir = args.output_folder + "/core_temp_dir/"
+        # core_results_dir = args.output_folder + "/%s_core_results/" % log_unique_time
+        # make_sure_path_exists(core_results_dir)
+        proc = subprocess.Popen(["ls -1ad %s/*_core_results | tail -n1" % args.output_folder], stdout=subprocess.PIPE,
+                                shell=True)
+        (out2, err2) = proc.communicate()
+        core_results_dir = out2.strip()
+        #keep_logging('Moving final results and reports to %s' % core_results_dir,'Moving final results and reports to %s' % core_results_dir, logger, 'info')
+
+        list_of_label_files = glob.glob("%s/*_label" % core_temp_dir)
+        list_of_vcf_files = []
+        with open("%s/vcf_filenames" % core_temp_dir, 'r') as out_fp:
+            for line in out_fp:
+                list_of_vcf_files.append(line)
+        for i in list_of_label_files:
+            if os.stat(i).st_size == 0:
+                keep_logging('The file {} is empty. Please rerun core_prep step again.\n'.format(i),
+                             'The file {} is empty. Please rerun core_prep step again.\n'.format(i), logger,
+                             'exception')
+                exit()
+        reference = ConfigSectionMap(args.index, Config)['ref_path'] + "/" + ConfigSectionMap(args.index, Config)[
+            'ref_name']
+        run_report_analysis_cmd = run_report_analysis(core_temp_dir, reference, args.analysis_name, log_unique_time, args.cluster, logger,
+                            core_results_dir, config_file)
+        time_taken = datetime.now() - start_time_2
+        keep_logging('Report Step Logs will be recorded in file with extension log.txt in %s\n' % report_logs_folder,
+                     'Report Step Logs will be recorded in file with extension log.txt in %s\n' % report_logs_folder, logger, 'info')
+        #keep_logging('Total Time taken: {}'.format(time_taken), 'Total Time taken: {}'.format(time_taken), logger,'info')
+
+        core_All_cmds.append(run_report_analysis_cmd)
+
+        """ Generate Trees """
+        tree_logs_folder = logs_folder + "/tree"
+        make_sure_path_exists(tree_logs_folder)
+        logger = generate_logger(tree_logs_folder, args.analysis_name, log_unique_time)
+        #keep_logging('START: Generating FastTree and RAxML trees', 'START: Generating FastTree and RAxML trees', logger,'info')
+        call("cp %s %s/%s_%s_config_copy.txt" % (config_file, tree_logs_folder, log_unique_time, args.analysis_name),
+             logger)
+        core_temp_dir = args.output_folder + "/core_temp_dir/"
+        # core_results_dir = args.output_folder + "/%s_core_results/" % log_unique_time
+        proc = subprocess.Popen(["ls -1ad %s/*_core_results | tail -n1" % args.output_folder], stdout=subprocess.PIPE,
+                                shell=True)
+        (out2, err2) = proc.communicate()
+        core_results_dir = out2.strip()
+        #keep_logging('Generating RaxML and fasttree trees in %s/trees' % core_results_dir,'Generating RaxML and fasttree trees in %s/trees' % core_results_dir, logger, 'info')
+        print core_results_dir
+        list_of_label_files = glob.glob("%s/*_label" % core_temp_dir)
+        list_of_vcf_files = []
+        with open("%s/vcf_filenames" % core_temp_dir, 'r') as out_fp:
+            for line in out_fp:
+                list_of_vcf_files.append(line)
+        for i in list_of_label_files:
+            if os.stat(i).st_size == 0:
+                keep_logging('The file {} is empty. Please rerun core_prep step again.\n'.format(i),
+                             'The file {} is empty. Please rerun core_prep step again.\n'.format(i), logger,
+                             'exception')
+                exit()
+        reference = ConfigSectionMap(args.index, Config)['ref_path'] + "/" + ConfigSectionMap(args.index, Config)[
+            'ref_name']
+        run_tree_analysis_cmd = run_tree_analysis(core_temp_dir, reference, args.analysis_name, log_unique_time,
+                                                  args.cluster, logger, core_results_dir, config_file)
+        time_taken = datetime.now() - start_time_2
+        keep_logging('Tree Step Logs will be recorded in file with extension log.txt in %s\n' % tree_logs_folder,
+                     'Tree Step Logs will be recorded in file with extension log.txt in %s\n' % tree_logs_folder, logger, 'info')
+        #keep_logging('Total Time taken: {}'.format(time_taken), 'Total Time taken: {}'.format(time_taken), logger,'info')
+
+        core_All_cmds.append(run_tree_analysis_cmd)
+
+        combine_job_name = core_temp_dir + "/" + log_unique_time + "_" + args.analysis_name + "_core_All.pbs"
+
+        Pbs_model_lines = "#PBS -M %s\n#PBS -m %s\n#PBS -V\n#PBS -l %s\n#PBS -q %s\n#PBS -A %s\n#PBS -l qos=flux\n" \
+                          % (ConfigSectionMap("scheduler", Config)['email'],
+                             ConfigSectionMap("scheduler", Config)['notification'],
+                             ConfigSectionMap("scheduler", Config)['large_resources'],
+                             ConfigSectionMap("scheduler", Config)['queue'],
+                             ConfigSectionMap("scheduler", Config)['flux_account'])
+
+        with open(combine_job_name, 'w') as out:
+            job_title = "#PBS -N %s_%s_core_All" % (log_unique_time, args.analysis_name)
+            out.write(job_title + '\n')
+            out.write(Pbs_model_lines + '\n')
+            out.write(
+                "#  Change to the directory you submitted from\nif [ -n \"$PBS_O_WORKDIR\" ]; then cd $PBS_O_WORKDIR; fi" + '\n')
+            out.write("echo \"PBS working directory: $PBS_O_WORKDIR\"" + '\n')
+            out.write("cd %s" % core_temp_dir + '\n')
+            for cmds in core_All_cmds:
+                out.write(cmds + '\n')
+        out.close()
+
+
     elif "core_prep" in args.steps:
+        """ Set Up Core Prep logs folder/logger object, cluster mode and copy config files to it"""
         core_prep_logs_folder = logs_folder + "/core_prep"
         make_sure_path_exists(core_prep_logs_folder)
         core_temp_dir = args.output_folder + "/core_temp_dir/"
         logger = generate_logger(core_prep_logs_folder, args.analysis_name, log_unique_time)
         keep_logging('START: Copying variant calling results to %s and running core_prep step.' % core_temp_dir, 'START: Copying variant calling results to %s and running core_prep step.' % core_temp_dir, logger, 'info')
         call("cp %s %s/%s_%s_config_copy.txt" % (config_file, core_prep_logs_folder, log_unique_time, args.analysis_name), logger)
-
         make_sure_path_exists(core_temp_dir)
         keep_logging('Copying vcf files to %s' % core_temp_dir, 'Copying vcf files to %s' % core_temp_dir, logger, 'info')
-        cp_command = "cp %s/*/*_vcf_results/*_filter2_indel_final.vcf %s/*/*_vcf_results/*_aln_mpileup_raw.vcf %s/*/*_vcf_results/*_raw.vcf_5bp_indel_removed.vcf* %s/*/*_vcf_results/*filter2_final.vcf* %s/*/*_vcf_results/*vcf_no_proximate_snp.vcf* %s/*/*_vcf_results/*array %s/*/*_vcf_results/*unmapped.bed_positions %s" % (args.output_folder, args.output_folder, args.output_folder, args.output_folder, args.output_folder, args.output_folder, args.output_folder, core_temp_dir)
+        cp_command = "cp %s/*/*_vcf_results/*_filter2_indel_final.vcf %s/*/*_vcf_results/*_aln_mpileup_raw.vcf %s/*/*_vcf_results/*_raw.vcf_5bp_indel_removed.vcf* %s/*/*_vcf_results/*filter2_final.vcf* %s/*/*_vcf_results/*vcf_no_proximate_snp.vcf* %s/*/*_vcf_results/*array %s/*/*unmapped.bed_positions %s" % (args.output_folder, args.output_folder, args.output_folder, args.output_folder, args.output_folder, args.output_folder, args.output_folder, core_temp_dir)
         # cp_command = "cp %s/*/*_filter2_indel_final.vcf %s/*/*_aln_mpileup_raw.vcf %s/*/*_raw.vcf_5bp_indel_removed.vcf* %s/*/*filter2_final.vcf* %s/*/*vcf_no_proximate_snp.vcf* %s/*/*array %s/*/*unmapped.bed_positions %s" % (
         # args.output_folder, args.output_folder, args.output_folder, args.output_folder, args.output_folder,
         # args.output_folder, args.output_folder, core_temp_dir)
         call(cp_command, logger)
+
+        """ Decompress zipped files in core temp folder"""
         list_of_gzipped_files = glob.glob("%s/*.gz" % core_temp_dir)
         keep_logging('Decompressing gzipped files in %s' % core_temp_dir, 'Decompressing gzipped files in %s' % core_temp_dir, logger, 'info')
         gzipped_command_list = []
         for i in list_of_gzipped_files:
             gzipped_command_list.append("gzip -df %s" % i)
+
+        """ Set the number of cores variable for Parallel-local mode """
         num_cores = multiprocessing.cpu_count()
         results = Parallel(n_jobs=num_cores)(delayed(run_command_list)(i) for i in gzipped_command_list)
+
+        """ Generate a custom vcf file list to process for core prep step. If file is not provided, it will consider all the samples in output folder"""
+        """ Perform Sanity check to confirm that variant calling results are present in core temp folder """
         if args.filenames:
             list_of_files = get_filenames(args.dir, args.type, args.filenames, args.analysis_name, args.suffix)
             list_of_vcf_files = generate_custom_vcf_file_list(sorted(list_of_files), logger)
-
-
             keep_logging('Number of final variant call vcf files: %s' % len(list_of_vcf_files), 'Number of final variant call vcf files: %s' % len(list_of_vcf_files), logger, 'info')
             keep_logging('Make sure the number of final variant call vcf files looks correct', 'Make sure the number of final variant call vcf files looks correct', logger, 'info')
             keep_logging('Running core_prep on these files...', 'Running core_prep on these files...', logger, 'info')
-
             with open("%s/vcf_filenames" % core_temp_dir, 'w') as out_fp:
                 for file in list_of_vcf_files:
                     out_fp.write(os.path.basename(file)+'\n')
@@ -617,12 +957,13 @@ def run_tree_analysis(core_temp_dir, reference, analysis_name, log_unique_time,
             #         out_fp.write(os.path.basename(file)+'\n')
             # out_fp.close()
         reference = ConfigSectionMap(args.index, Config)['ref_path'] + "/" + ConfigSectionMap(args.index, Config)['ref_name']
-        run_core_prep_analysis(core_temp_dir, reference, args.analysis_name, log_unique_time, args.cluster, logger, config_file)
+        core_prep_pipeline_cmd = run_core_prep_analysis(core_temp_dir, reference, args.analysis_name, log_unique_time, args.cluster, logger, config_file)
         time_taken = datetime.now() - start_time_2
         keep_logging('Logs were recorded in file with extension log.txt in %s' % core_prep_logs_folder, 'Logs were recorded in file with extension log.txt in %s' % core_prep_logs_folder, logger, 'info')
         keep_logging('Total Time taken: {}'.format(time_taken), 'Total Time taken: {}'.format(time_taken), logger, 'info')
 
     elif "core" in args.steps:
+        """ Generate Core Variants from core_prep intermediate files """
         core_logs_folder = logs_folder + "/core"
         make_sure_path_exists(core_logs_folder)
         logger = generate_logger(core_logs_folder, args.analysis_name, log_unique_time)
@@ -713,9 +1054,7 @@ def run_tree_analysis(core_temp_dir, reference, analysis_name, log_unique_time,
                     fp.close()
             f1.close()
 
-
-
-        run_core_analysis(core_temp_dir, reference, args.analysis_name, log_unique_time, args.cluster, logger, core_results_dir, config_file)
+        core_pipeline_cmd = run_core_analysis(core_temp_dir, reference, args.analysis_name, log_unique_time, args.cluster, logger, core_results_dir, config_file)
         time_taken = datetime.now() - start_time_2
         keep_logging('Logs were recorded in file with extension log.txt in %s' % core_logs_folder, 'Logs were recorded in file with extension log.txt in %s' % core_logs_folder, logger, 'info')
         keep_logging('Total Time taken: {}'.format(time_taken), 'Total Time taken: {}'.format(time_taken), logger, 'info')
@@ -746,7 +1085,7 @@ def run_tree_analysis(core_temp_dir, reference, analysis_name, log_unique_time,
                 keep_logging('The file {} is empty. Please rerun core_prep step again.\n'.format(i), 'The file {} is empty. Please rerun core_prep step again.\n'.format(i), logger, 'exception')
                 exit()
         reference = ConfigSectionMap(args.index, Config)['ref_path'] + "/" + ConfigSectionMap(args.index, Config)['ref_name']
-        run_report_analysis(core_temp_dir, reference, args.analysis_name, log_unique_time, args.cluster, logger, core_results_dir, config_file)
+        run_report_analysis_cmd = run_report_analysis(core_temp_dir, reference, args.analysis_name, log_unique_time, args.cluster, logger, core_results_dir, config_file)
         time_taken = datetime.now() - start_time_2
         keep_logging('Logs were recorded in file with extension log.txt in %s' % report_logs_folder, 'Logs were recorded in file with extension log.txt in %s' % report_logs_folder, logger, 'info')
         keep_logging('Total Time taken: {}'.format(time_taken), 'Total Time taken: {}'.format(time_taken), logger, 'info')
@@ -776,7 +1115,7 @@ def run_tree_analysis(core_temp_dir, reference, analysis_name, log_unique_time,
                 keep_logging('The file {} is empty. Please rerun core_prep step again.\n'.format(i), 'The file {} is empty. Please rerun core_prep step again.\n'.format(i), logger, 'exception')
                 exit()
         reference = ConfigSectionMap(args.index, Config)['ref_path'] + "/" + ConfigSectionMap(args.index, Config)['ref_name']
-        run_tree_analysis(core_temp_dir, reference, args.analysis_name, log_unique_time, args.cluster, logger, core_results_dir, config_file)
+        run_tree_analysis_cmd = run_tree_analysis(core_temp_dir, reference, args.analysis_name, log_unique_time, args.cluster, logger, core_results_dir, config_file)
         time_taken = datetime.now() - start_time_2
         keep_logging('Logs were recorded in file with extension log.txt in %s' % tree_logs_folder, 'Logs were recorded in file with extension log.txt in %s' % tree_logs_folder, logger, 'info')
         keep_logging('Total Time taken: {}'.format(time_taken), 'Total Time taken: {}'.format(time_taken), logger, 'info')

From 64932f2591128fabea056bee7dc77b3dfceee6d2 Mon Sep 17 00:00:00 2001
From: Ali Pirani <alipirani88@gmail.com>
Date: Wed, 24 Oct 2018 06:37:06 -0400
Subject: [PATCH 4/9] Update README.md

---
 README.md | 135 ++++++++++--------------------------------------------
 1 file changed, 25 insertions(+), 110 deletions(-)

diff --git a/README.md b/README.md
index 65e139f..f3a288c 100644
--- a/README.md
+++ b/README.md
@@ -74,27 +74,17 @@ You can run a part of the pipeline by customizing the order of the -steps argume
 
 Note: The order of variant calling steps needs to be sequential. If skipping any of the steps, make sure those skipped steps had previously finished without any errors.
 
+**2. Generate various Core/Non-core SNP consensus, SNP/Indel Matrices and recombination filtering with Gubbins:**
 
-**2. Preparing files for Core SNP extraction and diagnostics purposes:**
+Option ***core_All***: This will run all the core SNP consensus/matrix generating steps.
 
+This step will run in sequential order and generate:
 
-Option ***core_prep***: Run this step before running the last core steps. This will generate all the intermediate data files required for core SNP matrix/consensus.
+- intermediate data files required for generating core SNP matrix/consensus.
+- Various data matrices will be generated during this step that can be used for diagnosing variant filter criterias and their impact on overall distribution of core variants.
+- prefix_core_results directory under the output directory which will be the final results folder.
+- Gubbins recombination filtered consensus fasta files and RaxML/Iqtree trees generated from this recombination filtered consensus.
 
-**3. Generate core SNP consensus and data matrix for diagnostics plots:**
-
-Option ***core***: This step will generate core SNP/Indel Matrix and different types of consensus fasta files. Various data matrices will be generated during this step that can be used for diagnosing variant filter criterias and their impact on the overall distribution core variants. 
-
-**4. Generate report and aggregate results for the pipeline:**
-
-Option ***report*** : This step will aggregate the results in prefix_core_results directory under the output directory.
-
-**4. Generate report and aggregate results for the pipeline:**
-
-Option ***report***: This step will aggregate and move final results to prefix_core_results directory under the output directory.
-
-**5. Phylogenetic reconstruction and recombination filtering using FastTree/RAxML/Gubbins:**
-
-Option ***tree***: This step will generate a FastTree and a RAxML tree from pre-recombination filtered consensus files. If the -gubbins option is set to yes, it will run gubbins on all final consensus files.
 
 ## Command line options
 
@@ -166,15 +156,8 @@ Possible options for the -cluster option (Supported system: pbs):
 
 ***parallel-local***:  This option will run the pipeline and analyze samples in parallel but on a local system. This is preferred for an input sample size of less than 20  and a multiple core local system.
 
-***cluster***: This option will run the pipeline on a single cluster. This option is similar to local but will rather run on a cluster node. It will not make use of multiple cores present on a cluster. Use this option for small numbers of samples or for testing purposes or for small numbers of large size samples which require multiple cores to analyze individual samples.
+***cluster***: The pipeline is optimized for this option. When this option is set, the pipeline will run variant call jobs for each sample on individual small compute clusters or on a single large cluster for core snp generation step. 
 
-***parallel-cluster***: The variant call step (All) is optimized for this option. When this option is set, the pipeline will run variant call jobs for each sample on an individual compute cluster. When you set this option for each step in the pipeline, make sure all the jobs submitted by the pipeline at each step is completed before proceeding to another step. You can check the status of the job with: 
-
-```
-qstat -u USERNAME  
-```
-
-Note: Use parallel-cluster mode for All/clean,align,post-align,varcall,filter,stats steps. Use cluster/parallel-local mode for core_prep and core steps. parallel-cluster and cluster will be merged in the next release.
 
 ## Quick Start
 
@@ -188,7 +171,7 @@ See option resources in the scheduler section of the [config](https://github.com
 - Run variant calling step (All) on a set of PE reads with default parameters
 
 ```
-python /nfs/esnitkin/bin_group/pipeline/Github/variant_calling_pipeline/variant_call.py -type PE -readsdir /Path-To-Your/test_readsdir/ -outdir /Path/test_output_core/ -analysis output_prefix -index MRSA_USA_300 -steps All -cluster parallel-cluster
+python /nfs/esnitkin/bin_group/pipeline/Github/variant_calling_pipeline/variant_call.py -type PE -readsdir /Path-To-Your/test_readsdir/ -outdir /Path/test_output_core/ -analysis output_prefix -index MRSA_USA_300 -steps All -cluster cluster
 
 ```
 
@@ -196,117 +179,53 @@ The above command will run the variant calling (step 1) pipeline on a set of PE
 
 The results of variant calling will be placed in an individual folder generated for each sample in the output directory. A log file for each sample will be generated and can be found in each sample folder inside the output directory. A single log file of this step will be generated in the main output directory. For more information on log file prefix and convention, please refer to the [log](#log) section below.
 
-- Run the core_prep step to generate files for core SNP calling.
-
-Run this steps to generate various intermediate files that will be used for generating core SNPs.
-
-```
-python /nfs/esnitkin/bin_group/pipeline/Github/variant_calling_pipeline/variant_call.py -type PE -readsdir /Path-To-Your/test_readsdir/ -outdir /Path/test_output_core/ -analysis output_prefix -index MRSA_USA_300 -steps core_prep -cluster cluster
-
-```
-
-- Run the core step to generate final core SNP consensus fasta files.
+- Generate core SNPs/Matrices from variant calling results 
 
 Since this step compares multiple files simultaneously and involves multiple I/O operations, it is recommended to provide higher memory compute resources. 
 
 example:
 
 ```
-nodes=1:ppn=4,mem=47000mb,walltime=24:00:00
+nodes=1:ppn=12,mem=47000mb,walltime=250:00:00
 ```
 
 Replace the resources option in the scheduler section of the config file with the above line before running the command.
 
 ```
-python /nfs/esnitkin/bin_group/pipeline/Github/variant_calling_pipeline/variant_call.py -type PE -readsdir /Path-To-Your/test_readsdir/ -outdir /Path/test_output_core/ -analysis output_prefix -index MRSA_USA_300 -steps core -cluster cluster
-
-```
-
-- Run the report step to aggregate results under the \*_core_results folder
-
-```
-python /nfs/esnitkin/bin_group/pipeline/Github/variant_calling_pipeline/variant_call.py -type PE -readsdir /Path-To-Your/test_readsdir/ -outdir /Path/test_output_core/ -analysis output_prefix -index MRSA_USA_300 -steps report -cluster cluster
-
-```
-
-- Run the tree step to generate FastTree and RAxML phylogenetic trees and recombination filtering using Gubbins
-
-```
-python /nfs/esnitkin/bin_group/pipeline/Github/variant_calling_pipeline/variant_call.py -type PE -readsdir /Path-To-Your/test_readsdir/ -outdir /Path/test_output_core/ -analysis output_prefix -index MRSA_USA_300 -steps tree -cluster cluster -gubbins yes
+python /nfs/esnitkin/bin_group/pipeline/Github/variant_calling_pipeline/variant_call.py -type PE -readsdir /Path-To-Your/test_readsdir/ -outdir /Path/test_output_core/ -analysis output_prefix -index MRSA_USA_300 -steps core_All -cluster cluster -gubbins yes
 
 ```
 
 ## Output Files
 
-All the final results from the report step will be saved under the date_time_core_results directory under the output folder. 
-
+All the final results will be saved under the date_time_core_results directory under the output folder. There will be three directories with different types of results.
 
 ```
 
-2018_01_13_13_18_03_core_results
+2018_10_23_17_25_08_core_results
 ├── core_snp_consensus
-│   ├── consensus_allele_variant_positions
-│   ├── consensus_ref_allele_unmapped_variant
-│   ├── consensus_ref_allele_variant_positions
-│   ├── consensus_ref_variant_positions
-│   ├── consensus_variant_positions
-│   └── core_vcf
 ├── data_matrix
-│   ├── Indel_matrix_allele.csv
-│   ├── Indel_matrix_code.csv
-│   ├── SNP_matrix_allele.csv
-│   ├── SNP_matrix_allele_new.csv
-│   ├── SNP_matrix_code.csv
-│   ├── phage_region_positions.txt
-│   ├── repeat_region_positions.txt
-│   ├── mask_positions.txt
-│   ├── Functional_class_filter_positions.txt
-│   ├── bargraph_counts.txt
-│   ├── bargraph_indel_counts.txt
-│   ├── bargraph_indel_percentage.txt
-│   ├── bargraph_percentage.txt
-│   ├── snpEff_results
-│   └── temp
-├── gubbins
-│   ├── 2018_07_11_14_45_01_KPNIH1_allele_var_consensus.fa
-│   ├── 2018_07_11_14_45_01_KPNIH1_ref_allele_unmapped_consensus.fa
-│   ├── 2018_07_11_14_45_01_KPNIH1_ref_allele_var_consensus.fa
-│   ├── 2018_07_11_14_45_01_KPNIH1_ref_var_consensus.fa
-│   └── 2018_07_11_14_45_01_KPNIH1_var_consensus.fa
-└── trees
+└── gubbins
 
 ```
 
-Four directories will be created after the report step where input for different downstream analyses and matrices for QC will be generated.
-
-### 1. core_snp_consensus
-This folder contain different combinations of core/non-core consensus fasta files for individual samples. The core_vcf folder contains annotated vcf files used for generating the consensus. 
-
-### 2. gubbins
-This folder contains different combinations of core/non-core multi-fasta consensus files generated by merging individual consensus files in core_snp_consensus folder. These multi-fasta consensus will be used as input for Gubbins recombination filtering and RAxML/FatTree phylogenetic tree construction.
-Output files from gubbins will be saved in this directory.
+**core_snp_consensus** The core_vcf folder contains annotated core vcf files used for generating the core SNP consensus. Other folders contains different combination of core/non-core consensus fasta files for individual samples.
 
-**var_consensus.fa:** consensus generated from core variant positions.
+**gubbins** contains different combinations of core/non-core multi-fasta alignments. Alignments with "gubbins.fa" extension will be used as an input for Gubbins. The pipeline will run RaxML and Iqtree on gubbins recombination filtered consensus fasta and the final output from all the three three programs will be saved under this folder.
 
-**ref_var_consensus.fa** full consensus relative to the reference genome generated from core variant positions (final core variants + reference alleles + non-core variants).
+- core_var_aln: alignment generated from only core variant positions.
 
-Note: non-core variant in this consensus refers to positions where a variant was observed but was filtered out for not meeting one of three criteria. Therefore, it will be replaced by the reference allele observed at this position.
+- genome_aln_w_ref_allele_gubbins: genome alignment relative to the reference genome generated from core variant positions (final core variants + reference alleles).
 
-- core variant criteria: Since this position was filtered out in another sample, this position will be regarded as a non-core position.
-- hard variant filters: If the variant called at this position didn't meet hard variant filters such as DP (depth), MQ (mapping quality), FQ (all reads supporting one variant), QUAL (variant quality), proximate_snp (the variant was in close proximity to another variant by 10 bp), they would be filtered out from the final core SNPs.
-- functional filters: If the position falls in one of the three functional class (repetitive, masked or phage region), they would be filtered out from final core SNPs.
+Note: non-core variants will be replaced by reference allele.
 
-**allele_var_consensus.fa:** consensus generated from all unique variant positions that were called in any sample regardless of it being a core/non-core position. This will contain all core variant positions, non-core variant positions will be substituted with a dash (denoting unmapped) and N’s for not meeting hard variant filters or falling under a functional class filter. Non-core variants that meet all filter parameters will be substituted with the variant allele.
+- noncore_plus_core_variants_aln: alignment contains only non-core and core variant positions. Unmapped position will be denoted by a dash(-), variant position (uncertain) that didn't meet the hard variant filter threshold or fell under functional class filter will be denoted by "N". Variant position that met all filter threshold will be substituted with the variant allele.
 
-**ref_allele_var_consensus.fa** full consensus relative to the reference genome generated from all unique variant positions that were called in any sample regardless of it being a core/non-core position. This will contain all core variant positions, non-core variant positions will be substituted with a dash (denoting unmapped) and N’s for not meeting hard variant filters or falling under a functional class filter. Non-core variants that meet all filter parameters will be substituted with the variant allele. Positions that were unmapped in all samples relative to the reference genome will be denoted by the reference allele.
+- genome_aln_w_alt_allele_unmapped_gubbins: genome alignment relative to the reference genome with positions that were unmapped in all samples relative to the reference genome will be denoted by dashes. It contains all core variant positions, non-core variant positions will be substituted with a dash (denoting unmapped) and N’s for not meeting hard variant filter thresholds or falling under functional class filters. Non-core variants that met all filter thresholds will be substituted with variant allele. 
 
-**ref_allele_unmapped_consensus.fa:** full consensus relative to the reference genome generated from all unique variant positions that were called in any sample. This will contain all core variant positions, non-core variant positions will be substituted with a dash (denoting unmapped) and N’s for not meeting hard variant filters or falling under functional class filters. Non-core variants that meet all filter parameters will be substituted with the variant allele. Positions that were unmapped in all samples relative to the reference genome will be denoted by dashes.
+**data_matrix** This folder contains different types of data matrices and reports that can be queried for variant diagnostics/QC plots. 
 
-
-### 3. data_matrix
-This folder contains different types of data matrices and reports that can be queried for variant diagnostics/QC plots. 
-
-**SNP/Indel Matrix:**
+- matrices/SNP_matrix*.csv:
 
 SNP_matrix_allele.csv and Indel_matrix_allele.csv: contain allele information for each unique variant position (rownames) called in each individual sample (columns). Positions that were unmapped and filtered out are replaced by the reference allele.
 
@@ -325,7 +244,7 @@ The different status codes are:
 | 3 | non-core or true variant but filtered out due to another sample |
 
 
-**Functional class:**
+- Functional_annotation_results:
 
 phage_region_positions.txt contains positions identified by Phaster as phage regions.
 
@@ -375,10 +294,6 @@ Rscript generate_diagnostics_plots.R
 ![alt tag](https://github.com/alipirani88/variant_calling_pipeline/blob/master/img/barplot_DP.png)
 
 
-### 4. trees
-All the scripts used for running RAxML/FastTree and their output are saved in this directory. Multi-fasta consensus files (pre-recombination filtered) residing in the gubbins folder will be used for constructing RAxML/FastTree trees.
-
-
 <!-- 
 barplot.pdf
 

From 780ddd856ff1d04be1686cf8c65d3ae925b6faa0 Mon Sep 17 00:00:00 2001
From: Ali Pirani <alipirani88@gmail.com>
Date: Wed, 24 Oct 2018 06:40:06 -0400
Subject: [PATCH 5/9] Update README.md

---
 README.md | 18 +++++++-----------
 1 file changed, 7 insertions(+), 11 deletions(-)

diff --git a/README.md b/README.md
index f3a288c..c38b6b2 100644
--- a/README.md
+++ b/README.md
@@ -225,13 +225,11 @@ Note: non-core variants will be replaced by reference allele.
 
 **data_matrix** This folder contains different types of data matrices and reports that can be queried for variant diagnostics/QC plots. 
 
-- matrices/SNP_matrix*.csv:
+- matrices/SNP_matrix_allele.csv and Indel_matrix_allele.csv: contain allele information for each unique variant position (rownames) called in each individual sample (columns). Positions that were unmapped and filtered out are replaced by the reference allele.
 
-SNP_matrix_allele.csv and Indel_matrix_allele.csv: contain allele information for each unique variant position (rownames) called in each individual sample (columns). Positions that were unmapped and filtered out are replaced by the reference allele.
+- matrices/SNP_matrix_allele_new.csv will also contain allele information for each unique variant position (rownames) called in each individual sample (columns) except the positions that were unmapped and filtered out will be substituted with dash (-) and N's.
 
-SNP_matrix_allele_new.csv will also contain allele information for each unique variant position (rownames) called in each individual sample (columns) except the positions that were unmapped and filtered out will be substituted with dash (-) and N's.
-
-SNP_matrix_code.csv and Indel_matrix_code.csv: contain one of the five status codes for each unique variant position (rownames) called in individual sample (columns). 
+- matrices/SNP_matrix_code.csv and Indel_matrix_code.csv: contain one of the five status codes for each unique variant position (rownames) called in individual sample (columns). 
 
 The different status codes are: 
 
@@ -244,15 +242,13 @@ The different status codes are:
 | 3 | non-core or true variant but filtered out due to another sample |
 
 
-- Functional_annotation_results:
-
-phage_region_positions.txt contains positions identified by Phaster as phage regions.
+- Functional_annotation_results/phage_region_positions.txt contains positions identified by Phaster as phage regions.
 
-repeat_region_positions.txt contains positions identified by nucmer as tandem repeats.
+- Functional_annotation_results/repeat_region_positions.txt contains positions identified by nucmer as tandem repeats.
 
-mask_positions.txt contains positions set by the user to mask from the final core position list.
+- Functional_annotation_results/mask_positions.txt contains positions set by the user to mask from the final core position list.
 
-Functional_class_filter_positions.txt is an aggregated unique list of positions that fall under repeat, mask and phage region (REPEAT_MASK_PHAGE).
+- Functional_annotation_results/Functional_class_filter_positions.txt is an aggregated unique list of positions that fall under repeat, mask and phage region (REPEAT_MASK_PHAGE).
 
 **Bargraph matrices**
 

From ccf0dc4bf60be1275672a31a2512d4e22c68d623 Mon Sep 17 00:00:00 2001
From: Ali Pirani <alipirani88@gmail.com>
Date: Wed, 24 Oct 2018 11:54:50 -0400
Subject: [PATCH 6/9] Update README.md

---
 README.md | 58 +++++++++++++++++++++++++------------------------------
 1 file changed, 26 insertions(+), 32 deletions(-)

diff --git a/README.md b/README.md
index c38b6b2..f344cbc 100644
--- a/README.md
+++ b/README.md
@@ -93,10 +93,10 @@ This step will run in sequential order and generate:
 usage: variant_call.py [-h] -type TYPE -readsdir DIR -outdir OUTPUT_FOLDER
                        -index INDEX [-steps STEPS] -analysis ANALYSIS_NAME
                        [-config CONFIG] [-suffix SUFFIX]
-                       [-filenames FILENAMES] [-cluster CLUSTER]
-                       [-clean CLEAN] [-extract_unmapped EXTRACT_UNMAPPED]
-                       [-datadir DATADIR] [-snpeff_db SNPEFF_DB]
-                       [-debug_mode DEBUG_MODE] [-gubbins GUBBINS]
+                       [-filenames FILENAMES] [-cluster CLUSTER] [-clean]
+                       [-extract_unmapped EXTRACT_UNMAPPED] [-datadir DATADIR]
+                       [-snpeff_db SNPEFF_DB] [-debug_mode DEBUG_MODE]
+                       [-gubbins GUBBINS]
 
 Variant Calling pipeline for Illumina PE/SE data.
 
@@ -105,39 +105,33 @@ optional arguments:
 
 Required arguments:
   -type TYPE            Type of reads: SE or PE
-  -readsdir DIR         Path to sequencing reads data directory. NOTE: Provide full/absolute path.
-  -outdir OUTPUT_FOLDER Output folder path ending with output directory name to save the results. Creates a new output directory path if it doesn't exist. NOTE: Provide full/absolute path.
-  -index INDEX          Reference index name. Most frequently used reference genomes index options: KPNIH1 | MRSA_USA_300 | MRSA_USA_100 | CDIFF_630 | paris. Make sure the paths are properly set in config file.
-  -steps STEPS          Variant calling steps in sequential order.
-                        1.   All: This will run all the steps starting from cleaning the reads to variant calling;
-                        2.   clean,align,post-align,varcall,filter,stats : This will also run all steps from cleaning to variant calling. 
-                        You can also run part of the pipeline by giving, for example, "align,post-align,varcall,filter,stats" which will skip the cleaning part.
-                        The order must be sequential while using this option. Also, if skipping any of the steps, make sure you have the results already present in your output folder.
-                        3.   coverage_depth_stats: Run only depth of coverage stats module after the cleaning and read mapping steps
-                        4.   core_prep: Run this step before running the core steps. This will prepare the data required for generating core SNPs
-                        5.   core: extract core snps and generate diagnostics plot data matrices to explore filtered snps.
-  -analysis ANALYSIS_NAME Unique analysis name that will be used as a prefix when saving results and log files.
+  -readsdir DIR         Path to Sequencing Reads Data directory. NOTE: Provide full/absolute path.
+  -outdir OUTPUT_FOLDER
+                        Output Folder Path ending with output directory name to save the results. Creates a new output directory path if it doesn't exist. NOTE: Provide full/absolute path.
+  -index INDEX          Reference Index Name. Most Frequently used reference genomes index options: KPNIH1 | MRSA_USA_300 | MRSA_USA_100 | CDIFF_630 | paris Make sure the paths are properly set in config file
+  -steps STEPS          Variant Calling Steps in sequential order.
+                        1.   All: Run all variant calling  steps starting from trimming the reads, mapping, post-processing the alignments and calling variants;
+                        2.   core_All: Extract core snps and generate different types of alignments, SNP/Indel Matrices and diagnostics plots to explore filtered snps.
+  -analysis ANALYSIS_NAME
+                        Unique analysis name that will be used as prefix to saving results and log files.
 
 Optional arguments:
-  -config CONFIG        Path to config file. Make sure to check config settings before running the pipeline
+  -config CONFIG        Path to Config file, Make sure to check config settings before running pipeline
   -suffix SUFFIX        Fastq reads suffix such as fastq, fastq.gz, fq.gz, fq; Default: fastq.gz
   -filenames FILENAMES  fastq filenames with one single-end filename per line. 
-                        If the type is set to PE, it will detect the second paired-end filename with the suffix from the first filename. 
-                        Useful for running variant calling pipeline on selected files in a reads directory or extracting core snps for selected samples in the input reads directory. 
-                        Otherwise the pipeline will consider all the samples available in the reads directory.
-  -cluster CLUSTER      Run variant calling pipeline in one of the four modes. Default: local. The suggested mode for core snp is a cluster that will run all the steps in parallel with the available cores. Make sure to provide a large memory node for this option
-                        The possible modes are: cluster/parallel-cluster/parallel-local/local
-                        cluster: Runs all the jobs on a single large cluster. This will mimic the local run but rather on a large compute node.
-                        parallel-cluster: Submit variant call jobs for each sample in parallel on compute nodes. This mode is no available for core snp extraction step.
-                        parallel-local: Run variant call jobs for each sample in parallel locally.
-                        local: Run variant call jobs locally.
-                        Make sure to check if the [scheduler] section in the config file is set up correctly for your cluster.
-  -clean CLEAN          Clean up intermediate files. Default: OFF
-  -extract_unmapped     EXTRACT_UNMAPPED
-                        Extract unmapped reads, assemble them and detect antimicrobial resistance (AMR) genes using ariba
+                        If the type is set to PE, it will detect the second paired-end filename with the suffix from first filename. 
+                        Useful for running variant calling pipeline on selected files in a reads directory or extracting core snps for selected samples in input reads directory. 
+                        Otherwise the pipeline will consider all the samples available in reads directory.
+  -cluster CLUSTER      Run variant calling pipeline in one of the four modes. Default: local. Suggested mode for core snp is "cluster" that will run all the steps in parallel with the available cores. Make sure to provide a large memory node for this option
+                        The possible modes are: cluster/parallel-local/local
+                        Set your specific hpc cluster parameters in config file under the [scheduler] section. Supports only PBS scheduling system. 
+  -clean                clean up intermediate files. Default: OFF
+  -extract_unmapped EXTRACT_UNMAPPED
+                        Extract unmapped reads, assemble it and detect AMR genes using ariba
   -datadir DATADIR      Path to snpEff data directory
-  -snpeff_db SNPEFF_DB  Name of pre-built snpEff database to use for annotation
-  -debug_mode DEBUG_MODE yes/no for debug mode
+  -snpeff_db SNPEFF_DB  Name of pre-build snpEff database to use for Annotation
+  -debug_mode DEBUG_MODE
+                        yes/no for debug mode
   -gubbins GUBBINS      yes/no for running gubbins
 
 ```

From af2829a05c3d2194e7589906ae1a7239ad2b4e78 Mon Sep 17 00:00:00 2001
From: Ali Pirani <alipirani88@gmail.com>
Date: Wed, 24 Oct 2018 12:16:17 -0400
Subject: [PATCH 7/9] Removing unused folders

---
 modules/cluster_based_prep/log_modules.py     |  30 -
 .../cluster_based_prep/logging_subprocess.py  |  41 --
 .../prep_cluster_calling.py                   |  97 ---
 other/FQ_analysis.py                          |  78 ---
 other/README.md                               |   2 -
 other/__init__.py                             |   1 -
 other/allele_frequency_analysis.py            |  93 ---
 other/config_backup                           | 160 -----
 other/config_default_21dec                    | 172 -----
 other/config_gatk                             |  93 ---
 other/pipeline.py.save                        | 139 ----
 other/pipeline_gatk.py                        | 101 ---
 plots/Sample_barplot.png                      | Bin 227887 -> 0 bytes
 variant_call_backup.py                        | 643 -----------------
 variant_call_debug.py                         | 651 ------------------
 15 files changed, 2301 deletions(-)
 delete mode 100644 modules/cluster_based_prep/log_modules.py
 delete mode 100644 modules/cluster_based_prep/logging_subprocess.py
 delete mode 100644 modules/cluster_based_prep/prep_cluster_calling.py
 delete mode 100755 other/FQ_analysis.py
 delete mode 100755 other/README.md
 delete mode 100755 other/__init__.py
 delete mode 100755 other/allele_frequency_analysis.py
 delete mode 100755 other/config_backup
 delete mode 100755 other/config_default_21dec
 delete mode 100755 other/config_gatk
 delete mode 100755 other/pipeline.py.save
 delete mode 100755 other/pipeline_gatk.py
 delete mode 100644 plots/Sample_barplot.png
 delete mode 100644 variant_call_backup.py
 delete mode 100644 variant_call_debug.py

diff --git a/modules/cluster_based_prep/log_modules.py b/modules/cluster_based_prep/log_modules.py
deleted file mode 100644
index 9289934..0000000
--- a/modules/cluster_based_prep/log_modules.py
+++ /dev/null
@@ -1,30 +0,0 @@
-__author__ = 'alipirani'
-
-import logging
-from datetime import datetime
-
-def keep_logging(pmessage, lmessage, logger, mode):
-    print(pmessage)
-    if mode == 'warning':
-        logger.warning(lmessage)
-    elif mode == 'info':
-        logger.info(lmessage)
-    elif mode == 'exception':
-        logger.exception(lmessage)
-    elif mode == 'debug':
-        logger.debug(lmessage)
-    else:
-        logger.error(lmessage)
-
-
-def generate_logger(output_folder, analysis_name, log_unique_time):
-    # Create a new logger; create a file handler; create a logging format; add the handlers to the logger
-    logger = logging.getLogger(__name__)
-    logger.setLevel(logging.DEBUG)
-    #handler = logging.FileHandler('{}/{}_{}_.log.txt'.format(args.output_folder, args.analysis_name, datetime.now().strftime('%Y_%m_%d_%H_%M_%S')))
-    handler = logging.FileHandler('{}/{}_{}.log.txt'.format(output_folder, log_unique_time, analysis_name))
-    handler.setLevel(logging.DEBUG)
-    formatter = logging.Formatter('%(asctime)s - %(name)s - %(levelname)s - %(message)s')
-    handler.setFormatter(formatter)
-    logger.addHandler(handler)
-    return logger
\ No newline at end of file
diff --git a/modules/cluster_based_prep/logging_subprocess.py b/modules/cluster_based_prep/logging_subprocess.py
deleted file mode 100644
index 4aee619..0000000
--- a/modules/cluster_based_prep/logging_subprocess.py
+++ /dev/null
@@ -1,41 +0,0 @@
-# https://gist.github.com/hangtwenty/6390750
-import sys
-if sys.version_info < (3, 2):
-    import subprocess32 as sp
-else:
-    import subprocess as sp
-import select
-import logging
-from logging import DEBUG, ERROR
-
-def call(popenargs, logger, stderr_log_level=logging.ERROR, stdout_log_level=logging.DEBUG, **kwargs):
-    """
-    Variant of subprocess.call that accepts a logger instead of stdout/stderr,
-    and logs stdout messages via logger.debug and stderr messages via
-    logger.error.
-    """
-
-    try:
-
-        child = sp.Popen(popenargs, stdout=sp.PIPE, stderr=sp.PIPE, shell=True, **kwargs)
-
-        log_level = {child.stdout: stdout_log_level, child.stderr: stderr_log_level}
-        #print log_level
-        def check_io():
-            ready_to_read = select.select([child.stdout, child.stderr], [], [], 1000)[0]
-            #print ready_to_read
-            for io in ready_to_read:
-                line = io.readline()
-                #print line
-                if line:
-                    #print log_level[io]
-                    logger.log(log_level[io], line[:-1])
-
-        # keep checking stdout/stderr until the child exits
-        while child.poll() is None:
-            check_io()
-        check_io()  # check again to catch anything after the process exits
-    except Exception as e:
-        raise(e)
-
-    return child.wait()
\ No newline at end of file
diff --git a/modules/cluster_based_prep/prep_cluster_calling.py b/modules/cluster_based_prep/prep_cluster_calling.py
deleted file mode 100644
index 8fc34b0..0000000
--- a/modules/cluster_based_prep/prep_cluster_calling.py
+++ /dev/null
@@ -1,97 +0,0 @@
-import sys
-import os
-from os import path
-sys.path.append(path.dirname(path.dirname(path.dirname(path.abspath(__file__)))))
-import argparse
-import errno
-import glob
-import re
-import multiprocessing
-import subprocess as subprocess
-from datetime import datetime
-from joblib import Parallel, delayed
-from modules.logging_subprocess import *
-from modules.log_modules import *
-from argparse import RawTextHelpFormatter
-
-# Command Line Argument Parsing
-def parser():
-    parser = argparse.ArgumentParser(description='\nPrepare Cluster based Reference genome and config files\n', formatter_class=RawTextHelpFormatter)
-    required = parser.add_argument_group('Required arguments')
-    optional = parser.add_argument_group('Optional arguments')
-    required.add_argument('-cluster_names', action='store', dest="cluster_names", help='Provide a file describing cluster group. Each line represents a cluster and each sample name in a cluster is seperated by a tab.', required=True)
-    required.add_argument('-report', action='store', dest="report", help='comma-seperated Assembly report', required=True)
-    required.add_argument('-assemblies', action='store', dest="assemblies", help='Path to final assembly fasta files', required=True)
-    required.add_argument('-config', action='store', dest="index", help='path to config file', required=True)
-    required.add_argument('-reads_dir', action='store', dest="reads_dir", help='path to reads directory', required=True)
-    return parser
-
-
-
-
-def prep_cluster_names():
-    report_dict_contigs = {}
-    report_dict_length = {}
-    os.system("mkdir filename_meta")
-    os.system("mkdir filename_ls_commands")
-    with open(args.report) as fp:
-        for line in fp:
-            line = line.strip()
-            line_split = line.split(',')
-            first_part = re.sub("_S.*", "", line_split[0])
-            report_dict_contigs[first_part] = line_split[1]
-            report_dict_length[first_part] = line_split[2]
-    print "preparing cluster group reference genomes"
-    cluster_groups = {}
-    count = 0
-    with open(args.cluster_names) as fp:
-        for line in fp:
-            count = count + 1
-            line = line.strip()
-            line_split = line.split('\t')
-            cluster_groups[count] = line_split
-        fp.close()
-    f = open("cluster_reference_genome.sh", 'w+')
-    f_temp = open("cluster_temp.txt", 'w+')
-    for key in cluster_groups.keys():
-        cluster_no = key
-        cluster_dir = "cluster_" + str(key) + "_size_" + str(len(cluster_groups[key]))
-        os.system("mkdir %s" % cluster_dir)
-        cluster_file = "cluster_" + str(key) + "_size_" + str(len(cluster_groups[key])) + "_meta.txt"
-        cluster_file_names = "cluster_" + str(key) + "_size_" + str(len(cluster_groups[key])) + "_filenames.txt"
-        f1 = open("%s/%s" % (cluster_dir, cluster_file), 'w+')
-        f2 = open("%s/%s" % (cluster_dir, cluster_file_names), 'w+')
-        for i in cluster_groups[key]:
-            if i in report_dict_length.keys():
-                print_string = "cluster_" + str(key) + "_size_" + str(len(cluster_groups[key])) + ",%s,%s,%s" % (i, report_dict_contigs[i], report_dict_length[i])
-                f1.write(print_string + '\n')
-                cmd = "basename %s/%s_*R1.fastq.gz\n" % (args.reads_dir, i)
-                proc = subprocess.Popen([cmd], stdout=subprocess.PIPE, shell=True)
-                (out, err) = proc.communicate()
-                f2.write("%s" % (out))
-            else:
-                print "%s: Not found" % i
-        get_best_ref_cmd = "sort -t',' -k3n %s/%s | head -n1 | cut -d',' -f2\n" % (cluster_dir, cluster_file)
-        f.write(get_best_ref_cmd)
-        f_temp.write("cluster_" + str(key) + '\n')
-
-
-
-
-
-
-
-
-
-
-# Start of Main Method/Pipeline
-if __name__ == '__main__':
-    # Set up logging modules and config file
-    start_time = datetime.now().strftime('%Y-%m-%d %H:%M:%S')
-    start_time_2 = datetime.now()
-    args = parser().parse_args()
-    global log_unique_time
-    log_unique_time = datetime.now().strftime('%Y_%m_%d_%H_%M_%S')
-    global logger
-    if args.cluster_names:
-        prep_cluster_names()
\ No newline at end of file
diff --git a/other/FQ_analysis.py b/other/FQ_analysis.py
deleted file mode 100755
index afb40b4..0000000
--- a/other/FQ_analysis.py
+++ /dev/null
@@ -1,78 +0,0 @@
-__author__ = 'alipirani'
-
-import sys
-import os
-import argparse
-import errno
-
-
-################################################### Command Line Argument Parsing ###################################################
-parser = argparse.ArgumentParser(description='FQ analysis: Applying modified vcf filters to retail low FQ values for further analysis')
-parser.add_argument('-final_raw_vcf', action='store', dest="final_raw_vcf", help='Path to final_raw_vcf(5bp snp indel vcf file)', required=True)
-parser.add_argument('-o', action='store', dest="output_folder", help='Output Path ending with output directory name to save the results', required=True)
-parser.add_argument('-index', action='store', dest="index", help='Reference Index Name. Full path to reference', required=True)
-args = parser.parse_args()
-############################################################### End #################################################################
-
-analysis = args.final_raw_vcf.replace("_aln_mpileup_raw.vcf_5bp_indel_removed.vcf", "")
-out_path = args.output_folder
-reference = args.index
-final_raw_vcf = args.final_raw_vcf
-
-def gatk_filter2(final_raw_vcf, out_path, analysis, reference):
-    gatk_filter2_parameter_expression = "MQ > 50 && QUAL > 100 && DP > 15"
-    gatk_filter2_command = "java -jar ~/bin/GenomeAnalysisTK-3.3-0/GenomeAnalysisTK.jar -T VariantFiltration -R %s -o %s/%s_filter2_gatk.vcf --variant %s --filterExpression \"%s\" --filterName PASS_filter2" % (reference, out_path, analysis, final_raw_vcf, gatk_filter2_parameter_expression)
-    print "\n\nRunning Command: [%s]\n\n" % gatk_filter2_command
-    os.system(gatk_filter2_command)
-    filter_flag_command = "grep '#\|PASS_filter2' %s/%s_filter2_gatk.vcf > %s/%s_filter2_final.vcf" % (out_path, analysis, out_path, analysis)
-    os.system(filter_flag_command)
-    gatk_filter2_final_vcf = "%s/%s_filter2_final.vcf" % (out_path, analysis)
-    return gatk_filter2_final_vcf
-
-
-
-def remove_proximate_snps(gatk_filter2_final_vcf_file, out_path, analysis, reference):
-    all_position = []
-    remove_proximate_position_array = []
-    gatk_filter2_final_vcf_file_no_proximate_snp = gatk_filter2_final_vcf_file + "_no_proximate_snp.vcf"
-    with open(gatk_filter2_final_vcf_file, 'rU') as csv_file:
-        for line in csv_file:
-            if not line.startswith('#'):
-                line_array = line.split('\t')
-                all_position.append(line_array[1])
-    for position in all_position:
-        position_index = all_position.index(position)
-        next_position_index = position_index + 1
-
-        if next_position_index < len(all_position):
-            diff = int(all_position[next_position_index]) - int(position)
-            if diff < 10:
-                #print position + "  " + all_position[next_position_index]
-                if position not in remove_proximate_position_array and all_position[next_position_index] not in remove_proximate_position_array:
-                    remove_proximate_position_array.append(int(position))
-                    remove_proximate_position_array.append(int(all_position[next_position_index]))
-    #print remove_proximate_position_array
-    f1=open(gatk_filter2_final_vcf_file_no_proximate_snp, 'w+')
-    with open(gatk_filter2_final_vcf_file, 'rU') as csv_file2:
-        for line in csv_file2:
-            if line.startswith('gi') or line.startswith('MRSA_8058'):
-               line_array = line.split('\t')
-               if int(line_array[1]) not in remove_proximate_position_array:
-                   #print line_array[1]
-                   #print line_array[1]
-                   print_string = line
-                   f1.write(print_string)
-            else:
-                print_string = line
-                f1.write(print_string)
-    gatk_filter2_final_vcf_file_no_proximate_snp_positions = gatk_filter2_final_vcf_file + "_no_proximate_snp.vcf_positions_array"
-    f2=open(gatk_filter2_final_vcf_file_no_proximate_snp_positions, 'w+')
-    for i in remove_proximate_position_array:
-        position_print_string = str(i) + "\n"
-        f2.write(position_print_string)
-    return gatk_filter2_final_vcf_file_no_proximate_snp
-#remove_proximate_snps(gatk_filter2_final_vcf_file, out_path, analysis)
-
-gatk_filter2_final_vcf_file = gatk_filter2(final_raw_vcf, out_path, analysis, reference)
-
-remove_proximate_snps(gatk_filter2_final_vcf_file, out_path, analysis, reference)
diff --git a/other/README.md b/other/README.md
deleted file mode 100755
index edb0d76..0000000
--- a/other/README.md
+++ /dev/null
@@ -1,2 +0,0 @@
-# varcall_umich
-VariantCalling
diff --git a/other/__init__.py b/other/__init__.py
deleted file mode 100755
index 0b188d7..0000000
--- a/other/__init__.py
+++ /dev/null
@@ -1 +0,0 @@
-__author__ = 'alipirani'
diff --git a/other/allele_frequency_analysis.py b/other/allele_frequency_analysis.py
deleted file mode 100755
index 26d1f36..0000000
--- a/other/allele_frequency_analysis.py
+++ /dev/null
@@ -1,93 +0,0 @@
-from __future__ import division
-__author__ = 'alipirani'
-
-##Pending Changes
-
-import sys
-import os
-import argparse
-import errno
-import subprocess
-
-################################################### Command Line Argument Parsing ###################################################
-parser = argparse.ArgumentParser(description='Allele Frequency analysis: For the given variant positions; extract DP4 information from raw vcf file and calculate reference allele fraction and variant allele fraction')
-parser.add_argument('-raw_mpileup_file', action='store', dest="raw_mpileup_file", help='Path to raw_mpileup_file', required=True)
-parser.add_argument('-o', action='store', dest="output_folder", help='Output Path ending with output directory name to save the results', required=True)
-parser.add_argument('-position', action='store', dest="position", help='File containing positions', required=True)
-args = parser.parse_args()
-############################################################### End #################################################################
-print "Processing: %s..." % args.raw_mpileup_file
-position_array = []
-
-with open(args.position) as fp:
-        for line in fp:
-            line = line.strip()
-            position_array.append(int(line))
-out_file = args.output_folder + args.raw_mpileup_file + "_ref_fraction"
-#print position_array
-f1=open(out_file, 'w+')
-for i in position_array:
-    cmd = "grep -w \'" + str(i) + "\' " + args.raw_mpileup_file
-    proc = subprocess.Popen([cmd], stdout=subprocess.PIPE, shell=True)
-    (out, err) = proc.communicate()
-    if not out:
-        ref_fraction = "REF"
-	    f1.write(str(ref_fraction) + "\n")
-    else:
-        line_array = out.split('\t')
-        #print line_array[1]
-        format_string_array = line_array[7].split(';')
-        #print format_string_array
-        for i in format_string_array:
-            if i.startswith('DP4='):
-                allele_freq = i.split(',')
-                forward_ref = allele_freq[0].replace('DP4=', '')
-                reverse_ref = allele_freq[1]
-                forward_nonref = allele_freq[2]
-                reverse_nonref = allele_freq[3]
-                total = int(forward_ref) + int(reverse_ref) + int(forward_nonref) + int(reverse_nonref)
-                #print total
-                ref_alleles = (int(forward_ref) + int(reverse_ref))
-		        ref_fraction = ref_alleles / total
-                #print ref_alleles
-                #print total
-                f1.write(str(ref_fraction) + "\n")
-                #print ref_fraction
-
-
-
-
-
-
-
-
-
-
-
-
-
-#with open(args.raw_mpileup_file, 'rU') as csv_file2:
-        # f1=open(out_file, 'w+')
-        # for line in csv_file2:
-         #    if line.startswith('gi') or line.startswith('MRSA_8058'):
-         #        #print line
-         #        line_array = line.split('\t')
-		# #print line_array[1]
-         #        if int(line_array[1]) in position_array:
-         #            print line_array[1]
-         #            format_string_array = line_array[7].split(';')
-         #            print format_string_array
-         #            for i in format_string_array:
-         #                if i.startswith('DP4='):
-         #                    allele_freq = i.split(',')
-         #                    forward_ref = allele_freq[0].replace('DP4=', '')
-         #                    reverse_ref = allele_freq[1]
-         #                    forward_nonref = allele_freq[2]
-         #                    reverse_nonref = allele_freq[3]
-         #                    total = int(forward_ref) + int(reverse_ref) + int(forward_nonref) + int(reverse_nonref)
-		# 	                #print total
-         #                    ref_alleles = (int(forward_ref) + int(reverse_ref))
-         #                    print ref_alleles
-         #                    print total
-         #                    f1.write(str(ref_fraction) + "\n")
-         #                    #print ref_fraction
diff --git a/other/config_backup b/other/config_backup
deleted file mode 100755
index f0047a9..0000000
--- a/other/config_backup
+++ /dev/null
@@ -1,160 +0,0 @@
-# Set which tools to use in pipeline:
-[pipeline]
-# Options for Aligner:bwa / smalt / bowtie
-aligner: bwa
-# Options for variant_caller: samtoolswithpostalignbam / gatkhaplotypecaller /samtools
-variant_caller: samtools
-########################################################################################################################
-
-# Set bin folder path. Please make sure all the executables are placed in bin folder. Also make sure the path for individual tools are correct.
-[bin_path]
-binbase: /Users/alipirani/Documents/bin/bin_varcall/
-
-########################################################################################################################
-
-# Set Parameters for individual tools. Set the binbase of each tool: This should be the folder name of respective tools where the executables for each resp. tool resides.
-# Set parameter for Trimmomatic
-[Trimmomatic]
-trimmomatic_bin: /Trimmomatic/
-adaptor_filepath: adapters/TruSeq3-PE.fa
-seed_mismatches: 2
-palindrome_clipthreshold: 30
-simple_clipthreshold: 10
-minadapterlength: 8
-#change this to true and see the effect on alignment
-keep_both_reads: true
-window_size: 4
-window_size_quality: 20
-minlength: 40
-#headcrop_length: 8
-colon: :
-#clean_filenames: forward_paired.fq.gz,forward_unpaired.fq.gz,reverse_paired.fq.gz,reverse_unpaired.fq.gz
-targetlength: 125
-crop_length: 40
-f_p: forward_paired.fq.gz
-f_up: forward_unpaired.fq.gz
-r_p: reverse_paired.fq.gz
-r_up: reverse_unpaired.fq.gz
-
-[bwa]
-bwa_bin: /bwa-0.7.12/
-cores: 8
-base_cmd: bwa
-algorithm: mem
-index: index
-RG_header: -R
-Mark_splithits: -M
-
-[samtools]
-samtools_bin: /samtools-1.2/
-base_cmd: samtools
-#minimum mapping quality
-#change parameter S to -t SP and D to -t DP
-mpileup_parameters: -ug -f
-faiindex: faidx
-#-q30 -B -E -C50
-
-[bcftools]
-bcftools_bin: /bcftools-1.2/
-base_cmd: bcftools
-call_parameters: -vg
-
-[picard]
-picard_bin: /picard-tools-1.130/
-base_cmd: picard.jar
-
-[gatk]
-gatk_bin: /GenomeAnalysisTK-3.3-0/
-base_cmd: GenomeAnalysisTK.jar
-haplotype_parameters: -T HaplotypeCaller --genotyping_mode DISCOVERY
-#changes: 12th August
-gatk_filter1_parameter_expression = FQ < 40.00 && MQ > 20 && QUAL > 50 && DP > 15
-gatk_filter2_parameter_expression = FQ < 0.025 && MQ > 50 && QUAL > 100 && DP > 15
-#changed gatk_filter2_parameter_expression DP 15 from 10 that was used in VRE samples.
-
-
-
-
-[vcftools]
-vcftools_perl_bin: /vcftools_0.1.12b/perl/
-tabix_bin: /tabix-0.2.6/
-vcftools_bin: /vcftools_0.1.12b/bin/
-
-
-[qualimap]
-qualimap_bin: /qualimap/
-base_cmd: qualimap
-
-
-
-
-
-
-
-
-########################################################################################################################
-
-# Reference Genome to be used for pipeline
-# Set path for already indexed reference genome
-
-#Name of the reference genome. Provide this value with -index_name option.
-[KP_NTUH_chr]
-# Name of reference genome fasta file.
-Ref_Name: KP_NTUH_chr.fasta
-# path to the reference genome fasta file.
-Ref_Path: /Users/alipirani/Documents/bin/bin_varcall/bin_varcall/reference/KP_NTUH_chr/
-
-# Name of the reference genome. Provide this value with -index_name argument.
-[KPNIH1]
-# Name of reference genome fasta file.
-Ref_Name: KPNIH1.fasta
-# path to the reference genome fasta file.
-Ref_Path: /Users/alipirani/Documents/bin/bin_varcall/reference/KPNIH1/
-
-
-# Name of the reference genome. Provide this value with -index_name argument.
-[KPNIH32]
-# Name of reference genome fasta file.
-Ref_Name: KPNIH32.fasta
-# path to the reference genome fasta file.
-Ref_Path: /Users/alipirani/Documents/bin/bin_varcall/reference//KPNIH32/
-
-
-# Name of the reference genome. Provide this value with -index_name argument.
-[aus]
-# Name of reference genome fasta file.
-Ref_Name: Efae_aus0004_genome.fa
-# path to the reference genome fasta file.
-Ref_Path: /Users/alipirani/Documents/bin/bin_varcall/reference//aus/
-
-
-# Name of the reference genome. Provide this value with -index_name argument.
-[EPI51]
-# Name of reference genome fasta file.
-Ref_Name: Efae_EPI51_060509_genome.fa
-# path to the reference genome fasta file.
-Ref_Path: /Users/alipirani/Documents/bin/bin_varcall/reference//EPI51/
-
-
-# Name of the reference genome. Provide this value with -index_name argument.
-[EnGen0178]
-# Name of reference genome fasta file.
-Ref_Name: EnGen0178_genome.fa
-# path to the reference genome fasta file.
-Ref_Path: /Users/alipirani/Documents/bin/bin_varcall/reference//EnGen0178/
-
-
-# Name of the reference genome. Provide this value with -index_name argument.
-[EnGen0377]
-# Name of reference genome fasta file.
-Ref_Name: EnGen0377_genome.fa
-# path to the reference genome fasta file.
-Ref_Path: /Users/alipirani/Documents/bin/bin_varcall/reference//EnGen0377/
-
-[ECNIH3]
-# Name of reference genome fasta file.
-Ref_Name: ECNIH3.fa
-# path to the reference genome fasta file.
-Ref_Path: /home/apirani/bin/reference//ECNIH3/
-
-########################################################################################################################
\ No newline at end of file
diff --git a/other/config_default_21dec b/other/config_default_21dec
deleted file mode 100755
index 4e905a4..0000000
--- a/other/config_default_21dec
+++ /dev/null
@@ -1,172 +0,0 @@
-# Set which tools to use in pipeline:
-[pipeline]
-# Options for Aligner:bwa / smalt / bowtie
-aligner: bwa
-# Options for variant_caller: samtoolswithpostalignbam / gatkhaplotypecaller /samtools
-variant_caller: samtools
-########################################################################################################################
-
-# Set bin folder path. Please make sure all the executables are placed in bin folder. Also make sure the path for individual tools are correct.
-[bin_path]
-binbase: /home2/apirani/bin/
-
-########################################################################################################################
-
-# Set Parameters for individual tools. Set the binbase of each tool: This should be the folder name of respective tools where the executables for each resp. tool resides.
-# Set parameter for Trimmomatic
-[Trimmomatic]
-trimmomatic_bin: /Trimmomatic/
-adaptor_filepath: adapters/TruSeq3-PE.fa
-seed_mismatches: 2
-palindrome_clipthreshold: 30
-simple_clipthreshold: 10
-minadapterlength: 8
-#change this to true and see the effect on alignment
-keep_both_reads: true
-window_size: 4
-window_size_quality: 20
-minlength: 40
-headcrop_length: 18
-colon: :
-#clean_filenames: forward_paired.fq.gz,forward_unpaired.fq.gz,reverse_paired.fq.gz,reverse_unpaired.fq.gz
-targetlength: 125
-crop_length: 40
-f_p: forward_paired.fq.gz
-f_up: forward_unpaired.fq.gz
-r_p: reverse_paired.fq.gz
-r_up: reverse_unpaired.fq.gz
-
-[bwa]
-bwa_bin: /bwa-0.7.12/
-cores: 8
-base_cmd: bwa
-algorithm: mem
-index: index
-RG_header: -R
-Mark_splithits: -M
-
-[samtools]
-samtools_bin: /samtools-1.2/
-base_cmd: samtools
-#minimum mapping quality
-#change parameter S to -t SP and D to -t DP
-mpileup_parameters: -ug -f
-faiindex: faidx
-#-q30 -B -E -C50
-
-[bcftools]
-bcftools_bin: /bcftools-1.2/
-base_cmd: bcftools
-call_parameters: -vg
-
-[picard]
-picard_bin: /picard-tools-1.130/
-base_cmd: picard.jar
-
-[gatk]
-gatk_bin: /GenomeAnalysisTK-3.3-0/
-base_cmd: GenomeAnalysisTK.jar
-haplotype_parameters: -T HaplotypeCaller --genotyping_mode DISCOVERY
-#changes: 12th August
-gatk_filter1_parameter_expression = FQ < 40.00 && MQ > 20 && QUAL > 50 && DP > 15
-gatk_filter2_parameter_expression = FQ < 0.025 && MQ > 50 && QUAL > 100 && DP > 15
-#changed gatk_filter2_parameter_expression DP 15 from 10 that was used in VRE samples.
-
-
-
-
-[vcftools]
-#vcftools_perl_bin: /vcftools_0.1.12b/perl/
-vcftools_bin: /vcftools_0.1.12b/bin/
-tabix_bin: /tabix-0.2.6/
-#vcftools_bin: /vcftools_0.1.12b/bin/
-vcftools_perl_bin: /vcftools_0.1.12b/perl/
-
-
-[qualimap]
-qualimap_bin: /qualimap_v2.1/
-base_cmd: qualimap
-
-
-
-
-[bedtools]
-bedtools_bin: /bedtools2-master/bin/
-base_cmd: bedtools
-
-
-
-########################################################################################################################
-
-# Reference Genome to be used for pipeline
-# Set path for already indexed reference genome
-
-#Name of the reference genome. Provide this value with -index_name option.
-[KP_NTUH_chr]
-# Name of reference genome fasta file.
-Ref_Name: KP_NTUH_chr.fasta
-# path to the reference genome fasta file.
-Ref_Path: /Users/alipirani/Documents/bin/bin_varcall/bin_varcall/reference/KP_NTUH_chr/
-
-# Name of the reference genome. Provide this value with -index_name argument.
-[KPNIH1]
-# Name of reference genome fasta file.
-Ref_Name: KPNIH1.fasta
-# path to the reference genome fasta file.
-Ref_Path: /home2/apirani/bin/reference/KPNIH1/
-
-
-# Name of the reference genome. Provide this value with -index_name argument.
-[KPNIH32]
-# Name of reference genome fasta file.
-Ref_Name: KPNIH32.fasta
-# path to the reference genome fasta file.
-Ref_Path: /Users/alipirani/Documents/bin/bin_varcall/reference//KPNIH32/
-
-
-# Name of the reference genome. Provide this value with -index_name argument.
-[aus]
-# Name of reference genome fasta file.
-Ref_Name: Efae_aus0004_genome.fa
-# path to the reference genome fasta file.
-Ref_Path: /Users/alipirani/Documents/bin/bin_varcall/reference//aus/
-
-
-# Name of the reference genome. Provide this value with -index_name argument.
-[EPI51]
-# Name of reference genome fasta file.
-Ref_Name: Efae_EPI51_060509_genome.fa
-# path to the reference genome fasta file.
-Ref_Path: /Users/alipirani/Documents/bin/bin_varcall/reference//EPI51/
-
-
-# Name of the reference genome. Provide this value with -index_name argument.
-[EnGen0178]
-# Name of reference genome fasta file.
-Ref_Name: EnGen0178_genome.fa
-# path to the reference genome fasta file.
-Ref_Path: /Users/alipirani/Documents/bin/bin_varcall/reference//EnGen0178/
-
-
-# Name of the reference genome. Provide this value with -index_name argument.
-[EnGen0377]
-# Name of reference genome fasta file.
-Ref_Name: EnGen0377_genome.fa
-# path to the reference genome fasta file.
-Ref_Path: /Users/alipirani/Documents/bin/bin_varcall/reference//EnGen0377/
-
-[ECNIH3]
-# Name of reference genome fasta file.
-Ref_Name: ECNIH3.fa
-# path to the reference genome fasta file.
-Ref_Path: /home/apirani/bin/reference//ECNIH3/
-
-
-[MRSA_USA_300]
-# Name of reference genome fasta file.
-Ref_Name: MRSA_USA_300.fasta
-# path to the reference genome fasta file.
-Ref_Path: /home2/apirani/bin/reference/MRSA_USA_300
-
-
-########################################################################################################################
diff --git a/other/config_gatk b/other/config_gatk
deleted file mode 100755
index 3241fe7..0000000
--- a/other/config_gatk
+++ /dev/null
@@ -1,93 +0,0 @@
-# Set which tools to use in pipeline:
-[pipeline]
-# Options for Aligner:bwa / smalt / bowtie
-aligner: bwa
-# Options for variant_caller: samtoolswithpostalignbam / gatkhaplotypecaller /samtools
-variant_caller: gatkhaplotypecaller
-########################################################################################################################
-
-# Set bin folder path. Please make sure all the executables are placed in bin folder. Also make sure the path for individual tools are correct.
-[bin_path]
-binbase: /Users/alipirani/Documents/bin/
-
-########################################################################################################################
-
-# Set Parameters for individual tools. Set the binbase of each tool: This should be the folder name of respective tools where the executables for each resp. tool resides.
-# Set parameter for Trimmomatic
-[Trimmomatic]
-trimmomatic_bin: /Trimmomatic/
-adaptor_filepath: adapters/TruSeq3-PE.fa
-seed_mismatches: 2
-palindrome_clipthreshold: 30
-simple_clipthreshold: 10
-minadapterlength: 8
-keep_both_reads: false
-window_size: 4
-window_size_quality: 15
-minlength: 40
-headcrop_length: 8
-colon: :
-#clean_filenames: forward_paired.fq.gz,forward_unpaired.fq.gz,reverse_paired.fq.gz,reverse_unpaired.fq.gz
-targetlength: 125
-crop_length: 40
-f_p: forward_paired.fq.gz
-f_up: forward_unpaired.fq.gz
-r_p: reverse_paired.fq.gz
-r_up: reverse_unpaired.fq.gz
-
-[bwa]
-bwa_bin: /bwa-0.7.12/
-cores: 8
-base_cmd: bwa
-algorithm: mem
-index: index
-RG_header: -R
-Mark_splithits: -M
-
-[samtools]
-samtools_bin: /samtools-1.2/
-base_cmd: samtools
-#minimum mapping quality
-#change parameter S to -t SP and D to -t DP
-mpileup_parameters: -ug -f
-faiindex: faidx
-#-q30 -B -E -C50
-
-[bcftools]
-bcftools_bin: /bcftools-1.2/
-base_cmd: bcftools
-call_parameters: -vg
-
-[picard]
-picard_bin: /picard-tools-1.130/
-base_cmd: picard.jar
-
-[gatk]
-gatk_bin: /GenomeAnalysisTK-3.3-0/
-base_cmd: GenomeAnalysisTK.jar
-haplotype_parameters: -T HaplotypeCaller --genotyping_mode DISCOVERY
-
-[vcftools]
-vcftools_bin: /vcftools_0.1.12b/perl/
-tabix_bin: /tabix-0.2.6/
-
-########################################################################################################################
-
-# Reference Genome to be used for pipeline
-# Set path for already indexed reference genome
-
-#Name of the reference genome. Provide this value with -index_name option.
-[KP_NTUH_chr]
-# Name of reference genome fasta file.
-Ref_Name: KP_NTUH_chr.fasta
-# path to the reference genome fasta file.
-Ref_Path: /Users/alipirani/Documents/bin/reference/KP_NTUH_chr/
-
-# Name of the reference genome. Provide this value with -index_name argument.
-[KPNIH1]
-# Name of reference genome fasta file.
-Ref_Name: KPNIH1.fasta
-# path to the reference genome fasta file.
-Ref_Path: /Users/alipirani/Documents/bin/reference/KPNIH1/
-
-########################################################################################################################
\ No newline at end of file
diff --git a/other/pipeline.py.save b/other/pipeline.py.save
deleted file mode 100755
index 301b4cb..0000000
--- a/other/pipeline.py.save
+++ /dev/null
@@ -1,139 +0,0 @@
-__author__ = 'alipirani'
-
-import sys
-import os
-import argparse
-import errno
-from config_settings import ConfigSectionMap
-from modules/check_subroutines import *
-from modules/stages import *
-from modules/remove_5_bp_snp_indel import *
-from modules/bedtools import *
-
-################################################### Command Line Argument Parsing ###################################################
-parser = argparse.ArgumentParser(description='Variant Calling pipeline for Illumina PE data.')
-parser.add_argument('-PE1', action='store', dest="forward_raw", help='Path to Paired End file 1', required=True)
-parser.add_argument('-PE2', action='store', dest="reverse_raw", help='Path to Paired End file 2', required=True)
-parser.add_argument('-o', action='store', dest="output_folder", help='Output Path ending with output directory name to save the results', required=True)
-parser.add_argument('-analysis', action='store', dest="analysis_name", help='Unique analysis name to save the results', required=True)
-parser.add_argument('-c', action='store', dest="croplength", help='Crop Length in case needed')
-parser.add_argument('-f', action='store', dest="bam_input", help='Input Bam')
-parser.add_argument('-index', action='store', dest="index", help='Reference Index Name. Change this argument in config file and mention the reference header name such as KP_NTUH_chr/KPNIH1/KPNIH32.', required=True)
-#parser.add_argument('-r', action='store', dest="reference", help='Reference Fasta File to build index in case index not built')
-args = parser.parse_args()
-############################################################### End #################################################################
-
-print "\n################## Checking Dependencies ##################\n"
-################################################### Check Subroutines: Arguments, Input files, Reference Index ######################
-reference = ConfigSectionMap(args.index)['ref_path'] + "/" + ConfigSectionMap(args.index)['ref_name']
-out_path = args.output_folder + "/"
-make_sure_path_exists(out_path)
-file_exists(args.forward_raw, args.reverse_raw, reference)
-java_check()
-config_file_backup = "cp ./config %s/%s_config_log" % (out_path, args.analysis_name)
-os.system(config_file_backup)
-################################################################### End ############################################################
-print "\n############# End: Checking Dependencies ##################\n"
-
-
-print "\n################## Cleaning Raw reads using Trimmomatic ##################\n"
-################################################### Stages: Raw data Pre-processing using Trimmomatic ###############################
-trimmomatic(args.forward_raw, args.reverse_raw, out_path, args.croplength)
-####################################################################### End #########################################################
-print "\n############# End: Cleaning Raw reads using Trimmomatic ##################\n"
-
-
-print "\n################## Mapping Reads using BWA ##################\n"
-#################################################### Stages: Alignment ##############################################################
-split_field = prepare_readgroup(args.forward_raw)
-files_to_delete = []
-out_sam = align(args.bam_input, args.output_folder, args.index, split_field, args.analysis_name, files_to_delete)
-#out_sam = "/nfs/esnitkin/Ali/Nextera_XT_lib_samples/varcall/snitkin6_S180_L001_R2_001/snitkin6_S180_L001_R2_001_aln.sam"
-out_sorted_bam = prepare_bam(out_sam, out_path, args.analysis_name, files_to_delete)
-#out_sorted_bam = "%s/%s_aln_marked.bam" % (out_path, args.analysis_name)
-############################################################### End #################################################################
-print "\n############# End: Mapping Reads using BWA ##################\n"
-
-
-print "\n################## Creating BedGraph Coverage ##################\n"
-#################################################### Stages: BedGraph Coverage ######################################################
-bedgraph_coverage(out_sorted_bam, out_path, args.analysis_name, reference)
-only_unmapped_positions_file = bedtools(out_sorted_bam, out_path, args.analysis_name)
-######################################################### End #######################################################################
-print "\n############# End: Creating BedGraph Coverage ##################\n"
-
-
-print "\n################## Variant Calling ########################\n"
-##################################################### Stages: Variant Calling #######################################################
-caller = ConfigSectionMap("pipeline")['variant_caller']
-if caller == "samtoolswithpostalignbam":
-    print "\n################## Variant Calling using Samtools and post-align bam input files ##################\n"
-    out_finalbam = post_align_bam(out_sorted_bam, out_path, args.index, args.analysis_name)
-    final_raw_vcf = variant_calling(out_finalbam, out_path, args.index, args.analysis_name)
-    print "The final raw VCF file: %s" % final_raw_vcf
-    print "\n############################ END: samtoolswithpostalignbam Variant Calling. #######################\n"
-elif caller == "gatkhaplotypecaller":
-    print "\n################## Variant Calling using GATK haplotyper and post-align bam input files ##################\n"
-    out_finalbam = post_align_bam(out_sorted_bam, out_path, args.index, args.analysis_name)
-    final_raw_vcf = variant_calling(out_finalbam, out_path, args.index, args.analysis_name)
-    print "The final raw VCF file: %s" % final_raw_vcf
-    print "\n############################# END: gatkhaplotypecaller Variant Calling. ###################################\n"
-elif caller == "samtools":
-    print "\n################## Variant Calling using Samtools without post-align bam input files.##################\n"
-    final_raw_vcf_mpileup = variant_calling(out_sorted_bam, out_path, args.index, args.analysis_name)
-    #final_raw_vcf_mpileup = "%s/%s_aln_mpileup_raw.vcf" % (out_path, args.analysis_name)
-    final_raw_vcf = remove_5_bp_snp_indel(final_raw_vcf_mpileup, out_path, args.analysis_name, reference)
-    print "The final raw VCF file: %s" % final_raw_vcf
-    print "\n################################ END: samtools Variant Calling. ########################################\n"
-else:
-    print "\nPlease provide Variant Caller name in config file under the section [pipeline].\n Options for Variant caller:\n samtools\nsamtoolswithpostalignbam\ngatkhaplotypecaller\n"
-    exit()
-    usage()
-############################################################ End ####################################################################
-print "\n################## End: Variant Calling ##################\n"
-
-
-print "\n################## Variant Filteration #######################\n"
-#################################################### Stages: Variant Filteration ####################################################
-#filter1_variants(final_raw_vcf, out_path, args.analysis_name, args.index)
-filter2_variants(final_raw_vcf, out_path, args.analysis_name, args.index)
-################################################################## END ##############################################################
-print "\n################## End: Variant Filteration ##################\n"
-
-
-
-print "\n################## Generating Alignment and VCF Statistics #######################\n"
-#################################################### Stages: Statistics #############################################################
-alignment_stats_file = alignment_stats(out_sorted_bam, out_path, args.analysis_name)
-########################################################## End ######################################################################
-print "\n################## Calculating Depth of Coverage ##################################\n"
-gatk_DepthOfCoverage(out_sorted_bam, out_path, args.analysis_name, reference)
-########################################################## End ######################################################################
-################################################### Stages: VCF Statistics ##########################################################
-vcf_stats_file = vcf_stats(final_raw_vcf, out_path, args.analysis_name)
-############################################################################ End ####################################################
-print "\n############### END: Generating Alignment and VCF Statistics ######################\n"
-
-
-
-print "\n################## Generating Qualimap Report #######################\n"
-################################################### Stages: Qualimap ################################################################
-qualimap_report = qualimap(out_sorted_bam, out_path, args.analysis_name)
-########################################################## End ######################################################################
-
-################################################### Stages: Remove Unwanted Intermediate files ######################################
-# print "Removing Imtermediate Files...\n%s" % files_to_delete
-# for files in files_to_delete:
-#     os.remove(files)
-# print "Removing Imtermediate Files...\n%s" % files_to_delete
-# for files in files_to_delete:
-#     os.remove(files)
-############################################################################ End ####################################################
-
-
-
-
-
-
-
-
diff --git a/other/pipeline_gatk.py b/other/pipeline_gatk.py
deleted file mode 100755
index ab8d12d..0000000
--- a/other/pipeline_gatk.py
+++ /dev/null
@@ -1,101 +0,0 @@
-__author__ = 'alipirani'
-# Back up file
-import sys
-import os
-import argparse
-from config_settings import ConfigSectionMap
-from modules.check_subroutines import *
-from modules.stages import *
-
-################################################### Command Line Argument Parsing ########################################################################################################################
-parser = argparse.ArgumentParser(description='Assembly pipeline for Illumina PE data')
-parser.add_argument('-PE1', action='store', dest="forward_raw", help='Paired End file 1', required=True)
-parser.add_argument('-PE2', action='store', dest="reverse_raw", help='Paired End file 2', required=True)
-parser.add_argument('-o', action='store', dest="output_folder", help='Output Path ending with output directory name to save the results', required=True)
-parser.add_argument('-analysis', action='store', dest="analysis_name", help='Unique analysis name to save the results', required=True)
-parser.add_argument('-c', action='store', dest="croplength", help='Crop Length in case needed')
-parser.add_argument('-f', action='store', dest="bam_input", help='Input Bam')
-parser.add_argument('-index_name', action='store', dest="index", help='Reference Index Name', required=True)
-parser.add_argument('-r', action='store', dest="reference", help='Reference Fasta File to build index in case index not built')
-args = parser.parse_args()
-############################################################################ End #########################################################################################################################
-
-################################################### Check Subroutines: Arguments, Input files, Reference Index ###########################################################################################
-reference = ConfigSectionMap(args.index)['ref_path'] + "/" + ConfigSectionMap(args.index)['ref_name']
-out_path = args.output_folder + "/"
-make_sure_path_exists(out_path)
-file_exists(args.forward_raw, args.reverse_raw, reference)
-#fileformat(args.forward_raw, args.reverse_raw, out_path)
-java_check()
-############################################################################ End #########################################################################################################################
-
-
-
-#
-# ################################################### Stages: Raw data Pre-processing using Trimmomatic ####################################################################################################
-# trimmomatic(args.forward_raw, args.reverse_raw, out_path, args.croplength)
-# ############################################################################ End #########################################################################################################################
-#
-#
-# # ################################################### Stages: Alignment ####################################################################################################################################
-# split_field = prepare_readgroup(args.forward_raw)
-# out_sam = align(args.bam_input, args.output_folder, args.index, split_field, args.analysis_name)
-# #out_sam = "~/Desktop/test/aln.sam"
-# out_sorted_bam = prepare_bam(out_sam, out_path, args.analysis_name)
-# #out_sorted_bam = "/Users/alipirani/Desktop/sample_19/aln_sort.bam"
-# # ############################################################################ End #########################################################################################################################
-#
-#
-
-# ################################################### Stages: Variant Calling ##############################################################################################################################
-
-out_sorted_bam = out_path + "/" + args.analysis_name + "_aln_sort_bam"
-caller = ConfigSectionMap("pipeline")['variant_caller']
-#print caller
-if caller == "samtoolswithpostalignbam":
-    print "\n################## Variant Calling using Samtools and post-align bam input files ##################\n"
-    out_finalbam = post_align_bam(out_sorted_bam, out_path, args.index, args.analysis_name)
-    final_raw_vcf = variant_calling(out_finalbam, out_path, args.index, args.analysis_name)
-    print "The final raw VCF file: %s" % final_raw_vcf
-    print "\n############################ END: samtoolswithpostalignbam Variant Calling. #######################\n"
-elif caller == "gatkhaplotypecaller":
-    print "\n################## Variant Calling using GATK haplotyper and post-align bam input files ##################\n"
-    out_finalbam = post_align_bam(out_sorted_bam, out_path, args.index, args.analysis_name)
-    final_raw_vcf = variant_calling(out_finalbam, out_path, args.index, args.analysis_name)
-    print "The final raw VCF file: %s" % final_raw_vcf
-    print "\n############################# END: gatkhaplotypecaller Variant Calling. ###################################\n"
-elif caller == "samtools":
-    print "\n################## Variant Calling using Samtools without post-align bam input files.##################\n"
-    final_raw_vcf = variant_calling(out_sorted_bam, out_path, args.index, args.analysis_name)
-    print "The final raw VCF file: %s" % final_raw_vcf
-    print "\n################################ END: samtools Variant Calling. ########################################\n"
-else:
-    print "\nPlease provide Variant Caller name in config file under the section [pipeline].\n Options for Variant caller:\n samtools\nsamtoolswithpostalignbam\ngatkhaplotypecaller\n"
-    exit()
-############################################################################ End #########################################################################################################################
-
-################################################### Stages: Statistics ##############################################################################################################################
-alignment_stats_file = alignment_stats(out_sorted_bam, out_path)
-#final_vcf_stats = vcf_stats(final_raw_vcf, out_path)
-############################################################################ End #########################################################################################################################
-
-################################################### Stages: VCF Statistics ##############################################################################################################################
-#final_raw_vcf = "/Users/alipirani/Desktop/testing_analysis_name///test_purpose_aln_mpileup_raw.vcf"
-#print final_raw_vcf
-vcf_stats_file = vcf_stats(final_raw_vcf, out_path)
-############################################################################ End #########################################################################################################################
-
-
-################################################### Stages: Remove Unwanted Intermediate files ##############################################################################################################################
-#out_sam = "/Users/alipirani/Desktop/testing_analysis_name///test_purpose_aln.sam"
-#remove_files(args.analysis_name, out_path, out_sam, out_sorted_bam)
-############################################################################ End #########################################################################################################################
-
-
-
-
-
-
-
-
-
diff --git a/plots/Sample_barplot.png b/plots/Sample_barplot.png
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diff --git a/variant_call_backup.py b/variant_call_backup.py
deleted file mode 100644
index 775e9ae..0000000
--- a/variant_call_backup.py
+++ /dev/null
@@ -1,643 +0,0 @@
-__author__ = 'alipirani'
-
-import sys
-import os
-import argparse
-import errno
-import ConfigParser
-import glob
-import re
-import multiprocessing
-import subprocess as subprocess
-from datetime import datetime
-from joblib import Parallel, delayed
-from config_settings import ConfigSectionMap
-from modules.logging_subprocess import *
-from modules.log_modules import *
-from argparse import RawTextHelpFormatter
-
-""" Command Line Argument Parsing """
-def parser():
-    parser = argparse.ArgumentParser(description='\nVariant Calling pipeline for Illumina PE/SE data.\n', formatter_class=RawTextHelpFormatter)
-    required = parser.add_argument_group('Required arguments')
-    optional = parser.add_argument_group('Optional arguments')
-    required.add_argument('-type', action='store', dest="type", help='Type of reads: SE or PE', required=True)
-    required.add_argument('-readsdir', action='store', dest="dir", help='Path to Sequencing Reads Data directory. NOTE: Provide full/absolute path.', required=True)
-    required.add_argument('-outdir', action='store', dest="output_folder", help='Output Folder Path ending with output directory name to save the results. Creates a new output directory path if it doesn\'t exist. NOTE: Provide full/absolute path.', required=True)
-    required.add_argument('-index', action='store', dest="index", help='Reference Index Name. Most Frequently used reference genomes index options: KPNIH1 | MRSA_USA_300 | MRSA_USA_100 | CDIFF_630 | paris Make sure the paths are properly set in config file', required=True)
-    required.add_argument('-steps', action='store', dest="steps", help='Variant Calling Steps in sequential order.\n'
-                                                                     '1.   All: This will run all the steps starting from cleaning the reads to variant calling;\n'
-                                                                     '2.   clean,align,post-align,varcall,filter,stats : This will also run all steps starting from cleaning to variant calling. \nYou can also run part of the pipeline by giving "align,post-align,varcall,filter,stats" which will skip the cleaning part.\nThe order is required to be sequential while using this option. Also, while skipping any of the step make sure you have results already present in your output folder.\n'
-                                                                     '3.   coverage_depth_stats: Run Only Depth of Coverage Stats module after cleaning and read mapping steps\n'
-                                                                     '4.   core_prep: Run this step before running the core steps. This will prepare the data required for generating core SNPs\n'
-                                                                     '5.   core: extract core snps and generate diagnostics plot data matrices to explore filtered snps.')
-    required.add_argument('-analysis', action='store', dest="analysis_name", help='Unique analysis name that will be used as prefix to saving results and log files.', required=True)
-    optional.add_argument('-config', action='store', dest="config", help='Path to Config file, Make sure to check config settings before running pipeline', required=False)
-    optional.add_argument('-suffix', action='store', dest="suffix", help='Fastq reads suffix such as fastq, fastq.gz, fq.gz, fq; Default: fastq.gz', required=False)
-    optional.add_argument('-filenames', action='store', dest="filenames", help='fastq filenames with one single-end filename per line. \nIf the type is set to PE, it will detect the second paired-end filename with the suffix from first filename. \nUseful for running variant calling pipeline on selected files in a reads directory or extracting core snps for selected samples in input reads directory. \nOtherwise the pipeline will consider all the samples available in reads directory.', required=False)
-    optional.add_argument('-cluster', action='store', dest='cluster', help='Run variant calling pipeline in one of the four modes. Default: local. Suggested mode for core snp is cluster that will run all the steps in parallel with the available cores. Make sure to provide a large memory node for this option\nThe possible modes are: cluster/parallel-cluster/parallel-local/local\ncluster: Runs all the jobs on a single large cluster. This will mimic the local run but rather on a large compute node.\nparallel-cluster: Submit variant call jobs for each sample in parallel on compute nodes. This mode is no available for core snp extraction step.\nparallel-local: Run variant call jobs for each sample in parallel locally.\nlocal: Run variant call jobs locally.\nMake Sure to check if the [scheduler] section in config file is set up correctly for your cluster.')
-    optional.add_argument('-clean', action='store', dest="clean", help='clean up intermediate files. Default: OFF')
-    optional.add_argument('-extract_unmapped', action='store', dest="extract_unmapped", help='Extract unmapped reads, assemble it and detect AMR genes using ariba')
-    optional.add_argument('-datadir', action='store', dest="datadir", help='Path to snpEff data directory')
-    optional.add_argument('-snpeff_db', action='store', dest="snpeff_db", help='Name of pre-build snpEff database to use for Annotation')
-    optional.add_argument('-debug_mode', action='store', dest="debug_mode", help='yes/no for debug mode')
-    return parser
-
-""" Sanity checks and directory structure maintenance methods """
-def file_exists(path1):
-    if not os.path.isfile(path1):
-        file_basename = os.path.basename(path1)
-        keep_logging('The file {} does not exists. Please provide another file with full path or check the files path.\n'.format(file_basename), 'The input file {} does not exists. Please provide another file or check the files path.\n'.format(file_basename), logger, 'exception')
-        exit()
-
-def make_sure_path_exists(out_path):
-    try:
-        os.makedirs(out_path)
-    except OSError as exception:
-        if exception.errno != errno.EEXIST:
-            keep_logging('Errors in output folder path! please change the output path or analysis name.', 'Errors in output folder path! please change the output path or analysis name', logger, 'exception')
-            exit()
-
-def get_filenames(dir, type, filenames, analysis, suffix):
-    if not filenames:
-        if not suffix:
-            suffix = ".fastq.gz"
-        try:
-            list_of_files = glob.glob("%s/*%s" % (dir, suffix))
-            if len(list_of_files) < 1:
-                print "No fastq files with suffix %s found in reads directory %s" % (suffix, dir)
-        except OSError as exception:
-            if exception.errno != errno.EEXIST:
-                keep_logging('Error while listing files in reads directory.', 'Error while listing files in reads directory.', logger, 'exception')
-                exit()
-    else:
-        list_of_files = []
-        with open(filenames) as fp:
-            for line in fp:
-                line = line.strip()
-                line = dir + "/" + line
-                list_of_files.append(line)
-    return list_of_files
-
-""" Methods to generate jobs for various pipeline tasks """
-def create_varcall_jobs(filenames_array, type, output_folder, reference, steps, config_file, logger):
-    jobs_temp_dir = "%s/temp_jobs" % output_folder
-    make_sure_path_exists(jobs_temp_dir)
-    keep_logging('Generating cluster jobs in temporary directory %s' % jobs_temp_dir, 'Generating cluster jobs in temporary directory %s' % jobs_temp_dir, logger, 'exception')
-    ##Change the email address; nodes and processor requirements accordingly
-
-    Pbs_model_lines = "#PBS -M %s\n#PBS -m %s\n#PBS -V\n#PBS -l %s\n#PBS -q %s\n#PBS -A %s\n#PBS -l qos=flux\n"\
-                      % (ConfigSectionMap("scheduler", Config)['email'], ConfigSectionMap("scheduler", Config)['notification'], ConfigSectionMap("scheduler", Config)['resources'], ConfigSectionMap("scheduler", Config)['queue'], ConfigSectionMap("scheduler", Config)['flux_account'])
-
-    for file in filenames_array:
-        filename_base = os.path.basename(file)
-        if "R1_001_final.fastq.gz" in filename_base or "R1.fastq.gz" in filename_base or "1_combine.fastq.gz" in filename_base or "1_sequence.fastq.gz" in filename_base or "_forward.fastq.gz" in filename_base or "R1_001.fastq.gz" in filename_base or "_1.fastq.gz" in filename_base or ".1.fastq.gz" in filename_base or "_R1.fastq.gz" in filename_base:
-            # Forward reads file name and get analysis name from its name
-            first_file = file
-            # Get the name of reverse reads files
-            if "R1_001_final.fastq.gz" in filename_base:
-                second_part = filename_base.replace("R1_001_final.fastq.gz", "R2_001_final.fastq.gz")
-                first_part_split = filename_base.split('R1_001_final.fastq.gz')
-                first_part = first_part_split[0].replace('_L001', '')
-                first_part = re.sub("_S.*_", "", first_part)
-            elif "_R1.fastq.gz" in filename_base:
-                second_part = filename_base.replace("_R1.fastq.gz", "_R2.fastq.gz")
-                first_part_split = filename_base.split('_R1.fastq.gz')
-                first_part = first_part_split[0].replace('_L001', '')
-                first_part = re.sub("_S.*_", "", first_part)
-            elif "R1.fastq.gz" in filename_base:
-                second_part = filename_base.replace("R1.fastq.gz", "R2.fastq.gz")
-                first_part_split = filename_base.split('R1.fastq.gz')
-                first_part = first_part_split[0].replace('_L001', '')
-                first_part = re.sub("_S.*_", "", first_part)
-            elif "1_combine.fastq.gz" in filename_base:
-                second_part = filename_base.replace("1_combine.fastq.gz", "2_combine.fastq.gz")
-                first_part_split = filename_base.split('1_combine.fastq.gz')
-                first_part = first_part_split[0].replace('_L001', '')
-                first_part = re.sub("_S.*_", "", first_part)
-            elif "1_sequence.fastq.gz" in filename_base:
-                second_part = filename_base.replace("1_sequence.fastq.gz", "2_sequence.fastq.gz")
-                first_part_split = filename_base.split('1_sequence.fastq.gz')
-                first_part = first_part_split[0].replace('_L001', '')
-                first_part = re.sub("_S.*_", "", first_part)
-            elif "_forward.fastq.gz" in filename_base:
-                second_part = filename_base.replace("_forward.fastq.gz", "_reverse.fastq.gz")
-                first_part_split = filename_base.split('_forward.fastq.gz')
-                first_part = first_part_split[0].replace('_L001', '')
-                first_part = re.sub("_S.*_", "", first_part)
-            elif "R1_001.fastq.gz" in filename_base:
-                second_part = filename_base.replace("R1_001.fastq.gz", "R2_001.fastq.gz")
-                first_part_split = filename_base.split('R1_001.fastq.gz')
-                first_part = first_part_split[0].replace('_L001', '')
-                first_part = re.sub("_S.*_", "", first_part)
-            elif "_1.fastq.gz" in filename_base:
-                second_part = filename_base.replace("_1.fastq.gz", "_2.fastq.gz")
-                first_part_split = filename_base.split('_1.fastq.gz')
-                first_part = first_part_split[0].replace('_L001', '')
-                first_part = re.sub("_S.*_", "", first_part)
-            elif ".1.fastq.gz" in filename_base:
-                second_part = filename_base.replace(".1.fastq.gz", ".2.fastq.gz")
-                first_part_split = filename_base.split('.1.fastq.gz')
-                first_part = first_part_split[0].replace('_L001', '')
-                first_part = re.sub("_S.*_", "", first_part)
-
-            """ Have a standard filename preparation step"""
-            # else:
-            #     print "Using Standard second file naming convention"
-            #     second_part = filename_base.replace("_R1_", "_R2_")
-            #     first_part_split = filename_base.split('_R1.fastq.gz')
-            #     first_part = first_part_split[0].replace('_L001', '')
-            #     first_part = re.sub("_S.*_", "", first_part)
-            second_file = args.dir + "/" + second_part
-            job_name = jobs_temp_dir + "/" + first_part + ".pbs"
-            if not steps:
-                steps == "All"
-            if type == "SE":
-                command = "/nfs/esnitkin/bin_group/anaconda2/bin/python %s/pipeline.py -PE1 %s -o %s/%s -analysis %s -index %s -type SE -config %s -steps %s" % (os.path.dirname(os.path.abspath(__file__)), first_file, output_folder, first_part, first_part, reference, config_file, steps)
-            else:
-                command = "/nfs/esnitkin/bin_group/anaconda2/bin/python %s/pipeline.py -PE1 %s -PE2 %s -o %s/%s -analysis %s -index %s -type PE -config %s -steps %s" % (os.path.dirname(os.path.abspath(__file__)), first_file, second_file, output_folder, first_part, first_part, reference, config_file, steps)
-
-            with open(job_name, 'w') as out:
-                job_title = "#PBS -N %s" % first_part
-                out.write(job_title+'\n')
-                out.write(Pbs_model_lines+'\n')
-                #out.write(cd_command+'\n') ## changed it to automatically change to PBS working directory
-                out.write("#  Change to the directory you submitted from\nif [ -n \"$PBS_O_WORKDIR\" ]; then cd $PBS_O_WORKDIR; fi" + '\n')
-                out.write("echo $PBS_O_WORKDIR" + '\n')
-                out.write("cd %s/temp_jobs" % output_folder + '\n')
-                out.write(command+'\n')
-        elif "R2_001_final.fastq.gz" in filename_base or "R2.fastq.gz" in filename_base or "2_combine.fastq.gz" in filename_base or "2_sequence.fastq.gz" in filename_base or "_reverse.fastq.gz" in filename_base or "R2_001.fastq.gz" in filename_base or "_2.fastq.gz" in filename_base or ".2.fastq.gz" in filename_base or "_R2.fastq.gz" in filename_base:
-            continue
-        else:
-            keep_logging('Error while generating cluster jobs. Make sure the fastq filenames ends with one of these suffix: R1_001_final.fastq.gz, R1.fastq.gz, 1_combine.fastq.gz, 1_sequence.fastq.gz, _forward.fastq.gz, R1_001.fastq.gz, _1.fastq.gz, .1.fastq.gz, _R1.fastq.gz', 'Error while generating cluster jobs. Make sure the fastq filenames ends with one of these suffix: R1_001_final.fastq.gz, R1.fastq.gz, 1_combine.fastq.gz, 1_sequence.fastq.gz, _forward.fastq.gz, R1_001.fastq.gz, _1.fastq.gz, .1.fastq.gz, _R1.fastq.gz', logger, 'exception')
-            exit()
-    list_of_jobs = glob.glob("%s/*.pbs" % jobs_temp_dir)
-    return list_of_jobs
-
-def generate_custom_vcf_file_list(filenames_array, logger):
-    keep_logging('Generating custom vcf file list for core pipeline steps', 'Generating custom vcf files list for core pipeline steps', logger, 'exception')
-    list_of_vcf_files = []
-    for file in filenames_array:
-        filename_base = os.path.basename(file)
-        if "R1_001_final.fastq.gz" in filename_base or "R1.fastq.gz" in filename_base or "1_combine.fastq.gz" in filename_base or "1_sequence.fastq.gz" in filename_base or "_forward.fastq.gz" in filename_base or "R1_001.fastq.gz" in filename_base or "_1.fastq.gz" in filename_base or ".1.fastq.gz" in filename_base or "_R1.fastq.gz" in filename_base:
-            # Forward reads file name and get analysis name from its name
-            first_file = file
-            if "R1_001_final.fastq.gz" in filename_base:
-                first_part_split = filename_base.split('R1_001_final.fastq.gz')
-                first_part = first_part_split[0].replace('_L001', '')
-                first_part = re.sub("_S.*_", "", first_part)
-                first_part = first_part + "_filter2_final.vcf_no_proximate_snp.vcf"
-            elif "_R1.fastq.gz" in filename_base:
-                first_part_split = filename_base.split('_R1.fastq.gz')
-                first_part = first_part_split[0].replace('_L001', '')
-                first_part = re.sub("_S.*_", "", first_part)
-                first_part = first_part + "_filter2_final.vcf_no_proximate_snp.vcf"
-            elif "R1.fastq.gz" in filename_base:
-                first_part_split = filename_base.split('R1.fastq.gz')
-                first_part = first_part_split[0].replace('_L001', '')
-                first_part = re.sub("_S.*_", "", first_part)
-                first_part = first_part + "_filter2_final.vcf_no_proximate_snp.vcf"
-            elif "1_combine.fastq.gz" in filename_base:
-                first_part_split = filename_base.split('1_combine.fastq.gz')
-                first_part = first_part_split[0].replace('_L001', '')
-                first_part = re.sub("_S.*_", "", first_part)
-                first_part = first_part + "_filter2_final.vcf_no_proximate_snp.vcf"
-            elif "1_sequence.fastq.gz" in filename_base:
-                first_part_split = filename_base.split('1_sequence.fastq.gz')
-                first_part = first_part_split[0].replace('_L001', '')
-                first_part = re.sub("_S.*_", "", first_part)
-                first_part = first_part + "_filter2_final.vcf_no_proximate_snp.vcf"
-            elif "_forward.fastq.gz" in filename_base:
-                first_part_split = filename_base.split('_forward.fastq.gz')
-                first_part = first_part_split[0].replace('_L001', '')
-                first_part = re.sub("_S.*_", "", first_part)
-                first_part = first_part + "_filter2_final.vcf_no_proximate_snp.vcf"
-            elif "R1_001.fastq.gz" in filename_base:
-                first_part_split = filename_base.split('R1_001.fastq.gz')
-                first_part = first_part_split[0].replace('_L001', '')
-                first_part = re.sub("_S.*_", "", first_part)
-                first_part = first_part + "_filter2_final.vcf_no_proximate_snp.vcf"
-            elif "_1.fastq.gz" in filename_base:
-                first_part_split = filename_base.split('_1.fastq.gz')
-                first_part = first_part_split[0].replace('_L001', '')
-                first_part = re.sub("_S.*_", "", first_part)
-                first_part = first_part + "_filter2_final.vcf_no_proximate_snp.vcf"
-            elif ".1.fastq.gz" in filename_base:
-                first_part_split = filename_base.split('.1.fastq.gz')
-                first_part = first_part_split[0].replace('_L001', '')
-                first_part = re.sub("_S.*_", "", first_part)
-                first_part = first_part + "_filter2_final.vcf_no_proximate_snp.vcf"
-            list_of_vcf_files.append(first_part)
-    return list_of_vcf_files
-
-def run_command(job):
-    keep_logging('Running Job: bash %s' % job, 'Running Job: bash %s' % job, logger, 'info')
-    call("bash %s" % job, logger)
-    done = "Job Run completed: %s" % job
-    return done
-
-def run_command_list(command):
-    keep_logging('Running command: %s' % command, 'Running command: %s' % command, logger, 'info')
-    call("%s" % command, logger)
-    done = "Command Run completed: %s" % command
-    return done
-
-def run_varcall_jobs(list_of_jobs, cluster, log_unique_time, analysis_name, output_folder, logger):
-    #Generate command list to run on single cluster or in parallel
-    command_list = ""
-    command_list_qsub = []
-    for job in list_of_jobs:
-        command_list = command_list + "bash %s\n" % job
-        command_list_qsub.append(job)
-
-    #cluster mode
-    if cluster == "cluster":
-        keep_logging('Running Job in cluster mode', 'Running Job in cluster mode', logger, 'info')
-        cluster_job_dir = output_folder + "/temp_jobs/cluster/"
-        make_sure_path_exists(cluster_job_dir)
-        Pbs_model_lines = "#PBS -M %s\n#PBS -m %s\n#PBS -V\n#PBS -l %s\n#PBS -q %s\n#PBS -A %s\n#PBS -l qos=flux\n"\
-                      % (ConfigSectionMap("scheduler", Config)['email'], ConfigSectionMap("scheduler", Config)['notification'], ConfigSectionMap("scheduler", Config)['resources'], ConfigSectionMap("scheduler", Config)['queue'], ConfigSectionMap("scheduler", Config)['flux_account'])
-        job_name = cluster_job_dir + log_unique_time + "_" + analysis_name + ".pbs"
-        with open(job_name, 'w') as out:
-            job_title = "#PBS -N %s_%s" % (log_unique_time, analysis_name)
-            out.write(job_title+'\n')
-            out.write(Pbs_model_lines+'\n')
-            out.write("#  Change to the directory you submitted from\nif [ -n \"$PBS_O_WORKDIR\" ]; then cd $PBS_O_WORKDIR; fi" + '\n')
-            out.write("echo $PBS_O_WORKDIR" + '\n')
-            out.write("cd %s/temp_jobs" % output_folder + '\n')
-            out.write(command_list+'\n')
-        out.close()
-        keep_logging('Submitting single cluster Job: qsub %s' % job_name, 'Submitting single cluster Job: qsub %s' % job_name, logger, 'info')
-        #call("qsub %s" % job_name, logger)
-        qid = subprocess.check_output("qsub %s" % job_name, shell=True)
-        print qid.split('.')[0]
-        keep_logging('You can check the job status with: qstat -u USERNAME', 'You can check the job status with: qstat -u USERNAME', logger, 'info')
-    elif cluster == "parallel-cluster":
-        keep_logging('Running Jobs in parallel-cluster mode', 'Running Jobs in parallel-cluster mode', logger, 'info')
-        for job in command_list_qsub:
-            keep_logging('Submitting Job: qsub %s' % job, 'Submitting Job: qsub %s' % job, logger, 'info')
-            call("qsub %s" % job, logger)
-        keep_logging('You can check the job status with: qstat -u USERNAME', 'You can check the job status with: qstat -u USERNAME', logger, 'info')
-    elif cluster == "parallel-local":
-        keep_logging('Running Jobs in parallel-local mode', 'Running Jobs in parallel-local mode', logger, 'info')
-        cluster_job_dir = output_folder + "/temp_jobs/parallel-local/"
-        make_sure_path_exists(cluster_job_dir)
-        job_name = cluster_job_dir + log_unique_time + "_" + analysis_name + ".sh"
-        with open(job_name, 'w') as out:
-            out.write(command_list+'\n')
-        num_cores = multiprocessing.cpu_count()
-        keep_logging('Number of cores available: %s' % num_cores, 'Number of cores available: %s' % num_cores, logger, 'info')
-        results = Parallel(n_jobs=num_cores)(delayed(run_command)(i) for i in command_list_qsub)
-    elif cluster == "local":
-        keep_logging('Running Jobs in local mode', 'Running Jobs in local mode', logger, 'info')
-        for job in command_list_qsub:
-            keep_logging('Running Job: bash %s' % job, 'Running Job: bash %s' % job, logger, 'info')
-            call("bash %s" % job, logger)
-
-""" Pipeline individual task methods """
-def run_core_prep_analysis(core_temp_dir, reference, analysis_name, log_unique_time, cluster, logger, config_file):
-    file_exists(reference)
-    if args.debug_mode == "yes":
-        core_prep_pipeline = "/nfs/esnitkin/bin_group/anaconda2/bin/python %s/modules/variant_diagnostics/core_pipeline_debug.py -filter2_only_snp_vcf_dir %s -filter2_only_snp_vcf_filenames %s/vcf_filenames -reference %s -steps 1 -jobrun %s -config %s" % (os.path.dirname(os.path.abspath(__file__)), core_temp_dir, core_temp_dir, reference, cluster, config_file)
-    else:
-        core_prep_pipeline = "/nfs/esnitkin/bin_group/anaconda2/bin/python %s/modules/variant_diagnostics/core_pipeline.py -filter2_only_snp_vcf_dir %s -filter2_only_snp_vcf_filenames %s/vcf_filenames -reference %s -steps 1 -jobrun %s -config %s" % (os.path.dirname(os.path.abspath(__file__)), core_temp_dir, core_temp_dir, reference, cluster, config_file)
-
-    job_name = core_temp_dir + "/" + log_unique_time + "_" + analysis_name + ".pbs"
-
-    Pbs_model_lines = "#PBS -M %s\n#PBS -m %s\n#PBS -V\n#PBS -l nodes=1:ppn=4,mem=47000mb,walltime=92:00:00\n#PBS -q %s\n#PBS -A %s\n#PBS -l qos=flux\n"\
-                      % (ConfigSectionMap("scheduler", Config)['email'], ConfigSectionMap("scheduler", Config)['notification'], ConfigSectionMap("scheduler", Config)['queue'], ConfigSectionMap("scheduler", Config)['flux_account'])
-
-    with open(job_name, 'w') as out:
-        job_title = "#PBS -N %s_%s_core" % (log_unique_time, analysis_name)
-        out.write(job_title+'\n')
-        out.write(Pbs_model_lines+'\n')
-        out.write("#  Change to the directory you submitted from\nif [ -n \"$PBS_O_WORKDIR\" ]; then cd $PBS_O_WORKDIR; fi" + '\n')
-        out.write("echo \"PBS working directory: $PBS_O_WORKDIR\"" + '\n')
-        out.write("cd %s" % core_temp_dir + '\n')
-        out.write(core_prep_pipeline+'\n')
-    out.close()
-    if cluster == "local":
-        keep_logging('Running local mode: bash %s' % job_name, 'Running local mode: bash %s' % job_name, logger, 'info')
-        call("bash %s" % job_name, logger)
-    elif cluster == "parallel-local":
-        keep_logging('Running parallel-local mode: bash %s' % job_name, 'Running parallel-local mode: bash %s' % job_name, logger, 'info')
-        call("bash %s" % job_name, logger)
-    elif cluster == "cluster":
-        #call("qsub %s" % job_name, logger)
-        keep_logging('Submitting single cluster Job: qsub %s' % job_name, 'Submitting single cluster Job: qsub %s' % job_name, logger, 'info')
-        qid = subprocess.check_output("qsub %s" % job_name, shell=True)
-        print qid.split('.')[0]
-    elif cluster == "parallel-cluster":
-        #call("qsub %s" % job_name, logger)
-        keep_logging('Submitting parallel-cluster Job: qsub %s' % job_name, 'Submitting parallel-cluster Job: qsub %s' % job_name, logger, 'info')
-        qid = subprocess.check_output("qsub %s" % job_name, shell=True)
-        print qid.split('.')[0]
-    keep_logging('You can check the job status with: qstat -u USERNAME', 'You can check the job status with: qstat -u USERNAME', logger, 'info')
-
-def run_core_analysis(core_temp_dir, reference, analysis_name, log_unique_time, cluster, logger, core_results_dir, config_file):
-    file_exists(reference)
-    if args.debug_mode == "yes":
-        core_pipeline = "/nfs/esnitkin/bin_group/anaconda2/bin/python %s/modules/variant_diagnostics/core_pipeline_debug.py -filter2_only_snp_vcf_dir %s -filter2_only_snp_vcf_filenames %s/vcf_filenames -reference %s -steps 2 -jobrun %s -results_dir %s -config %s" % (os.path.dirname(os.path.abspath(__file__)), core_temp_dir, core_temp_dir, reference, cluster, core_results_dir, config_file)
-    else:
-        core_pipeline = "/nfs/esnitkin/bin_group/anaconda2/bin/python %s/modules/variant_diagnostics/core_pipeline.py -filter2_only_snp_vcf_dir %s -filter2_only_snp_vcf_filenames %s/vcf_filenames -reference %s -steps 2 -jobrun %s -results_dir %s -config %s" % (os.path.dirname(os.path.abspath(__file__)), core_temp_dir, core_temp_dir, reference, cluster, core_results_dir, config_file)
-    job_name = core_temp_dir + "/" + log_unique_time + "_" + analysis_name + ".pbs"
-
-    Pbs_model_lines = "#PBS -M %s\n#PBS -m %s\n#PBS -V\n#PBS -l nodes=1:ppn=4,mem=47000mb,walltime=92:00:00\n#PBS -q %s\n#PBS -A %s\n#PBS -l qos=flux\n"\
-                      % (ConfigSectionMap("scheduler", Config)['email'], ConfigSectionMap("scheduler", Config)['notification'], ConfigSectionMap("scheduler", Config)['queue'], ConfigSectionMap("scheduler", Config)['flux_account'])
-
-    with open(job_name, 'w') as out:
-        job_title = "#PBS -N %s_%s_core" % (log_unique_time, analysis_name)
-        out.write(job_title+'\n')
-        out.write(Pbs_model_lines+'\n')
-        out.write("#  Change to the directory you submitted from\nif [ -n \"$PBS_O_WORKDIR\" ]; then cd $PBS_O_WORKDIR; fi" + '\n')
-        out.write("echo \"PBS working directory: $PBS_O_WORKDIR\"" + '\n')
-        out.write("cd %s" % core_temp_dir + '\n')
-        out.write(core_pipeline+'\n')
-    out.close()
-    if cluster == "local":
-        keep_logging('Running local mode: bash %s' % job_name, 'Running local mode: bash %s' % job_name, logger, 'info')
-        call("bash %s" % job_name, logger)
-    elif cluster == "parallel-local":
-        call("bash %s" % job_name, logger)
-    elif cluster == "cluster":
-        #call("qsub %s" % job_name, logger)
-        keep_logging('Submitting single cluster Job: qsub %s' % job_name, 'Submitting single cluster Job: qsub %s' % job_name, logger, 'info')
-        qid = subprocess.check_output("qsub %s" % job_name, shell=True)
-        print qid.split('.')[0]
-    elif cluster == "parallel-cluster":
-        #call("qsub %s" % job_name, logger)
-        keep_logging('Submitting parallel-cluster Job: qsub %s' % job_name, 'Submitting parallel-cluster Job: qsub %s' % job_name, logger, 'info')
-        qid = subprocess.check_output("qsub %s" % job_name, shell=True)
-        print qid.split('.')[0]
-    #keep_logging('You can check the job status with: qstat -u USERNAME', 'You can check the job status with: qstat -u USERNAME', logger, 'info')
-
-def run_report_analysis(core_temp_dir, reference, analysis_name, log_unique_time, cluster, logger, core_results_dir, config_file):
-    file_exists(reference)
-    if args.debug_mode == "yes":
-        core_pipeline = "/nfs/esnitkin/bin_group/anaconda2/bin/python %s/modules/variant_diagnostics/core_pipeline_debug.py -filter2_only_snp_vcf_dir %s -filter2_only_snp_vcf_filenames %s/vcf_filenames -reference %s -steps 3 -jobrun %s -results_dir %s -config %s" % (os.path.dirname(os.path.abspath(__file__)), core_temp_dir, core_temp_dir, reference, cluster, core_results_dir, config_file)
-    else:
-        core_pipeline = "/nfs/esnitkin/bin_group/anaconda2/bin/python %s/modules/variant_diagnostics/core_pipeline.py -filter2_only_snp_vcf_dir %s -filter2_only_snp_vcf_filenames %s/vcf_filenames -reference %s -steps 3 -jobrun %s -results_dir %s -config %s" % (os.path.dirname(os.path.abspath(__file__)), core_temp_dir, core_temp_dir, reference, cluster, core_results_dir, config_file)
-    job_name = core_temp_dir + "/" + log_unique_time + "_" + analysis_name + ".pbs"
-    Pbs_model_lines = "#PBS -M %s\n#PBS -m %s\n#PBS -V\n#PBS -l nodes=1:ppn=4,mem=47000mb,walltime=92:00:00\n#PBS -q %s\n#PBS -A %s\n#PBS -l qos=flux\n"\
-                      % (ConfigSectionMap("scheduler", Config)['email'], ConfigSectionMap("scheduler", Config)['notification'], ConfigSectionMap("scheduler", Config)['queue'], ConfigSectionMap("scheduler", Config)['flux_account'])
-    with open(job_name, 'w') as out:
-        job_title = "#PBS -N %s_%s_core" % (log_unique_time, analysis_name)
-        out.write(job_title+'\n')
-        out.write(Pbs_model_lines+'\n')
-        out.write("#  Change to the directory you submitted from\nif [ -n \"$PBS_O_WORKDIR\" ]; then cd $PBS_O_WORKDIR; fi" + '\n')
-        out.write("echo \"PBS working directory: $PBS_O_WORKDIR\"" + '\n')
-        out.write("cd %s" % core_temp_dir + '\n')
-        out.write(core_pipeline+'\n')
-    out.close()
-
-    if cluster == "local":
-        keep_logging('Running local mode: bash %s' % job_name, 'Running local mode: bash %s' % job_name, logger, 'info')
-        call("bash %s" % job_name, logger)
-    elif cluster == "parallel-local":
-        call("bash %s" % job_name, logger)
-    elif cluster == "cluster":
-        call("qsub %s" % job_name, logger)
-        keep_logging('Submitting single cluster Job: qsub %s' % job_name, 'Submitting single cluster Job: qsub %s' % job_name, logger, 'info')
-        qid = subprocess.check_output("qsub %s" % job_name, shell=True)
-        print qid.split('.')[0]
-    elif cluster == "parallel-cluster":
-        call("qsub %s" % job_name, logger)
-        keep_logging('Submitting parallel-cluster Job: qsub %s' % job_name, 'Submitting parallel-cluster Job: qsub %s' % job_name, logger, 'info')
-        qid = subprocess.check_output("qsub %s" % job_name, shell=True)
-        print qid.split('.')[0]
-    #keep_logging('You can check the job status with: qstat -u USERNAME', 'You can check the job status with: qstat -u USERNAME', logger, 'info')
-
-def run_tree_analysis(core_temp_dir, reference, analysis_name, log_unique_time, cluster, logger, core_results_dir, config_file):
-    if args.debug_mode == "yes":
-        core_pipeline = "/nfs/esnitkin/bin_group/anaconda2/bin/python %s/modules/variant_diagnostics/core_pipeline_debug.py -filter2_only_snp_vcf_dir %s -filter2_only_snp_vcf_filenames %s/vcf_filenames -reference %s -steps 4 -jobrun %s -results_dir %s -config %s" % (os.path.dirname(os.path.abspath(__file__)), core_temp_dir, core_temp_dir, reference, cluster, core_results_dir, config_file)
-    else:
-        core_pipeline = "/nfs/esnitkin/bin_group/anaconda2/bin/python %s/modules/variant_diagnostics/core_pipeline.py -filter2_only_snp_vcf_dir %s -filter2_only_snp_vcf_filenames %s/vcf_filenames -reference %s -steps 4 -jobrun %s -results_dir %s -config %s" % (os.path.dirname(os.path.abspath(__file__)), core_temp_dir, core_temp_dir, reference, cluster, core_results_dir, config_file)
-    job_name = core_temp_dir + "/" + log_unique_time + "_" + analysis_name + ".pbs"
-    Pbs_model_lines = "#PBS -M %s\n#PBS -m %s\n#PBS -V\n#PBS -l nodes=1:ppn=4,mem=47000mb,walltime=92:00:00\n#PBS -q %s\n#PBS -A %s\n#PBS -l qos=flux\n"\
-                      % (ConfigSectionMap("scheduler", Config)['email'], ConfigSectionMap("scheduler", Config)['notification'], ConfigSectionMap("scheduler", Config)['queue'], ConfigSectionMap("scheduler", Config)['flux_account'])
-    with open(job_name, 'w') as out:
-        job_title = "#PBS -N %s_%s_core_tree" % (log_unique_time, analysis_name)
-        out.write(job_title+'\n')
-        out.write(Pbs_model_lines+'\n')
-        out.write("#  Change to the directory you submitted from\nif [ -n \"$PBS_O_WORKDIR\" ]; then cd $PBS_O_WORKDIR; fi" + '\n')
-        out.write("echo \"PBS working directory: $PBS_O_WORKDIR\"" + '\n')
-        out.write("cd %s" % core_temp_dir + '\n')
-        out.write(core_pipeline+'\n')
-    out.close()
-
-    if cluster == "local":
-        keep_logging('Running local mode: bash %s' % job_name, 'Running local mode: bash %s' % job_name, logger, 'info')
-        call("bash %s" % job_name, logger)
-    elif cluster == "parallel-local":
-        call("bash %s" % job_name, logger)
-    elif cluster == "cluster":
-        call("qsub %s" % job_name, logger)
-        keep_logging('Submitting single cluster Job: qsub %s' % job_name, 'Submitting single cluster Job: qsub %s' % job_name, logger, 'info')
-        qid = subprocess.check_output("qsub %s" % job_name, shell=True)
-        print qid.split('.')[0]
-    elif cluster == "parallel-cluster":
-        call("qsub %s" % job_name, logger)
-        keep_logging('Submitting parallel-cluster Job: qsub %s' % job_name, 'Submitting parallel-cluster Job: qsub %s' % job_name, logger, 'info')
-        qid = subprocess.check_output("qsub %s" % job_name, shell=True)
-        print qid.split('.')[0]
-    #keep_logging('You can check the job status with: qstat -u USERNAME', 'You can check the job status with: qstat -u USERNAME', logger, 'info')
-
-""" Start of Main Method/Pipeline """
-if __name__ == '__main__':
-    # Set up logging modules and config file
-    start_time = datetime.now().strftime('%Y-%m-%d %H:%M:%S')
-    start_time_2 = datetime.now()
-    args = parser().parse_args()
-    global config_file
-    global log_unique_time
-    if args.output_folder != '':
-        args.output_folder += '/'
-    make_sure_path_exists(args.output_folder)
-    log_unique_time = datetime.now().strftime('%Y_%m_%d_%H_%M_%S')
-    if args.config:
-        config_file = args.config
-    else:
-        config_file = os.path.dirname(os.path.abspath(__file__)) + "/config"
-    global logger
-    logs_folder = args.output_folder + "/Logs"
-    make_sure_path_exists(logs_folder)
-    # logger = generate_logger(logs_folder, args.analysis_name, log_unique_time)
-    global Config
-    global files_to_delete
-    files_to_delete = []
-    Config = ConfigParser.ConfigParser()
-    Config.read(config_file)
-
-
-    # Run pipeline steps
-    if "core" not in args.steps and "core_prep" not in args.steps and "report" not in args.steps and "tree" not in args.steps:
-        vc_logs_folder = logs_folder + "/variant_calling"
-        make_sure_path_exists(vc_logs_folder)
-        logger = generate_logger(vc_logs_folder, args.analysis_name, log_unique_time)
-        call("cp %s %s/%s_%s_config_copy.txt" % (config_file, vc_logs_folder, log_unique_time, args.analysis_name), logger)
-        if args.cluster:
-            cluster_mode = args.cluster
-        else:
-            cluster_mode = "local"
-
-        keep_logging('START: Variant Calling Pipeline', 'START: Variant Calling Pipeline', logger, 'info')
-
-        list_of_files = get_filenames(args.dir, args.type, args.filenames, args.analysis_name, args.suffix)
-        list_of_jobs = create_varcall_jobs(list_of_files, args.type, args.output_folder, args.index, args.steps, config_file, logger)
-        run_varcall_jobs(list_of_jobs, cluster_mode, log_unique_time, args.analysis_name, args.output_folder, logger)
-        time_taken = datetime.now() - start_time_2
-        keep_logging('Logs were recorded in file with extension log.txt in %s' % vc_logs_folder, 'Logs were recorded in file with extension log.txt in %s' % vc_logs_folder, logger, 'info')
-        keep_logging('Total Time taken: {}'.format(time_taken), 'Total Time taken: {}'.format(time_taken), logger, 'info')
-        keep_logging('End: Variant calling Pipeline', 'End: Variant calling Pipeline', logger, 'info')
-
-    elif "core_prep" in args.steps:
-        core_prep_logs_folder = logs_folder + "/core_prep"
-        make_sure_path_exists(core_prep_logs_folder)
-        logger = generate_logger(core_prep_logs_folder, args.analysis_name, log_unique_time)
-        keep_logging('START: Extract core snps and generate diagnostic plots', 'START: Extract core snps and generate diagnostic plots', logger, 'info')
-        call("cp %s %s/%s_%s_config_copy.txt" % (config_file, core_prep_logs_folder, log_unique_time, args.analysis_name), logger)
-        core_temp_dir = args.output_folder + "/core_temp_dir/"
-        make_sure_path_exists(core_temp_dir)
-        keep_logging('Copying vcf files to %s' % core_temp_dir, 'Copying vcf files to %s' % core_temp_dir, logger, 'info')
-        cp_command = "cp %s/*/*_filter2_indel_final.vcf %s/*/*_aln_mpileup_raw.vcf %s/*/*_raw.vcf_5bp_indel_removed.vcf.gz %s/*/*filter2_final.vcf.gz %s/*/*vcf_no_proximate_snp.vcf.gz %s/*/*array %s/*/*unmapped.bed_positions %s" % (args.output_folder, args.output_folder, args.output_folder, args.output_folder, args.output_folder, args.output_folder, args.output_folder, core_temp_dir)
-        call(cp_command, logger)
-        list_of_gzipped_files = glob.glob("%s/*.gz" % core_temp_dir)
-        keep_logging('Decompressing gzipped files in %s' % core_temp_dir, 'Decompressing gzipped files in %s' % core_temp_dir, logger, 'info')
-        gzipped_command_list = []
-        for i in list_of_gzipped_files:
-            gzipped_command_list.append("gzip -df %s" % i)
-        num_cores = multiprocessing.cpu_count()
-        results = Parallel(n_jobs=num_cores)(delayed(run_command_list)(i) for i in gzipped_command_list)
-        if args.filenames:
-            list_of_files = get_filenames(args.dir, args.type, args.filenames, args.analysis_name, args.suffix)
-            list_of_vcf_files = generate_custom_vcf_file_list(list_of_files, logger)
-            print len(list_of_vcf_files)
-            with open("%s/vcf_filenames" % core_temp_dir, 'w') as out_fp:
-                for file in list_of_vcf_files:
-                    out_fp.write(os.path.basename(file)+'\n')
-            out_fp.close()
-        else:
-            call("ls -1a %s/*.vcf_no_proximate_snp.vcf > %s/vcf_filenames" % (core_temp_dir,core_temp_dir), logger)
-            list_cmd = "ls -1a %s/*.vcf_no_proximate_snp.vcf" % core_temp_dir
-            list_of_files = subprocess.check_output(list_cmd, shell=True)
-            with open("%s/vcf_filenames" % core_temp_dir, 'w') as out_fp:
-                for file in list_of_files.splitlines():
-                    out_fp.write(os.path.basename(file)+'\n')
-            out_fp.close()
-        reference = ConfigSectionMap(args.index, Config)['ref_path'] + "/" + ConfigSectionMap(args.index, Config)['ref_name']
-        run_core_prep_analysis(core_temp_dir, reference, args.analysis_name, log_unique_time, args.cluster, logger, config_file)
-        time_taken = datetime.now() - start_time_2
-        keep_logging('Logs were recorded in file with extension log.txt in %s' % core_prep_logs_folder, 'Logs were recorded in file with extension log.txt in %s' % core_prep_logs_folder, logger, 'info')
-        keep_logging('Total Time taken: {}'.format(time_taken), 'Total Time taken: {}'.format(time_taken), logger, 'info')
-
-    elif "core" in args.steps:
-        core_logs_folder = logs_folder + "/core"
-        make_sure_path_exists(core_logs_folder)
-        logger = generate_logger(core_logs_folder, args.analysis_name, log_unique_time)
-        keep_logging('START: Extract core snps and generate diagnostic plots', 'START: Extract core snps and generate diagnostic plots', logger, 'info')
-        call("cp %s %s/%s_%s_config_copy.txt" % (config_file, core_logs_folder, log_unique_time, args.analysis_name), logger)
-        core_temp_dir = args.output_folder + "/core_temp_dir/"
-        core_results_dir = args.output_folder + "/%s_core_results/" % log_unique_time
-        #make_sure_path_exists(core_results_dir)
-        if args.filenames:
-            list_of_files = get_filenames(args.dir, args.type, args.filenames, args.analysis_name, args.suffix)
-            list_of_vcf_files = generate_custom_vcf_file_list(list_of_files, logger)
-            list_of_label_files = []
-            for i in list_of_vcf_files:
-                list_of_label_files.append(i + '_positions_label')
-            if len(list_of_label_files) == len(list_of_vcf_files):
-                for i in list_of_label_files:
-                    if os.stat("%s/%s" % (core_temp_dir, i)).st_size == 0:
-                        keep_logging('The file {} is empty. Please rerun core_prep step again.\n'.format(i), 'The file {} is empty. Please rerun core_prep step again.\n'.format(i), logger, 'exception')
-                        exit()
-            else:
-                keep_logging('Problem in core_prep results. Rerun the core_prep step\n', 'Problem in core_prep results. Rerun the core_prep step\n', logger, 'exception')
-                exit()
-            with open("%s/vcf_filenames" % core_temp_dir, 'w') as out_fp:
-                for file in list_of_vcf_files:
-                    out_fp.write(os.path.basename(file)+'\n')
-            out_fp.close()
-        else:
-            list_of_label_files = glob.glob("%s/*_no_proximate_snp.vcf_positions_label" % core_temp_dir)
-            list_of_vcf_files = glob.glob("%s/*_filter2_final.vcf_no_proximate_snp.vcf" % core_temp_dir)
-            if len(list_of_label_files) == len(list_of_vcf_files):
-                for i in list_of_label_files:
-                    if os.stat(i).st_size == 0:
-                        keep_logging('The file {} is empty. Please rerun core_prep step again.\n'.format(i), 'The file {} is empty. Please rerun core_prep step again.\n'.format(i), logger, 'exception')
-                        exit()
-            else:
-                keep_logging('Problem in core_prep results. Rerun the core_prep step\n', 'Problem in core_prep results. Rerun the core_prep step\n', logger, 'exception')
-                exit()
-            with open("%s/vcf_filenames" % core_temp_dir, 'w') as out_fp:
-                for file in list_of_vcf_files:
-                    out_fp.write(os.path.basename(file)+'\n')
-            out_fp.close()
-        reference = ConfigSectionMap(args.index, Config)['ref_path'] + "/" + ConfigSectionMap(args.index, Config)['ref_name']
-        run_core_analysis(core_temp_dir, reference, args.analysis_name, log_unique_time, args.cluster, logger, core_results_dir, config_file)
-        time_taken = datetime.now() - start_time_2
-        keep_logging('Logs were recorded in file with extension log.txt in %s' % core_logs_folder, 'Logs were recorded in file with extension log.txt in %s' % core_logs_folder, logger, 'info')
-        keep_logging('Total Time taken: {}'.format(time_taken), 'Total Time taken: {}'.format(time_taken), logger, 'info')
-
-    elif "report" in args.steps:
-        report_logs_folder = logs_folder + "/report"
-        make_sure_path_exists(report_logs_folder)
-        logger = generate_logger(report_logs_folder, args.analysis_name, log_unique_time)
-        keep_logging('START: Generating alignment and variant calling report', 'START: Generating alignment and variant calling report', logger, 'info')
-        call("cp %s %s/%s_%s_config_copy.txt" % (config_file, report_logs_folder, log_unique_time, args.analysis_name), logger)
-        core_temp_dir = args.output_folder + "/core_temp_dir/"
-        core_results_dir = args.output_folder + "/%s_core_results/" % log_unique_time
-        make_sure_path_exists(core_results_dir)
-        list_of_label_files = glob.glob("%s/*_label" % core_temp_dir)
-        list_of_vcf_files = []
-        with open("%s/vcf_filenames" % core_temp_dir, 'r') as out_fp:
-            for line in out_fp:
-                list_of_vcf_files.append(line)
-        for i in list_of_label_files:
-            if os.stat(i).st_size == 0:
-                keep_logging('The file {} is empty. Please rerun core_prep step again.\n'.format(i), 'The file {} is empty. Please rerun core_prep step again.\n'.format(i), logger, 'exception')
-                exit()
-        reference = ConfigSectionMap(args.index, Config)['ref_path'] + "/" + ConfigSectionMap(args.index, Config)['ref_name']
-        run_report_analysis(core_temp_dir, reference, args.analysis_name, log_unique_time, args.cluster, logger, core_results_dir, config_file)
-        time_taken = datetime.now() - start_time_2
-        keep_logging('Logs were recorded in file with extension log.txt in %s' % report_logs_folder, 'Logs were recorded in file with extension log.txt in %s' % report_logs_folder, logger, 'info')
-        keep_logging('Total Time taken: {}'.format(time_taken), 'Total Time taken: {}'.format(time_taken), logger, 'info')
-
-    elif "tree" in args.steps:
-        tree_logs_folder = logs_folder + "/tree"
-        make_sure_path_exists(tree_logs_folder)
-        logger = generate_logger(tree_logs_folder, args.analysis_name, log_unique_time)
-        keep_logging('START: Generating FastTree and RAxML trees', 'START: Generating FastTree and RAxML trees', logger, 'info')
-        call("cp %s %s/%s_%s_config_copy.txt" % (config_file, tree_logs_folder, log_unique_time, args.analysis_name), logger)
-        core_temp_dir = args.output_folder + "/core_temp_dir/"
-        #core_results_dir = args.output_folder + "/%s_core_results/" % log_unique_time
-        proc = subprocess.Popen(["ls -1ad *_core_results | tail -n1"], stdout=subprocess.PIPE, shell=True)
-        (out2, err2) = proc.communicate()
-        core_results_dir = args.output_folder + "/" + out2.strip()
-        print core_results_dir
-        list_of_label_files = glob.glob("%s/*_label" % core_temp_dir)
-        list_of_vcf_files = []
-        with open("%s/vcf_filenames" % core_temp_dir, 'r') as out_fp:
-            for line in out_fp:
-                list_of_vcf_files.append(line)
-        for i in list_of_label_files:
-            if os.stat(i).st_size == 0:
-                keep_logging('The file {} is empty. Please rerun core_prep step again.\n'.format(i), 'The file {} is empty. Please rerun core_prep step again.\n'.format(i), logger, 'exception')
-                exit()
-        reference = ConfigSectionMap(args.index, Config)['ref_path'] + "/" + ConfigSectionMap(args.index, Config)['ref_name']
-        run_tree_analysis(core_temp_dir, reference, args.analysis_name, log_unique_time, args.cluster, logger, core_results_dir, config_file)
-        time_taken = datetime.now() - start_time_2
-        keep_logging('Logs were recorded in file with extension log.txt in %s' % tree_logs_folder, 'Logs were recorded in file with extension log.txt in %s' % tree_logs_folder, logger, 'info')
-        keep_logging('Total Time taken: {}'.format(time_taken), 'Total Time taken: {}'.format(time_taken), logger, 'info')
-    else:
-        logger = generate_logger(logs_folder, args.analysis_name, log_unique_time)
-        keep_logging('Please provide argument -steps to run pipeline', 'Please provide argument -steps to run pipeline', logger, 'info')
-        time_taken = datetime.now() - start_time_2
-        keep_logging('Logs were recorded in file with extension log.txt in %s' % logs_folder, 'Logs were recorded in file with extension log.txt in %s' % logs_folder, logger, 'info')
-        keep_logging('Total Time taken: {}'.format(time_taken), 'Total Time taken: {}'.format(time_taken), logger, 'info')
-
-
-    ## Changed this to individual steps log folder in Logs folder
-    #logger = generate_logger(logs_folder, args.analysis_name, log_unique_time)
-    # time_taken = datetime.now() - start_time_2
-    # keep_logging('Logs were recorded in file with extension log.txt in Logs folder placed in output folder', 'Logs were recorded in file with extension log.txt in Logs folder placed in output folder', logger, 'info')
-    # keep_logging('Total Time taken: {}'.format(time_taken), 'Total Time taken: {}'.format(time_taken), logger, 'info')
diff --git a/variant_call_debug.py b/variant_call_debug.py
deleted file mode 100644
index d765bd9..0000000
--- a/variant_call_debug.py
+++ /dev/null
@@ -1,651 +0,0 @@
-__author__ = 'alipirani'
-
-import sys
-import os
-import argparse
-import errno
-import ConfigParser
-import glob
-import re
-import multiprocessing
-import subprocess as subprocess
-from datetime import datetime
-from joblib import Parallel, delayed
-from config_settings import ConfigSectionMap
-from modules.logging_subprocess import *
-from modules.log_modules import *
-from argparse import RawTextHelpFormatter
-
-""" Command Line Argument Parsing """
-def parser():
-    parser = argparse.ArgumentParser(description='\nVariant Calling pipeline for Illumina PE/SE data.\n', formatter_class=RawTextHelpFormatter)
-    required = parser.add_argument_group('Required arguments')
-    optional = parser.add_argument_group('Optional arguments')
-    required.add_argument('-type', action='store', dest="type", help='Type of reads: SE or PE', required=True)
-    required.add_argument('-readsdir', action='store', dest="dir", help='Path to Sequencing Reads Data directory. NOTE: Provide full/absolute path.', required=True)
-    required.add_argument('-outdir', action='store', dest="output_folder", help='Output Folder Path ending with output directory name to save the results. Creates a new output directory path if it doesn\'t exist. NOTE: Provide full/absolute path.', required=True)
-    required.add_argument('-index', action='store', dest="index", help='Reference Index Name. Most Frequently used reference genomes index options: KPNIH1 | MRSA_USA_300 | MRSA_USA_100 | CDIFF_630 | paris Make sure the paths are properly set in config file', required=True)
-    required.add_argument('-steps', action='store', dest="steps", help='Variant Calling Steps in sequential order.\n'
-                                                                     '1.   All: This will run all the steps starting from cleaning the reads to variant calling;\n'
-                                                                     '2.   clean,align,post-align,varcall,filter,stats : This will also run all steps starting from cleaning to variant calling. \nYou can also run part of the pipeline by giving "align,post-align,varcall,filter,stats" which will skip the cleaning part.\nThe order is required to be sequential while using this option. Also, while skipping any of the step make sure you have results already present in your output folder.\n'
-                                                                     '3.   coverage_depth_stats: Run Only Depth of Coverage Stats module after cleaning and read mapping steps\n'
-                                                                     '4.   core_prep: Run this step before running the core steps. This will prepare the data required for generating core SNPs\n'
-                                                                     '5.   core: extract core snps and generate diagnostics plot data matrices to explore filtered snps.')
-    required.add_argument('-analysis', action='store', dest="analysis_name", help='Unique analysis name that will be used as prefix to saving results and log files.', required=True)
-    optional.add_argument('-config', action='store', dest="config", help='Path to Config file, Make sure to check config settings before running pipeline', required=False)
-    optional.add_argument('-suffix', action='store', dest="suffix", help='Fastq reads suffix such as fastq, fastq.gz, fq.gz, fq; Default: fastq.gz', required=False)
-    optional.add_argument('-filenames', action='store', dest="filenames", help='fastq filenames with one single-end filename per line. \nIf the type is set to PE, it will detect the second paired-end filename with the suffix from first filename. \nUseful for running variant calling pipeline on selected files in a reads directory or extracting core snps for selected samples in input reads directory. \nOtherwise the pipeline will consider all the samples available in reads directory.', required=False)
-    optional.add_argument('-cluster', action='store', dest='cluster', help='Run variant calling pipeline in one of the four modes. Default: local. Suggested mode for core snp is cluster that will run all the steps in parallel with the available cores. Make sure to provide a large memory node for this option\nThe possible modes are: cluster/parallel-cluster/parallel-local/local\ncluster: Runs all the jobs on a single large cluster. This will mimic the local run but rather on a large compute node.\nparallel-cluster: Submit variant call jobs for each sample in parallel on compute nodes. This mode is no available for core snp extraction step.\nparallel-local: Run variant call jobs for each sample in parallel locally.\nlocal: Run variant call jobs locally.\nMake Sure to check if the [scheduler] section in config file is set up correctly for your cluster.')
-    optional.add_argument('-clean', action='store', dest="clean", help='clean up intermediate files. Default: OFF')
-    optional.add_argument('-extract_unmapped', action='store', dest="extract_unmapped", help='Extract unmapped reads, assemble it and detect AMR genes using ariba')
-    optional.add_argument('-datadir', action='store', dest="datadir", help='Path to snpEff data directory')
-    optional.add_argument('-snpeff_db', action='store', dest="snpeff_db", help='Name of pre-build snpEff database to use for Annotation')
-    optional.add_argument('-debug_mode', action='store', dest="debug_mode", help='yes/no for debug mode')
-    return parser
-
-
-class set_global_variable():
-    # Set up logging modules and config file
-    args = parser().parse_args()
-    start_time = datetime.now().strftime('%Y-%m-%d %H:%M:%S')
-    start_time_2 = datetime.now()
-    log_unique_time = datetime.now().strftime('%Y_%m_%d_%H_%M_%S')
-    if args.config:
-        config_file = args.config
-    else:
-        config_file = os.path.dirname(os.path.abspath(__file__)) + "/config"
-    logs_folder = args.output_folder + "/Logs"
-    # logger = generate_logger(logs_folder, args.analysis_name, log_unique_time)
-    files_to_delete = []
-    Config = ConfigParser.ConfigParser()
-    Config.read(config_file)
-
-
-
-
-
-
-
-
-""" Sanity checks and directory structure maintenance methods """
-def file_exists(path1):
-    if not os.path.isfile(path1):
-        file_basename = os.path.basename(path1)
-        keep_logging('The file {} does not exists. Please provide another file with full path or check the files path.\n'.format(file_basename), 'The input file {} does not exists. Please provide another file or check the files path.\n'.format(file_basename), logger, 'exception')
-        exit()
-
-def make_sure_path_exists(out_path):
-    try:
-        os.makedirs(out_path)
-    except OSError as exception:
-        if exception.errno != errno.EEXIST:
-            keep_logging('Errors in output folder path! please change the output path or analysis name.', 'Errors in output folder path! please change the output path or analysis name', logger, 'exception')
-            exit()
-
-def get_filenames(dir, type, filenames, analysis, suffix):
-    if not filenames:
-        if not suffix:
-            suffix = ".fastq.gz"
-        try:
-            list_of_files = glob.glob("%s/*%s" % (dir, suffix))
-            if len(list_of_files) < 1:
-                print "No fastq files with suffix %s found in reads directory %s" % (suffix, dir)
-        except OSError as exception:
-            if exception.errno != errno.EEXIST:
-                keep_logging('Error while listing files in reads directory.', 'Error while listing files in reads directory.', logger, 'exception')
-                exit()
-    else:
-        list_of_files = []
-        with open(filenames) as fp:
-            for line in fp:
-                line = line.strip()
-                line = dir + "/" + line
-                list_of_files.append(line)
-    return list_of_files
-
-def generate_custom_vcf_file_list(filenames_array, logger):
-    keep_logging('Generating custom vcf file list for core pipeline steps', 'Generating custom vcf files list for core pipeline steps', logger, 'exception')
-    list_of_vcf_files = []
-    for file in filenames_array:
-        filename_base = os.path.basename(file)
-        if "R1_001_final.fastq.gz" in filename_base or "R1.fastq.gz" in filename_base or "1_combine.fastq.gz" in filename_base or "1_sequence.fastq.gz" in filename_base or "_forward.fastq.gz" in filename_base or "R1_001.fastq.gz" in filename_base or "_1.fastq.gz" in filename_base or ".1.fastq.gz" in filename_base or "_R1.fastq.gz" in filename_base:
-            # Forward reads file name and get analysis name from its name
-            first_file = file
-            if "R1_001_final.fastq.gz" in filename_base:
-                first_part_split = filename_base.split('R1_001_final.fastq.gz')
-                first_part = first_part_split[0].replace('_L001', '')
-                first_part = re.sub("_S.*_", "", first_part)
-                first_part = first_part + "_filter2_final.vcf_no_proximate_snp.vcf"
-            elif "_R1.fastq.gz" in filename_base:
-                first_part_split = filename_base.split('_R1.fastq.gz')
-                first_part = first_part_split[0].replace('_L001', '')
-                first_part = re.sub("_S.*_", "", first_part)
-                first_part = first_part + "_filter2_final.vcf_no_proximate_snp.vcf"
-            elif "R1.fastq.gz" in filename_base:
-                first_part_split = filename_base.split('R1.fastq.gz')
-                first_part = first_part_split[0].replace('_L001', '')
-                first_part = re.sub("_S.*_", "", first_part)
-                first_part = first_part + "_filter2_final.vcf_no_proximate_snp.vcf"
-            elif "1_combine.fastq.gz" in filename_base:
-                first_part_split = filename_base.split('1_combine.fastq.gz')
-                first_part = first_part_split[0].replace('_L001', '')
-                first_part = re.sub("_S.*_", "", first_part)
-                first_part = first_part + "_filter2_final.vcf_no_proximate_snp.vcf"
-            elif "1_sequence.fastq.gz" in filename_base:
-                first_part_split = filename_base.split('1_sequence.fastq.gz')
-                first_part = first_part_split[0].replace('_L001', '')
-                first_part = re.sub("_S.*_", "", first_part)
-                first_part = first_part + "_filter2_final.vcf_no_proximate_snp.vcf"
-            elif "_forward.fastq.gz" in filename_base:
-                first_part_split = filename_base.split('_forward.fastq.gz')
-                first_part = first_part_split[0].replace('_L001', '')
-                first_part = re.sub("_S.*_", "", first_part)
-                first_part = first_part + "_filter2_final.vcf_no_proximate_snp.vcf"
-            elif "R1_001.fastq.gz" in filename_base:
-                first_part_split = filename_base.split('R1_001.fastq.gz')
-                first_part = first_part_split[0].replace('_L001', '')
-                first_part = re.sub("_S.*_", "", first_part)
-                first_part = first_part + "_filter2_final.vcf_no_proximate_snp.vcf"
-            elif "_1.fastq.gz" in filename_base:
-                first_part_split = filename_base.split('_1.fastq.gz')
-                first_part = first_part_split[0].replace('_L001', '')
-                first_part = re.sub("_S.*_", "", first_part)
-                first_part = first_part + "_filter2_final.vcf_no_proximate_snp.vcf"
-            elif ".1.fastq.gz" in filename_base:
-                first_part_split = filename_base.split('.1.fastq.gz')
-                first_part = first_part_split[0].replace('_L001', '')
-                first_part = re.sub("_S.*_", "", first_part)
-                first_part = first_part + "_filter2_final.vcf_no_proximate_snp.vcf"
-            list_of_vcf_files.append(first_part)
-    return list_of_vcf_files
-
-""" Methods to generate jobs for various pipeline tasks """
-def create_varcall_jobs(filenames_array, type, output_folder, reference, steps, config_file, logger):
-    jobs_temp_dir = "%s/temp_jobs" % output_folder
-    make_sure_path_exists(jobs_temp_dir)
-    keep_logging('Generating cluster jobs in temporary directory %s' % jobs_temp_dir, 'Generating cluster jobs in temporary directory %s' % jobs_temp_dir, logger, 'exception')
-    ##Change the email address; nodes and processor requirements accordingly
-
-    Pbs_model_lines = "#PBS -M %s\n#PBS -m %s\n#PBS -V\n#PBS -l %s\n#PBS -q %s\n#PBS -A %s\n#PBS -l qos=flux\n"\
-                      % (ConfigSectionMap("scheduler", Config)['email'], ConfigSectionMap("scheduler", Config)['notification'], ConfigSectionMap("scheduler", Config)['resources'], ConfigSectionMap("scheduler", Config)['queue'], ConfigSectionMap("scheduler", Config)['flux_account'])
-
-    for file in filenames_array:
-        filename_base = os.path.basename(file)
-        if "R1_001_final.fastq.gz" in filename_base or "R1.fastq.gz" in filename_base or "1_combine.fastq.gz" in filename_base or "1_sequence.fastq.gz" in filename_base or "_forward.fastq.gz" in filename_base or "R1_001.fastq.gz" in filename_base or "_1.fastq.gz" in filename_base or ".1.fastq.gz" in filename_base or "_R1.fastq.gz" in filename_base:
-            # Forward reads file name and get analysis name from its name
-            first_file = file
-            # Get the name of reverse reads files
-            if "R1_001_final.fastq.gz" in filename_base:
-                second_part = filename_base.replace("R1_001_final.fastq.gz", "R2_001_final.fastq.gz")
-                first_part_split = filename_base.split('R1_001_final.fastq.gz')
-                first_part = first_part_split[0].replace('_L001', '')
-                first_part = re.sub("_S.*_", "", first_part)
-            elif "_R1.fastq.gz" in filename_base:
-                second_part = filename_base.replace("_R1.fastq.gz", "_R2.fastq.gz")
-                first_part_split = filename_base.split('_R1.fastq.gz')
-                first_part = first_part_split[0].replace('_L001', '')
-                first_part = re.sub("_S.*_", "", first_part)
-            elif "R1.fastq.gz" in filename_base:
-                second_part = filename_base.replace("R1.fastq.gz", "R2.fastq.gz")
-                first_part_split = filename_base.split('R1.fastq.gz')
-                first_part = first_part_split[0].replace('_L001', '')
-                first_part = re.sub("_S.*_", "", first_part)
-            elif "1_combine.fastq.gz" in filename_base:
-                second_part = filename_base.replace("1_combine.fastq.gz", "2_combine.fastq.gz")
-                first_part_split = filename_base.split('1_combine.fastq.gz')
-                first_part = first_part_split[0].replace('_L001', '')
-                first_part = re.sub("_S.*_", "", first_part)
-            elif "1_sequence.fastq.gz" in filename_base:
-                second_part = filename_base.replace("1_sequence.fastq.gz", "2_sequence.fastq.gz")
-                first_part_split = filename_base.split('1_sequence.fastq.gz')
-                first_part = first_part_split[0].replace('_L001', '')
-                first_part = re.sub("_S.*_", "", first_part)
-            elif "_forward.fastq.gz" in filename_base:
-                second_part = filename_base.replace("_forward.fastq.gz", "_reverse.fastq.gz")
-                first_part_split = filename_base.split('_forward.fastq.gz')
-                first_part = first_part_split[0].replace('_L001', '')
-                first_part = re.sub("_S.*_", "", first_part)
-            elif "R1_001.fastq.gz" in filename_base:
-                second_part = filename_base.replace("R1_001.fastq.gz", "R2_001.fastq.gz")
-                first_part_split = filename_base.split('R1_001.fastq.gz')
-                first_part = first_part_split[0].replace('_L001', '')
-                first_part = re.sub("_S.*_", "", first_part)
-            elif "_1.fastq.gz" in filename_base:
-                second_part = filename_base.replace("_1.fastq.gz", "_2.fastq.gz")
-                first_part_split = filename_base.split('_1.fastq.gz')
-                first_part = first_part_split[0].replace('_L001', '')
-                first_part = re.sub("_S.*_", "", first_part)
-            elif ".1.fastq.gz" in filename_base:
-                second_part = filename_base.replace(".1.fastq.gz", ".2.fastq.gz")
-                first_part_split = filename_base.split('.1.fastq.gz')
-                first_part = first_part_split[0].replace('_L001', '')
-                first_part = re.sub("_S.*_", "", first_part)
-
-            """ Have a standard filename preparation step"""
-            # else:
-            #     print "Using Standard second file naming convention"
-            #     second_part = filename_base.replace("_R1_", "_R2_")
-            #     first_part_split = filename_base.split('_R1.fastq.gz')
-            #     first_part = first_part_split[0].replace('_L001', '')
-            #     first_part = re.sub("_S.*_", "", first_part)
-            second_file = args.dir + "/" + second_part
-            job_name = jobs_temp_dir + "/" + first_part + ".pbs"
-            if not steps:
-                steps == "All"
-            if type == "SE":
-                command = "/nfs/esnitkin/bin_group/anaconda2/bin/python %s/pipeline.py -PE1 %s -o %s/%s -analysis %s -index %s -type SE -config %s -steps %s" % (os.path.dirname(os.path.abspath(__file__)), first_file, output_folder, first_part, first_part, reference, config_file, steps)
-            else:
-                command = "/nfs/esnitkin/bin_group/anaconda2/bin/python %s/pipeline.py -PE1 %s -PE2 %s -o %s/%s -analysis %s -index %s -type PE -config %s -steps %s" % (os.path.dirname(os.path.abspath(__file__)), first_file, second_file, output_folder, first_part, first_part, reference, config_file, steps)
-
-            with open(job_name, 'w') as out:
-                job_title = "#PBS -N %s" % first_part
-                out.write(job_title+'\n')
-                out.write(Pbs_model_lines+'\n')
-                #out.write(cd_command+'\n') ## changed it to automatically change to PBS working directory
-                out.write("#  Change to the directory you submitted from\nif [ -n \"$PBS_O_WORKDIR\" ]; then cd $PBS_O_WORKDIR; fi" + '\n')
-                out.write("echo $PBS_O_WORKDIR" + '\n')
-                out.write("cd %s/temp_jobs" % output_folder + '\n')
-                out.write(command+'\n')
-        elif "R2_001_final.fastq.gz" in filename_base or "R2.fastq.gz" in filename_base or "2_combine.fastq.gz" in filename_base or "2_sequence.fastq.gz" in filename_base or "_reverse.fastq.gz" in filename_base or "R2_001.fastq.gz" in filename_base or "_2.fastq.gz" in filename_base or ".2.fastq.gz" in filename_base or "_R2.fastq.gz" in filename_base:
-            continue
-        else:
-            keep_logging('Error while generating cluster jobs. Make sure the fastq filenames ends with one of these suffix: R1_001_final.fastq.gz, R1.fastq.gz, 1_combine.fastq.gz, 1_sequence.fastq.gz, _forward.fastq.gz, R1_001.fastq.gz, _1.fastq.gz, .1.fastq.gz, _R1.fastq.gz', 'Error while generating cluster jobs. Make sure the fastq filenames ends with one of these suffix: R1_001_final.fastq.gz, R1.fastq.gz, 1_combine.fastq.gz, 1_sequence.fastq.gz, _forward.fastq.gz, R1_001.fastq.gz, _1.fastq.gz, .1.fastq.gz, _R1.fastq.gz', logger, 'exception')
-            exit()
-    list_of_jobs = glob.glob("%s/*.pbs" % jobs_temp_dir)
-    return list_of_jobs
-
-def run_command(job):
-    keep_logging('Running Job: bash %s' % job, 'Running Job: bash %s' % job, logger, 'info')
-    call("bash %s" % job, logger)
-    done = "Job Run completed: %s" % job
-    return done
-
-def run_command_list(command):
-    keep_logging('Running command: %s' % command, 'Running command: %s' % command, logger, 'info')
-    call("%s" % command, logger)
-    done = "Command Run completed: %s" % command
-    return done
-
-def run_varcall_jobs(list_of_jobs, cluster, log_unique_time, analysis_name, output_folder, logger):
-    #Generate command list to run on single cluster or in parallel
-    command_list = ""
-    command_list_qsub = []
-    for job in list_of_jobs:
-        command_list = command_list + "bash %s\n" % job
-        command_list_qsub.append(job)
-
-    #cluster mode
-    if cluster == "cluster":
-        keep_logging('Running Job in cluster mode', 'Running Job in cluster mode', logger, 'info')
-        cluster_job_dir = output_folder + "/temp_jobs/cluster/"
-        make_sure_path_exists(cluster_job_dir)
-        Pbs_model_lines = "#PBS -M %s\n#PBS -m %s\n#PBS -V\n#PBS -l %s\n#PBS -q %s\n#PBS -A %s\n#PBS -l qos=flux\n"\
-                      % (ConfigSectionMap("scheduler", Config)['email'], ConfigSectionMap("scheduler", Config)['notification'], ConfigSectionMap("scheduler", Config)['resources'], ConfigSectionMap("scheduler", Config)['queue'], ConfigSectionMap("scheduler", Config)['flux_account'])
-        job_name = cluster_job_dir + log_unique_time + "_" + analysis_name + ".pbs"
-        with open(job_name, 'w') as out:
-            job_title = "#PBS -N %s_%s" % (log_unique_time, analysis_name)
-            out.write(job_title+'\n')
-            out.write(Pbs_model_lines+'\n')
-            out.write("#  Change to the directory you submitted from\nif [ -n \"$PBS_O_WORKDIR\" ]; then cd $PBS_O_WORKDIR; fi" + '\n')
-            out.write("echo $PBS_O_WORKDIR" + '\n')
-            out.write("cd %s/temp_jobs" % output_folder + '\n')
-            out.write(command_list+'\n')
-        out.close()
-        keep_logging('Submitting single cluster Job: qsub %s' % job_name, 'Submitting single cluster Job: qsub %s' % job_name, logger, 'info')
-        #call("qsub %s" % job_name, logger)
-        qid = subprocess.check_output("qsub %s" % job_name, shell=True)
-        print qid.split('.')[0]
-        keep_logging('You can check the job status with: qstat -u USERNAME', 'You can check the job status with: qstat -u USERNAME', logger, 'info')
-    elif cluster == "parallel-cluster":
-        keep_logging('Running Jobs in parallel-cluster mode', 'Running Jobs in parallel-cluster mode', logger, 'info')
-        for job in command_list_qsub:
-            keep_logging('Submitting Job: qsub %s' % job, 'Submitting Job: qsub %s' % job, logger, 'info')
-            call("qsub %s" % job, logger)
-        keep_logging('You can check the job status with: qstat -u USERNAME', 'You can check the job status with: qstat -u USERNAME', logger, 'info')
-    elif cluster == "parallel-local":
-        keep_logging('Running Jobs in parallel-local mode', 'Running Jobs in parallel-local mode', logger, 'info')
-        cluster_job_dir = output_folder + "/temp_jobs/parallel-local/"
-        make_sure_path_exists(cluster_job_dir)
-        job_name = cluster_job_dir + log_unique_time + "_" + analysis_name + ".sh"
-        with open(job_name, 'w') as out:
-            out.write(command_list+'\n')
-        num_cores = multiprocessing.cpu_count()
-        keep_logging('Number of cores available: %s' % num_cores, 'Number of cores available: %s' % num_cores, logger, 'info')
-        results = Parallel(n_jobs=num_cores)(delayed(run_command)(i) for i in command_list_qsub)
-    elif cluster == "local":
-        keep_logging('Running Jobs in local mode', 'Running Jobs in local mode', logger, 'info')
-        for job in command_list_qsub:
-            keep_logging('Running Job: bash %s' % job, 'Running Job: bash %s' % job, logger, 'info')
-            call("bash %s" % job, logger)
-
-""" Pipeline individual task methods """
-def run_core_prep_analysis(core_temp_dir, reference, analysis_name, log_unique_time, cluster, logger, config_file):
-    file_exists(reference)
-    if args.debug_mode == "yes":
-        core_prep_pipeline = "/nfs/esnitkin/bin_group/anaconda2/bin/python %s/modules/variant_diagnostics/core_pipeline_debug.py -filter2_only_snp_vcf_dir %s -filter2_only_snp_vcf_filenames %s/vcf_filenames -reference %s -steps 1 -jobrun %s -config %s" % (os.path.dirname(os.path.abspath(__file__)), core_temp_dir, core_temp_dir, reference, cluster, config_file)
-    else:
-        core_prep_pipeline = "/nfs/esnitkin/bin_group/anaconda2/bin/python %s/modules/variant_diagnostics/core_pipeline.py -filter2_only_snp_vcf_dir %s -filter2_only_snp_vcf_filenames %s/vcf_filenames -reference %s -steps 1 -jobrun %s -config %s" % (os.path.dirname(os.path.abspath(__file__)), core_temp_dir, core_temp_dir, reference, cluster, config_file)
-
-    job_name = core_temp_dir + "/" + log_unique_time + "_" + analysis_name + ".pbs"
-
-    Pbs_model_lines = "#PBS -M %s\n#PBS -m %s\n#PBS -V\n#PBS -l %s\n#PBS -q %s\n#PBS -A %s\n#PBS -l qos=flux\n"\
-                      % (ConfigSectionMap("scheduler", Config)['email'], ConfigSectionMap("scheduler", Config)['notification'], ConfigSectionMap("scheduler", Config)['resources'], ConfigSectionMap("scheduler", Config)['queue'], ConfigSectionMap("scheduler", Config)['flux_account'])
-
-    with open(job_name, 'w') as out:
-        job_title = "#PBS -N %s_%s_core" % (log_unique_time, analysis_name)
-        out.write(job_title+'\n')
-        out.write(Pbs_model_lines+'\n')
-        out.write("#  Change to the directory you submitted from\nif [ -n \"$PBS_O_WORKDIR\" ]; then cd $PBS_O_WORKDIR; fi" + '\n')
-        out.write("echo \"PBS working directory: $PBS_O_WORKDIR\"" + '\n')
-        out.write("cd %s" % core_temp_dir + '\n')
-        out.write(core_prep_pipeline+'\n')
-    out.close()
-    if cluster == "local":
-        keep_logging('Running local mode: bash %s' % job_name, 'Running local mode: bash %s' % job_name, logger, 'info')
-        call("bash %s" % job_name, logger)
-    elif cluster == "parallel-local":
-        keep_logging('Running parallel-local mode: bash %s' % job_name, 'Running parallel-local mode: bash %s' % job_name, logger, 'info')
-        call("bash %s" % job_name, logger)
-    elif cluster == "cluster":
-        #call("qsub %s" % job_name, logger)
-        keep_logging('Submitting single cluster Job: qsub %s' % job_name, 'Submitting single cluster Job: qsub %s' % job_name, logger, 'info')
-        qid = subprocess.check_output("qsub %s" % job_name, shell=True)
-        print qid.split('.')[0]
-    elif cluster == "parallel-cluster":
-        #call("qsub %s" % job_name, logger)
-        keep_logging('Submitting parallel-cluster Job: qsub %s' % job_name, 'Submitting parallel-cluster Job: qsub %s' % job_name, logger, 'info')
-        qid = subprocess.check_output("qsub %s" % job_name, shell=True)
-        print qid.split('.')[0]
-    keep_logging('You can check the job status with: qstat -u USERNAME', 'You can check the job status with: qstat -u USERNAME', logger, 'info')
-
-def run_core_analysis(core_temp_dir, reference, analysis_name, log_unique_time, cluster, logger, core_results_dir, config_file):
-    file_exists(reference)
-    if args.debug_mode == "yes":
-        core_pipeline = "/nfs/esnitkin/bin_group/anaconda2/bin/python %s/modules/variant_diagnostics/core_pipeline_debug.py -filter2_only_snp_vcf_dir %s -filter2_only_snp_vcf_filenames %s/vcf_filenames -reference %s -steps 2 -jobrun %s -results_dir %s -config %s" % (os.path.dirname(os.path.abspath(__file__)), core_temp_dir, core_temp_dir, reference, cluster, core_results_dir, config_file)
-    else:
-        core_pipeline = "/nfs/esnitkin/bin_group/anaconda2/bin/python %s/modules/variant_diagnostics/core_pipeline.py -filter2_only_snp_vcf_dir %s -filter2_only_snp_vcf_filenames %s/vcf_filenames -reference %s -steps 2 -jobrun %s -results_dir %s -config %s" % (os.path.dirname(os.path.abspath(__file__)), core_temp_dir, core_temp_dir, reference, cluster, core_results_dir, config_file)
-    job_name = core_temp_dir + "/" + log_unique_time + "_" + analysis_name + ".pbs"
-
-    Pbs_model_lines = "#PBS -M %s\n#PBS -m %s\n#PBS -V\n#PBS -l %s\n#PBS -q %s\n#PBS -A %s\n#PBS -l qos=flux\n"\
-                      % (ConfigSectionMap("scheduler", Config)['email'], ConfigSectionMap("scheduler", Config)['notification'], ConfigSectionMap("scheduler", Config)['resources'], ConfigSectionMap("scheduler", Config)['queue'], ConfigSectionMap("scheduler", Config)['flux_account'])
-
-    with open(job_name, 'w') as out:
-        job_title = "#PBS -N %s_%s_core" % (log_unique_time, analysis_name)
-        out.write(job_title+'\n')
-        out.write(Pbs_model_lines+'\n')
-        out.write("#  Change to the directory you submitted from\nif [ -n \"$PBS_O_WORKDIR\" ]; then cd $PBS_O_WORKDIR; fi" + '\n')
-        out.write("echo \"PBS working directory: $PBS_O_WORKDIR\"" + '\n')
-        out.write("cd %s" % core_temp_dir + '\n')
-        out.write(core_pipeline+'\n')
-    out.close()
-    if cluster == "local":
-        keep_logging('Running local mode: bash %s' % job_name, 'Running local mode: bash %s' % job_name, logger, 'info')
-        call("bash %s" % job_name, logger)
-    elif cluster == "parallel-local":
-        call("bash %s" % job_name, logger)
-    elif cluster == "cluster":
-        #call("qsub %s" % job_name, logger)
-        keep_logging('Submitting single cluster Job: qsub %s' % job_name, 'Submitting single cluster Job: qsub %s' % job_name, logger, 'info')
-        qid = subprocess.check_output("qsub %s" % job_name, shell=True)
-        print qid.split('.')[0]
-    elif cluster == "parallel-cluster":
-        #call("qsub %s" % job_name, logger)
-        keep_logging('Submitting parallel-cluster Job: qsub %s' % job_name, 'Submitting parallel-cluster Job: qsub %s' % job_name, logger, 'info')
-        qid = subprocess.check_output("qsub %s" % job_name, shell=True)
-        print qid.split('.')[0]
-    #keep_logging('You can check the job status with: qstat -u USERNAME', 'You can check the job status with: qstat -u USERNAME', logger, 'info')
-
-def run_report_analysis(core_temp_dir, reference, analysis_name, log_unique_time, cluster, logger, core_results_dir, config_file):
-    file_exists(reference)
-    if args.debug_mode == "yes":
-        core_pipeline = "/nfs/esnitkin/bin_group/anaconda2/bin/python %s/modules/variant_diagnostics/core_pipeline_debug.py -filter2_only_snp_vcf_dir %s -filter2_only_snp_vcf_filenames %s/vcf_filenames -reference %s -steps 3 -jobrun %s -results_dir %s -config %s" % (os.path.dirname(os.path.abspath(__file__)), core_temp_dir, core_temp_dir, reference, cluster, core_results_dir, config_file)
-    else:
-        core_pipeline = "/nfs/esnitkin/bin_group/anaconda2/bin/python %s/modules/variant_diagnostics/core_pipeline.py -filter2_only_snp_vcf_dir %s -filter2_only_snp_vcf_filenames %s/vcf_filenames -reference %s -steps 3 -jobrun %s -results_dir %s -config %s" % (os.path.dirname(os.path.abspath(__file__)), core_temp_dir, core_temp_dir, reference, cluster, core_results_dir, config_file)
-    job_name = core_temp_dir + "/" + log_unique_time + "_" + analysis_name + ".pbs"
-    Pbs_model_lines = "#PBS -M %s\n#PBS -m %s\n#PBS -V\n#PBS -l %s\n#PBS -q %s\n#PBS -A %s\n#PBS -l qos=flux\n"\
-                      % (ConfigSectionMap("scheduler", Config)['email'], ConfigSectionMap("scheduler", Config)['notification'], ConfigSectionMap("scheduler", Config)['resources'], ConfigSectionMap("scheduler", Config)['queue'], ConfigSectionMap("scheduler", Config)['flux_account'])
-    with open(job_name, 'w') as out:
-        job_title = "#PBS -N %s_%s_core" % (log_unique_time, analysis_name)
-        out.write(job_title+'\n')
-        out.write(Pbs_model_lines+'\n')
-        out.write("#  Change to the directory you submitted from\nif [ -n \"$PBS_O_WORKDIR\" ]; then cd $PBS_O_WORKDIR; fi" + '\n')
-        out.write("echo \"PBS working directory: $PBS_O_WORKDIR\"" + '\n')
-        out.write("cd %s" % core_temp_dir + '\n')
-        out.write(core_pipeline+'\n')
-    out.close()
-
-    if cluster == "local":
-        keep_logging('Running local mode: bash %s' % job_name, 'Running local mode: bash %s' % job_name, logger, 'info')
-        call("bash %s" % job_name, logger)
-    elif cluster == "parallel-local":
-        call("bash %s" % job_name, logger)
-    elif cluster == "cluster":
-        call("qsub %s" % job_name, logger)
-        keep_logging('Submitting single cluster Job: qsub %s' % job_name, 'Submitting single cluster Job: qsub %s' % job_name, logger, 'info')
-        qid = subprocess.check_output("qsub %s" % job_name, shell=True)
-        print qid.split('.')[0]
-    elif cluster == "parallel-cluster":
-        call("qsub %s" % job_name, logger)
-        keep_logging('Submitting parallel-cluster Job: qsub %s' % job_name, 'Submitting parallel-cluster Job: qsub %s' % job_name, logger, 'info')
-        qid = subprocess.check_output("qsub %s" % job_name, shell=True)
-        print qid.split('.')[0]
-    #keep_logging('You can check the job status with: qstat -u USERNAME', 'You can check the job status with: qstat -u USERNAME', logger, 'info')
-
-def run_tree_analysis(core_temp_dir, reference, analysis_name, log_unique_time, cluster, logger, core_results_dir, config_file):
-    if args.debug_mode == "yes":
-        core_pipeline = "/nfs/esnitkin/bin_group/anaconda2/bin/python %s/modules/variant_diagnostics/core_pipeline_debug.py -filter2_only_snp_vcf_dir %s -filter2_only_snp_vcf_filenames %s/vcf_filenames -reference %s -steps 4 -jobrun %s -results_dir %s -config %s" % (os.path.dirname(os.path.abspath(__file__)), core_temp_dir, core_temp_dir, reference, cluster, core_results_dir, config_file)
-    else:
-        core_pipeline = "/nfs/esnitkin/bin_group/anaconda2/bin/python %s/modules/variant_diagnostics/core_pipeline.py -filter2_only_snp_vcf_dir %s -filter2_only_snp_vcf_filenames %s/vcf_filenames -reference %s -steps 4 -jobrun %s -results_dir %s -config %s" % (os.path.dirname(os.path.abspath(__file__)), core_temp_dir, core_temp_dir, reference, cluster, core_results_dir, config_file)
-    job_name = core_temp_dir + "/" + log_unique_time + "_" + analysis_name + ".pbs"
-    Pbs_model_lines = "#PBS -M %s\n#PBS -m %s\n#PBS -V\n#PBS -l %s\n#PBS -q %s\n#PBS -A %s\n#PBS -l qos=flux\n"\
-                      % (ConfigSectionMap("scheduler", Config)['email'], ConfigSectionMap("scheduler", Config)['notification'], ConfigSectionMap("scheduler", Config)['resources'], ConfigSectionMap("scheduler", Config)['queue'], ConfigSectionMap("scheduler", Config)['flux_account'])
-    with open(job_name, 'w') as out:
-        job_title = "#PBS -N %s_%s_core_tree" % (log_unique_time, analysis_name)
-        out.write(job_title+'\n')
-        out.write(Pbs_model_lines+'\n')
-        out.write("#  Change to the directory you submitted from\nif [ -n \"$PBS_O_WORKDIR\" ]; then cd $PBS_O_WORKDIR; fi" + '\n')
-        out.write("echo \"PBS working directory: $PBS_O_WORKDIR\"" + '\n')
-        out.write("cd %s" % core_temp_dir + '\n')
-        out.write(core_pipeline+'\n')
-    out.close()
-
-    if cluster == "local":
-        keep_logging('Running local mode: bash %s' % job_name, 'Running local mode: bash %s' % job_name, logger, 'info')
-        call("bash %s" % job_name, logger)
-    elif cluster == "parallel-local":
-        call("bash %s" % job_name, logger)
-    elif cluster == "cluster":
-        call("qsub %s" % job_name, logger)
-        keep_logging('Submitting single cluster Job: qsub %s' % job_name, 'Submitting single cluster Job: qsub %s' % job_name, logger, 'info')
-        qid = subprocess.check_output("qsub %s" % job_name, shell=True)
-        print qid.split('.')[0]
-    elif cluster == "parallel-cluster":
-        call("qsub %s" % job_name, logger)
-        keep_logging('Submitting parallel-cluster Job: qsub %s' % job_name, 'Submitting parallel-cluster Job: qsub %s' % job_name, logger, 'info')
-        qid = subprocess.check_output("qsub %s" % job_name, shell=True)
-        print qid.split('.')[0]
-    #keep_logging('You can check the job status with: qstat -u USERNAME', 'You can check the job status with: qstat -u USERNAME', logger, 'info')
-
-
-""" Start of Main Method/Pipeline """
-if __name__ == '__main__':
-    print set_global_variable.log_unique_time
-    args = parser().parse_args()
-    if args.output_folder != '':
-        args.output_folder += '/'
-    make_sure_path_exists(set_global_variable.logs_folder)
-    make_sure_path_exists(args.output_folder)
-
-    # Run pipeline steps
-    if "core" not in args.steps and "core_prep" not in args.steps and "report" not in args.steps and "tree" not in args.steps:
-        vc_logs_folder = logs_folder + "/variant_calling"
-        make_sure_path_exists(vc_logs_folder)
-        logger = generate_logger(vc_logs_folder, args.analysis_name, log_unique_time)
-        call("cp %s %s/%s_%s_config_copy.txt" % (config_file, vc_logs_folder, log_unique_time, args.analysis_name), logger)
-        if args.cluster:
-            cluster_mode = args.cluster
-        else:
-            cluster_mode = "local"
-
-        keep_logging('START: Variant Calling Pipeline', 'START: Variant Calling Pipeline', logger, 'info')
-
-        list_of_files = get_filenames(args.dir, args.type, args.filenames, args.analysis_name, args.suffix)
-        list_of_jobs = create_varcall_jobs(list_of_files, args.type, args.output_folder, args.index, args.steps, config_file, logger)
-        run_varcall_jobs(list_of_jobs, cluster_mode, log_unique_time, args.analysis_name, args.output_folder, logger)
-        time_taken = datetime.now() - start_time_2
-        keep_logging('Logs were recorded in file with extension log.txt in %s' % vc_logs_folder, 'Logs were recorded in file with extension log.txt in %s' % vc_logs_folder, logger, 'info')
-        keep_logging('Total Time taken: {}'.format(time_taken), 'Total Time taken: {}'.format(time_taken), logger, 'info')
-        keep_logging('End: Variant calling Pipeline', 'End: Variant calling Pipeline', logger, 'info')
-
-    elif "core_prep" in args.steps:
-        core_prep_logs_folder = logs_folder + "/core_prep"
-        make_sure_path_exists(core_prep_logs_folder)
-        logger = generate_logger(core_prep_logs_folder, args.analysis_name, log_unique_time)
-        keep_logging('START: Extract core snps and generate diagnostic plots', 'START: Extract core snps and generate diagnostic plots', logger, 'info')
-        call("cp %s %s/%s_%s_config_copy.txt" % (config_file, core_prep_logs_folder, log_unique_time, args.analysis_name), logger)
-        core_temp_dir = args.output_folder + "/core_temp_dir/"
-        make_sure_path_exists(core_temp_dir)
-        keep_logging('Copying vcf files to %s' % core_temp_dir, 'Copying vcf files to %s' % core_temp_dir, logger, 'info')
-        cp_command = "cp %s/*/*_filter2_indel_final.vcf %s/*/*_aln_mpileup_raw.vcf %s/*/*_raw.vcf_5bp_indel_removed.vcf.gz %s/*/*filter2_final.vcf.gz %s/*/*vcf_no_proximate_snp.vcf.gz %s/*/*array %s/*/*unmapped.bed_positions %s" % (args.output_folder, args.output_folder, args.output_folder, args.output_folder, args.output_folder, args.output_folder, args.output_folder, core_temp_dir)
-        call(cp_command, logger)
-        list_of_gzipped_files = glob.glob("%s/*.gz" % core_temp_dir)
-        keep_logging('Decompressing gzipped files in %s' % core_temp_dir, 'Decompressing gzipped files in %s' % core_temp_dir, logger, 'info')
-        gzipped_command_list = []
-        for i in list_of_gzipped_files:
-            gzipped_command_list.append("gzip -df %s" % i)
-        num_cores = multiprocessing.cpu_count()
-        results = Parallel(n_jobs=num_cores)(delayed(run_command_list)(i) for i in gzipped_command_list)
-        if args.filenames:
-            list_of_files = get_filenames(args.dir, args.type, args.filenames, args.analysis_name, args.suffix)
-            list_of_vcf_files = generate_custom_vcf_file_list(list_of_files, logger)
-            print len(list_of_vcf_files)
-            with open("%s/vcf_filenames" % core_temp_dir, 'w') as out_fp:
-                for file in list_of_vcf_files:
-                    out_fp.write(os.path.basename(file)+'\n')
-            out_fp.close()
-        else:
-            call("ls -1a %s/*.vcf_no_proximate_snp.vcf > %s/vcf_filenames" % (core_temp_dir,core_temp_dir), logger)
-            list_cmd = "ls -1a %s/*.vcf_no_proximate_snp.vcf" % core_temp_dir
-            list_of_files = subprocess.check_output(list_cmd, shell=True)
-            with open("%s/vcf_filenames" % core_temp_dir, 'w') as out_fp:
-                for file in list_of_files.splitlines():
-                    out_fp.write(os.path.basename(file)+'\n')
-            out_fp.close()
-        reference = ConfigSectionMap(args.index, Config)['ref_path'] + "/" + ConfigSectionMap(args.index, Config)['ref_name']
-        run_core_prep_analysis(core_temp_dir, reference, args.analysis_name, log_unique_time, args.cluster, logger, config_file)
-        time_taken = datetime.now() - start_time_2
-        keep_logging('Logs were recorded in file with extension log.txt in %s' % core_prep_logs_folder, 'Logs were recorded in file with extension log.txt in %s' % core_prep_logs_folder, logger, 'info')
-        keep_logging('Total Time taken: {}'.format(time_taken), 'Total Time taken: {}'.format(time_taken), logger, 'info')
-
-    elif "core" in args.steps:
-        core_logs_folder = logs_folder + "/core"
-        make_sure_path_exists(core_logs_folder)
-        logger = generate_logger(core_logs_folder, args.analysis_name, log_unique_time)
-        keep_logging('START: Extract core snps and generate diagnostic plots', 'START: Extract core snps and generate diagnostic plots', logger, 'info')
-        call("cp %s %s/%s_%s_config_copy.txt" % (config_file, core_logs_folder, log_unique_time, args.analysis_name), logger)
-        core_temp_dir = args.output_folder + "/core_temp_dir/"
-        core_results_dir = args.output_folder + "/%s_core_results/" % log_unique_time
-        #make_sure_path_exists(core_results_dir)
-        if args.filenames:
-            list_of_files = get_filenames(args.dir, args.type, args.filenames, args.analysis_name, args.suffix)
-            list_of_vcf_files = generate_custom_vcf_file_list(list_of_files, logger)
-            list_of_label_files = []
-            for i in list_of_vcf_files:
-                list_of_label_files.append(i + '_positions_label')
-            if len(list_of_label_files) == len(list_of_vcf_files):
-                for i in list_of_label_files:
-                    if os.stat("%s/%s" % (core_temp_dir, i)).st_size == 0:
-                        keep_logging('The file {} is empty. Please rerun core_prep step again.\n'.format(i), 'The file {} is empty. Please rerun core_prep step again.\n'.format(i), logger, 'exception')
-                        exit()
-            else:
-                keep_logging('Problem in core_prep results. Rerun the core_prep step\n', 'Problem in core_prep results. Rerun the core_prep step\n', logger, 'exception')
-                exit()
-            with open("%s/vcf_filenames" % core_temp_dir, 'w') as out_fp:
-                for file in list_of_vcf_files:
-                    out_fp.write(os.path.basename(file)+'\n')
-            out_fp.close()
-        else:
-            list_of_label_files = glob.glob("%s/*_no_proximate_snp.vcf_positions_label" % core_temp_dir)
-            list_of_vcf_files = glob.glob("%s/*_filter2_final.vcf_no_proximate_snp.vcf" % core_temp_dir)
-            if len(list_of_label_files) == len(list_of_vcf_files):
-                for i in list_of_label_files:
-                    if os.stat(i).st_size == 0:
-                        keep_logging('The file {} is empty. Please rerun core_prep step again.\n'.format(i), 'The file {} is empty. Please rerun core_prep step again.\n'.format(i), logger, 'exception')
-                        exit()
-            else:
-                keep_logging('Problem in core_prep results. Rerun the core_prep step\n', 'Problem in core_prep results. Rerun the core_prep step\n', logger, 'exception')
-                exit()
-            with open("%s/vcf_filenames" % core_temp_dir, 'w') as out_fp:
-                for file in list_of_vcf_files:
-                    out_fp.write(os.path.basename(file)+'\n')
-            out_fp.close()
-        reference = ConfigSectionMap(args.index, Config)['ref_path'] + "/" + ConfigSectionMap(args.index, Config)['ref_name']
-        run_core_analysis(core_temp_dir, reference, args.analysis_name, log_unique_time, args.cluster, logger, core_results_dir, config_file)
-        time_taken = datetime.now() - start_time_2
-        keep_logging('Logs were recorded in file with extension log.txt in %s' % core_logs_folder, 'Logs were recorded in file with extension log.txt in %s' % core_logs_folder, logger, 'info')
-        keep_logging('Total Time taken: {}'.format(time_taken), 'Total Time taken: {}'.format(time_taken), logger, 'info')
-
-    elif "report" in args.steps:
-        report_logs_folder = logs_folder + "/report"
-        make_sure_path_exists(report_logs_folder)
-        logger = generate_logger(report_logs_folder, args.analysis_name, log_unique_time)
-        keep_logging('START: Generating alignment and variant calling report', 'START: Generating alignment and variant calling report', logger, 'info')
-        call("cp %s %s/%s_%s_config_copy.txt" % (config_file, report_logs_folder, log_unique_time, args.analysis_name), logger)
-        core_temp_dir = args.output_folder + "/core_temp_dir/"
-        core_results_dir = args.output_folder + "/%s_core_results/" % log_unique_time
-        make_sure_path_exists(core_results_dir)
-        list_of_label_files = glob.glob("%s/*_label" % core_temp_dir)
-        list_of_vcf_files = []
-        with open("%s/vcf_filenames" % core_temp_dir, 'r') as out_fp:
-            for line in out_fp:
-                list_of_vcf_files.append(line)
-        for i in list_of_label_files:
-            if os.stat(i).st_size == 0:
-                keep_logging('The file {} is empty. Please rerun core_prep step again.\n'.format(i), 'The file {} is empty. Please rerun core_prep step again.\n'.format(i), logger, 'exception')
-                exit()
-        reference = ConfigSectionMap(args.index, Config)['ref_path'] + "/" + ConfigSectionMap(args.index, Config)['ref_name']
-        run_report_analysis(core_temp_dir, reference, args.analysis_name, log_unique_time, args.cluster, logger, core_results_dir, config_file)
-        time_taken = datetime.now() - start_time_2
-        keep_logging('Logs were recorded in file with extension log.txt in %s' % report_logs_folder, 'Logs were recorded in file with extension log.txt in %s' % report_logs_folder, logger, 'info')
-        keep_logging('Total Time taken: {}'.format(time_taken), 'Total Time taken: {}'.format(time_taken), logger, 'info')
-
-    elif "tree" in args.steps:
-        tree_logs_folder = logs_folder + "/tree"
-        make_sure_path_exists(tree_logs_folder)
-        logger = generate_logger(tree_logs_folder, args.analysis_name, log_unique_time)
-        keep_logging('START: Generating FastTree and RAxML trees', 'START: Generating FastTree and RAxML trees', logger, 'info')
-        call("cp %s %s/%s_%s_config_copy.txt" % (config_file, tree_logs_folder, log_unique_time, args.analysis_name), logger)
-        core_temp_dir = args.output_folder + "/core_temp_dir/"
-        #core_results_dir = args.output_folder + "/%s_core_results/" % log_unique_time
-        proc = subprocess.Popen(["ls -1ad *_core_results | tail -n1"], stdout=subprocess.PIPE, shell=True)
-        (out2, err2) = proc.communicate()
-        core_results_dir = args.output_folder + "/" + out2.strip()
-        list_of_label_files = glob.glob("%s/*_label" % core_temp_dir)
-        list_of_vcf_files = []
-        with open("%s/vcf_filenames" % core_temp_dir, 'r') as out_fp:
-            for line in out_fp:
-                list_of_vcf_files.append(line)
-        for i in list_of_label_files:
-            if os.stat(i).st_size == 0:
-                keep_logging('The file {} is empty. Please rerun core_prep step again.\n'.format(i), 'The file {} is empty. Please rerun core_prep step again.\n'.format(i), logger, 'exception')
-                exit()
-        reference = ConfigSectionMap(args.index, Config)['ref_path'] + "/" + ConfigSectionMap(args.index, Config)['ref_name']
-        run_tree_analysis(core_temp_dir, reference, args.analysis_name, log_unique_time, args.cluster, logger, core_results_dir, config_file)
-        time_taken = datetime.now() - start_time_2
-        keep_logging('Logs were recorded in file with extension log.txt in %s' % tree_logs_folder, 'Logs were recorded in file with extension log.txt in %s' % tree_logs_folder, logger, 'info')
-        keep_logging('Total Time taken: {}'.format(time_taken), 'Total Time taken: {}'.format(time_taken), logger, 'info')
-
-
-    else:
-        logger = generate_logger(logs_folder, args.analysis_name, log_unique_time)
-        keep_logging('Please provide argument -steps to run pipeline', 'Please provide argument -steps to run pipeline', logger, 'info')
-        time_taken = datetime.now() - start_time_2
-        keep_logging('Logs were recorded in file with extension log.txt in %s' % logs_folder, 'Logs were recorded in file with extension log.txt in %s' % logs_folder, logger, 'info')
-        keep_logging('Total Time taken: {}'.format(time_taken), 'Total Time taken: {}'.format(time_taken), logger, 'info')
-
-
-    ## Changed this to individual steps log folder in Logs folder
-    #logger = generate_logger(logs_folder, args.analysis_name, log_unique_time)
-    # time_taken = datetime.now() - start_time_2
-    # keep_logging('Logs were recorded in file with extension log.txt in Logs folder placed in output folder', 'Logs were recorded in file with extension log.txt in Logs folder placed in output folder', logger, 'info')
-    # keep_logging('Total Time taken: {}'.format(time_taken), 'Total Time taken: {}'.format(time_taken), logger, 'info')

From 78156d4bf82992687d1a4a1b50d5ed0c3b1895f8 Mon Sep 17 00:00:00 2001
From: Ali Pirani <alipirani88@gmail.com>
Date: Wed, 24 Oct 2018 12:17:52 -0400
Subject: [PATCH 8/9] Updating Pipeline

---
 modules/variant_diagnostics/core_pipeline.py |  5 ++++-
 variant_call.py                              | 13 +++++--------
 2 files changed, 9 insertions(+), 9 deletions(-)

diff --git a/modules/variant_diagnostics/core_pipeline.py b/modules/variant_diagnostics/core_pipeline.py
index 1dd2a96..f4b3fea 100644
--- a/modules/variant_diagnostics/core_pipeline.py
+++ b/modules/variant_diagnostics/core_pipeline.py
@@ -3065,13 +3065,14 @@ def someOtherFunc(data, key):
         move_core_vcf_fasta_results = "mv %s/*_core.vcf.gz* %s/*_ANN* %s/*.fa %s/" % (args.filter2_only_snp_vcf_dir, args.filter2_only_snp_vcf_dir, args.filter2_only_snp_vcf_dir, core_vcf_fasta_dir)
         move_consensus_var_fasta_results = "mv %s/*_variants.fa %s/" % (core_vcf_fasta_dir, consensus_var_dir)
         move_consensus_ref_var_fasta_results = "mv %s/*.fa %s/" % (core_vcf_fasta_dir, consensus_ref_var_dir)
-        move_core_vcf = "mv %s/*_core.vcf.gz %s/" % (core_vcf_fasta_dir, core_vcf_dir)
+        move_core_vcf = "mv %s/*_core.vcf.gz %s/*vcf_core.vcf.gz.tbi %s/" % (core_vcf_fasta_dir, core_vcf_fasta_dir, core_vcf_dir)
         move_consensus_allele_var_fasta_results = "mv %s/*allele_variants.fa %s/" % (consensus_var_dir, consensus_allele_var_dir)
         move_consensus_ref_allele_var_fasta_results = "mv %s/*_ref_allele_variants.fa %s/" % (
             consensus_allele_var_dir, consensus_ref_allele_var_dir)
         move_consensus_ref_allele_unmapped_var_fasta_results = "mv %s/*_ref_allele_unmapped_variants.fa %s/" % (
             consensus_var_dir, consensus_ref_allele_unmapped_variant_dir)
         move_snpeff_results = "mv %s/*ANN* %s/" % (data_matrix_dir, data_matrix_snpeff_dir)
+        move_snpeff_vcf_results = "mv %s/*ANN* %s/" % (core_vcf_fasta_dir, data_matrix_snpeff_dir)
         copy_reference = "cp %s %s/%s.fa" % (args.reference, consensus_ref_var_dir, reference_base)
         copy_reference_2 = "cp %s %s/%s.fa" % (args.reference, consensus_ref_allele_var_dir, reference_base)
 
@@ -3086,6 +3087,7 @@ def someOtherFunc(data, key):
         call("%s" % copy_reference, logger)
         call("%s" % copy_reference_2, logger)
         call("%s" % move_snpeff_results, logger)
+        call("%s" % move_snpeff_vcf_results, logger)
         subprocess.call(["sed -i 's/title_here/%s/g' %s/generate_diagnostics_plots.R" % (os.path.basename(args.results_dir), data_matrix_dir)], shell=True)
 
         # Sanity Check if the variant consensus files generated are of same length
@@ -3223,6 +3225,7 @@ def someOtherFunc(data, key):
         # raxml(tree_dir, prepare_ref_allele_var_consensus_input, args.jobrun, logger, Config)
 
         if args.gubbins and args.gubbins == "yes":
+            os.chdir(gubbins_dir)
             call("%s/scripts/gubbins_iqtree_raxml.sh %s 1" % (os.path.dirname(os.path.abspath(__file__)), prepare_ref_var_consensus_input), logger)
             call("%s/scripts/gubbins_iqtree_raxml.sh %s 1" % (os.path.dirname(os.path.abspath(__file__)), prepare_ref_allele_unmapped_consensus_input), logger)
             #call("%s/scripts/gubbins_iqtree_raxml.sh %s 1" % (os.path.dirname(os.path.abspath(__file__)), prepare_ref_allele_var_consensus_input), logger)
diff --git a/variant_call.py b/variant_call.py
index 218e401..cbcb23d 100644
--- a/variant_call.py
+++ b/variant_call.py
@@ -29,16 +29,13 @@ def parser():
     required.add_argument('-outdir', action='store', dest="output_folder", help='Output Folder Path ending with output directory name to save the results. Creates a new output directory path if it doesn\'t exist. NOTE: Provide full/absolute path.', required=True)
     required.add_argument('-index', action='store', dest="index", help='Reference Index Name. Most Frequently used reference genomes index options: KPNIH1 | MRSA_USA_300 | MRSA_USA_100 | CDIFF_630 | paris Make sure the paths are properly set in config file', required=True)
     required.add_argument('-steps', action='store', dest="steps", help='Variant Calling Steps in sequential order.\n'
-                                                                     '1.   All: This will run all the steps starting from cleaning the reads to variant calling;\n'
-                                                                     '2.   clean,align,post-align,varcall,filter,stats : This will also run all steps starting from cleaning to variant calling. \nYou can also run part of the pipeline by giving "align,post-align,varcall,filter,stats" which will skip the cleaning part.\nThe order is required to be sequential while using this option. Also, while skipping any of the step make sure you have results already present in your output folder.\n'
-                                                                     '3.   coverage_depth_stats: Run Only Depth of Coverage Stats module after cleaning and read mapping steps\n'
-                                                                     '4.   core_prep: Run this step before running the core steps. This will prepare the data required for generating core SNPs\n'
-                                                                     '5.   core: extract core snps and generate diagnostics plot data matrices to explore filtered snps.')
+                                                                     '1.   All: Run all variant calling  steps starting from trimming the reads, mapping, post-processing the alignments and calling variants;\n'
+                                                                     '2.   core_All: Extract core snps and generate different types of alignments, SNP/Indel Matrices and diagnostics plots.')
     required.add_argument('-analysis', action='store', dest="analysis_name", help='Unique analysis name that will be used as prefix to saving results and log files.', required=True)
     optional.add_argument('-config', action='store', dest="config", help='Path to Config file, Make sure to check config settings before running pipeline', required=False)
     optional.add_argument('-suffix', action='store', dest="suffix", help='Fastq reads suffix such as fastq, fastq.gz, fq.gz, fq; Default: fastq.gz', required=False)
     optional.add_argument('-filenames', action='store', dest="filenames", help='fastq filenames with one single-end filename per line. \nIf the type is set to PE, it will detect the second paired-end filename with the suffix from first filename. \nUseful for running variant calling pipeline on selected files in a reads directory or extracting core snps for selected samples in input reads directory. \nOtherwise the pipeline will consider all the samples available in reads directory.', required=False)
-    optional.add_argument('-cluster', action='store', dest='cluster', help='Run variant calling pipeline in one of the four modes. Default: local. Suggested mode for core snp is cluster that will run all the steps in parallel with the available cores. Make sure to provide a large memory node for this option\nThe possible modes are: cluster/parallel-cluster/parallel-local/local\ncluster: Runs all the jobs on a single large cluster. This will mimic the local run but rather on a large compute node.\nparallel-cluster: Submit variant call jobs for each sample in parallel on compute nodes. This mode is no available for core snp extraction step.\nparallel-local: Run variant call jobs for each sample in parallel locally.\nlocal: Run variant call jobs locally.\nMake Sure to check if the [scheduler] section in config file is set up correctly for your cluster.')
+    optional.add_argument('-cluster', action='store', dest='cluster', help='Run variant calling pipeline in one of the four modes. Default: local. Suggested mode for core snp is \"cluster\" that will run all the steps in parallel with the available cores. Make sure to provide a large memory node for this option\nThe possible modes are: cluster/parallel-local/local\nSet your specific hpc cluster parameters in config file under the [scheduler] section. Supports only PBS scheduling system. ')
     optional.add_argument('-clean', action="store_true", help='clean up intermediate files. Default: OFF')
     optional.add_argument('-extract_unmapped', action='store', dest="extract_unmapped", help='Extract unmapped reads, assemble it and detect AMR genes using ariba')
     optional.add_argument('-datadir', action='store', dest="datadir", help='Path to snpEff data directory')
@@ -297,7 +294,7 @@ def run_varcall_jobs(list_of_jobs, cluster, log_unique_time, analysis_name, outp
         # print qid.split('.')[0]
         # keep_logging('You can check the job status with: qstat -u USERNAME', 'You can check the job status with: qstat -u USERNAME', logger, 'info')
 
-        keep_logging('Running Jobs in parallel-cluster mode', 'Running Jobs in parallel-cluster mode', logger, 'info')
+        keep_logging('Running Jobs in cluster mode', 'Running Jobs in cluster mode', logger, 'info')
         for job in command_list_qsub:
             keep_logging('Submitting Job: qsub %s' % job, 'Submitting Job: qsub %s' % job, logger, 'info')
             call("qsub %s" % job, logger)
@@ -583,7 +580,7 @@ def run_tree_analysis(core_temp_dir, reference, analysis_name, log_unique_time,
     Config.read(config_file)
 
     # Run pipeline steps
-    if "core" not in args.steps and "core_prep" not in args.steps and "report" not in args.steps and "tree" not in args.steps:
+    if "core_All" not in args.steps and "core" not in args.steps and "core_prep" not in args.steps and "report" not in args.steps and "tree" not in args.steps:
         """ Set Up variant calling logs folder/logger object, cluster mode and copy config files to it"""
         vc_logs_folder = logs_folder + "/variant_calling"
         make_sure_path_exists(vc_logs_folder)

From 7b2c92a5aa76895d2a815d185b3d861945add2be Mon Sep 17 00:00:00 2001
From: Ali Pirani <alipirani88@gmail.com>
Date: Thu, 1 Nov 2018 14:36:34 -0400
Subject: [PATCH 9/9] Integrating Beast Pipeline

---
 config_ali                                    |  17 +-
 modules/beast/SCOTTI_generate_xml.py          | 412 ++++++++++++++++++
 modules/beast/add_invariant_sites_beast.sh    |  14 +
 modules/beast/beast.py                        | 116 +++++
 modules/beast/beast_pbs_flux.pl               |  99 +++++
 modules/beast/change_prefixes_beast_xml.sh    |  24 +
 modules/beast/countInvarSites.py              |  56 +++
 modules/beast/fasta_functions.py              | 246 +++++++++++
 modules/beast/fasta_functions.pyc             | Bin 0 -> 1435 bytes
 .../beast/generate_input_file_beast_pbs.sh    |  12 +
 modules/beast/get_num_invariant_sites_v2.py   |  89 ++++
 modules/beast/insert_starting_tree_beast.sh   |  17 +
 modules/beast/scotti.py                       |  31 ++
 modules/phage_detection.py                    |   5 +-
 modules/phage_detection.pyc                   | Bin 5607 -> 5607 bytes
 modules/variant_diagnostics/core_pipeline.py  |  25 +-
 .../mask_gubbins_variants.py                  |  10 +-
 variant_call.py                               |  19 +-
 variant_calling_pipeline_dev/other            |   1 -
 19 files changed, 1164 insertions(+), 29 deletions(-)
 create mode 100644 modules/beast/SCOTTI_generate_xml.py
 create mode 100755 modules/beast/add_invariant_sites_beast.sh
 create mode 100644 modules/beast/beast.py
 create mode 100755 modules/beast/beast_pbs_flux.pl
 create mode 100755 modules/beast/change_prefixes_beast_xml.sh
 create mode 100644 modules/beast/countInvarSites.py
 create mode 100755 modules/beast/fasta_functions.py
 create mode 100644 modules/beast/fasta_functions.pyc
 create mode 100755 modules/beast/generate_input_file_beast_pbs.sh
 create mode 100755 modules/beast/get_num_invariant_sites_v2.py
 create mode 100755 modules/beast/insert_starting_tree_beast.sh
 create mode 100644 modules/beast/scotti.py
 delete mode 160000 variant_calling_pipeline_dev/other

diff --git a/config_ali b/config_ali
index 39e946b..0afa147 100644
--- a/config_ali
+++ b/config_ali
@@ -14,8 +14,8 @@ binbase: /nfs/esnitkin/bin_group/variant_calling_bin/
 resources: nodes=1:ppn=4,pmem=4000mb,walltime=250:00:00
 large_resources: nodes=1:ppn=12,mem=47gb,walltime=250:00:00
 email: apirani@med.umich.edu
-queue: flux
-flux_account: esnitkin_flux
+queue: fluxod
+flux_account: esnitkin_fluxod
 notification: ae
 
 # Set Parameters for individual tools. Set the binbase of each tool: This should be the folder name of respective tools where the executables for each resp. tool resides.
@@ -274,6 +274,12 @@ Ref_Name: cdiff_630.fasta
 # path to the reference genome fasta file.
 Ref_Path: /nfs/esnitkin/bin_group/variant_calling_bin/reference/CDIFF_630/
 
+[CDIFF_630_ncbi]
+# Name of reference genome fasta file.
+Ref_Name: cdiff_630.fasta
+# path to the reference genome fasta file.
+Ref_Path: /nfs/esnitkin/bin_group/variant_calling_bin/reference/CDIFF_630_ncbi/
+
 [Cdiff_VPI10463]
 # Name of reference genome fasta file.
 Ref_Name: Cdiff_VPI10463.fasta
@@ -974,3 +980,10 @@ Ref_Path: /nfs/esnitkin/bin_group/variant_calling_bin/reference/MRSA_Newman/
 Ref_Name: AB030.fasta
 # path to the reference genome fasta file.
 Ref_Path: /nfs/esnitkin/bin_group/variant_calling_bin/reference/AB030/
+
+
+[Steno_K279a]
+# Name of reference genome fasta file.
+Ref_Name: Steno_K279a.fasta
+# path to the reference genome fasta file.
+Ref_Path: /nfs/esnitkin/bin_group/variant_calling_bin/reference/Steno_K279a/
diff --git a/modules/beast/SCOTTI_generate_xml.py b/modules/beast/SCOTTI_generate_xml.py
new file mode 100644
index 0000000..49dfc07
--- /dev/null
+++ b/modules/beast/SCOTTI_generate_xml.py
@@ -0,0 +1,412 @@
+import sys
+import os
+import math
+import argparse
+#import random
+#import re
+#import os.path
+#import math
+
+#does it represent an integer?
+def IsInt(s):
+    try: 
+        int(s)
+        return True
+    except ValueError:
+        return False
+
+#does it represent an integer?
+def IsFloat(s):
+    try: 
+        float(s)
+        return True
+    except ValueError:
+        return False
+
+#make tree string into format for mugration
+def removeStates(treeString):
+	l=len(treeString)
+	newString=""
+	i=0
+	while i < l :
+		if treeString[i]=="[":
+			while treeString[i]!="]":
+				i+=1
+			i+=1
+		newString+=treeString[i]
+		i+=1
+	return newString		
+
+#scale branch lengths 
+def scaleTreeString(treeString,scale):
+	l=len(treeString)
+	newString=""
+	i=0
+	while i < l :
+		if treeString[i]==":":
+			newString+=":"
+			numb=""
+			i+=1
+			while treeString[i]!="," and treeString[i]!=")" and treeString[i]!=";":
+				numb+=treeString[i]
+				i+=1
+			newString+=str(float(numb)*scale)
+		newString+=treeString[i]
+		i+=1
+	return newString
+
+
+parser = argparse.ArgumentParser()
+#parser.add_argument('--template',"-t", help='the file SCOTTI_template.xml with path. It will be used as template to generate the xml file.',default=os.path.dirname(os.path.abspath(__file__))+"SCOTTI_template.xml")
+parser.add_argument('--fasta',"-f", help='Input fasta alignment. If not specified, looks in th working directory for SCOTTI_aligment.fas',default=os.getcwd()+"SCOTTI_alignment.fas")
+parser.add_argument('--output',"-o", help='output file that will contain the newly created SCOTTI xml to be run with BEAST2.',default=os.getcwd()+"SCOTTI_analysis")
+parser.add_argument('--overwrite',"-ov", action='store_true', help="Overwrite output files.")#, dest='overW'
+parser.set_defaults(overwrite=False)
+parser.add_argument('--dates',"-d", help='Input csv file with sampling dates associated to each sample name (same name as fasta file). If not specified, looks for SCOTTI_dates.csv',default=os.getcwd()+"SCOTTI_dates.csv")
+parser.add_argument('--hosts',"-ho", help='Input csv file with sampling hosts associated to each sample name (same name as fasta file). If not specified, looks for SCOTTI_hosts.csv',default=os.getcwd()+"SCOTTI_hosts.csv")
+parser.add_argument('--hostTimes',"-ht", help='Input csv file with the earliest times in which hosts are infectable, and latest time when hosts are infective. Use same host names as those used for the sampling hosts file. If not specified, looks for SCOTTI_hostTimes.csv',default=os.getcwd()+"SCOTTI_hostTimes.csv")
+parser.add_argument('--maxHosts',"-m", help='Maximum number of hosts (between sampled, non-sampled, and non-observed) allowed.', type=int, default=-1)
+parser.add_argument('--unlimLife',"-u", action='store_true', help="non-sampled, non-observed hosts have unlimited life span (unlimited contribution in time to the outbreak). By default non-sampled non-observed hosts have limited duration. Usually asymptomaic patients have limited contributions, while to model environmental contamination it's better to use unlimited hosts. Unlimited life span can also decrease computational demand.")#, dest='limL', action='store_true'
+parser.set_defaults(unlimLife=False)
+parser.add_argument('--penalizeMigration',"-p", action='store_true', help="penalize lineages that are still in a deme after deme closure. By default, don't (original version).")#, dest='limL', action='store_true'
+parser.set_defaults(penalizeMigration=False)
+parser.add_argument('--numIter',"-n", help='Number of iterations of the MCMC. Default=100,000,000.', type=int, default=100000000)
+parser.add_argument('--mutationModel',"-mu", help='String represnting the mutation model to be used. Possibilities are \"HKY\" or \"JC\". Further alternaties can be specified by modifying the output xml manually.', default="HKY")
+parser.add_argument('--fixedAs', "-fA", type=int, help = 'Number of sites fixed for A in the genome and not included in the alignment.',default=0)
+parser.add_argument('--fixedCs', "-fC", type=int, help = 'Number of sites fixed for C in the genome and not included in the alignment.',default=0)
+parser.add_argument('--fixedGs', "-fG", type=int, help = 'Number of sites fixed for G in the genome and not included in the alignment.',default=0)
+parser.add_argument('--fixedTs', "-fT", type=int, help = 'Number of sites fixed for T in the genome and not included in the alignment.',default=0)
+
+args = parser.parse_args()
+
+
+#if !(os.path.isfile(args.template)):
+#    print "Error: template file SCOTTI_template.xml not found, please specify it correctly in input using the option -t .\n"
+#    exit()
+if (not (os.path.isfile(args.fasta))):
+    print "Error: input fasta file not found, please specify it correctly in input using the option -f .\n"
+    exit()
+if (os.path.isfile(args.output + ".xml")) and (not args.overwrite):
+    print "Output xml file already exists, to allow overwriting of output file use option -ov, otherwise specify a different output file.\n"
+    exit()
+if not (os.path.isfile(args.dates)):
+    print "Error: input dates csv file not found, please specify it correctly in input using the option -d .\n"
+    exit()
+if not (os.path.isfile(args.hosts)):
+    print "Error: input hosts csv file not found, please specify it correctly in input using the option -s .\n"
+    exit()
+if not (os.path.isfile(args.hostTimes)):
+    print "Error: input hosts csv file not found, please specify it correctly in input using the option -i .\n"
+    exit()
+if (args.numIter<=0):
+    print "Error: the number of MCMC iterations specified is negative or null.\n"
+    exit()
+elif (args.numIter<=1000):
+    print "Very small number of MCMC iterations, might want to specifiy something bigger.\n"
+if (args.mutationModel!="HKY" and args.mutationModel!="JC"):
+    print "Mutation model not supported. Please specify something among \"HKY\" or \"JC\".\n"
+    exit()
+if (args.fixedAs<0 or args.fixedCs<0 or args.fixedGs<0 or args.fixedTs<0):
+    print "Error: the number of fixed sites for each base type must be positive.\n"
+    exit()
+
+#read fasta file
+sqFile=open(args.fasta)
+seqs={}
+line=sqFile.readline()
+linesplit=line.split()
+while line!="" and (len(linesplit)<1 or linesplit[0][0]!=">"):
+    line=sqFile.readline()
+    linesplit=line.split()
+if line=="":
+    print "Wrong format in fasta file\n"
+    exit()
+while line!="":
+    if len(linesplit[0])>1:
+        name=linesplit[0].replace(">","")
+    else:
+        name=linesplit[1]
+    seq=""
+    line=sqFile.readline()
+    linesplit=line.split()
+    while line!="" and (len(linesplit)>0  and linesplit[0][0]!=">") and line!="\n":
+        seq+=linesplit[0]
+        line=sqFile.readline()
+        linesplit=line.split()
+    if name in seqs.keys():
+        print "Error, multiple entries with same name "+name+" in fasta file. Only first part of the name line is used for the name."
+        exit()
+    seqs[name]=seq
+    while line!="" and  (len(linesplit)<1 or linesplit[0][0]!=">"):
+        line=sqFile.readline()
+        linesplit=line.split()
+sqFile.close()
+
+#read in file with host-sample information
+hFile=open(args.hosts)
+hosts={}
+line=hFile.readline()
+linesplit=("".join(line.split())).split(",")  
+while line!="" and len(linesplit)>1: 
+    sam=linesplit[0]
+    hos=linesplit[1]
+    if not (sam in seqs.keys()):
+        print "Error: sample "+sam+" found in sample-host file but not found in the fasta file."
+        exit()
+    if sam in hosts.keys():
+        print "Error, multiple entries with same name "+sam+" in hosts file. "
+        exit()
+    hosts[sam]=hos
+    line=hFile.readline()
+    linesplit=("".join(line.split())).split(",")
+    while line=="\n":
+        line=hFile.readline()
+        linesplit=("".join(line.split())).split(",")
+hFile.close()
+
+#read in sampling dates
+dFile=open(args.dates)
+dates={}
+line=dFile.readline()
+linesplit=("".join(line.split())).split(",")  
+while line!="" and len(linesplit)>1:  
+    sam=linesplit[0]
+    dat=linesplit[1]
+    if not (IsFloat(dat)):
+        print "Error: date "+str(dat)+" for sample "+sam+" cannot be converted to a number"
+        exit()
+    if not (sam in seqs.keys()):
+        print "Error: sample "+sam+" found in sampling dates file but not found in the fasta file."
+        exit()
+    if sam in dates.keys():
+        print "Error, multiple entries with same name "+sam+" in dates file. "
+        exit()
+    dates[sam]=float(dat)
+    line=dFile.readline()
+    linesplit=("".join(line.split())).split(",")
+    while line=="\n":
+        line=dFile.readline()
+        linesplit=("".join(line.split())).split(",")
+dFile.close()
+    
+#read in file with host times information
+hFile=open(args.hostTimes)
+hostT={}
+line=hFile.readline()
+linesplit=("".join(line.split())).split(",")  
+while line!="" and len(linesplit)>2: 
+    hos=linesplit[0]
+    dat=float(linesplit[1])
+    dat2=float(linesplit[2])
+    if (not (IsFloat(dat))) or (not (IsFloat(dat2))):
+        print "Error: date "+str(dat)+" or "+str(dat2)+" for sample "+sam+" cannot be converted to a number"
+        exit()
+    #if not (hos in seqs.keys()):
+    #    print "Error: sample "+hos+" found in host times file but not found in the fasta file."
+    #    exit()
+    if hos in hostT.keys():
+        print "Error, multiple entries with same name "+hos+" in hosts-times file. "
+        exit()
+    hostT[hos]=[dat, dat2]
+    line=hFile.readline()
+    linesplit=("".join(line.split())).split(",")
+    while line=="\n":
+        line=hFile.readline()
+        linesplit=("".join(line.split())).split(",")
+hFile.close()
+
+
+    
+#check that the details are correct
+for s in seqs.keys():
+    if not (s in dates.keys()):
+        print "Error, no date specified for sample "+s
+        exit()
+    if not (s in hosts.keys()):
+        print "Error, no host specified for sample "+s
+        exit()
+for s in hosts.keys():
+    if not (s in seqs.keys()):
+        print "Error, no sequence specified for sample "+s
+        exit()
+    if not (s in dates.keys()):
+        print "Error, no date specified for sample "+s
+        exit()
+for s in dates.keys():
+    if not (s in seqs.keys()):
+        print "Error, no sequence specified for sample "+s
+        exit()
+    if not (s in hosts.keys()):
+        print "Error, no host specified for sample "+s
+        exit()
+for s in hosts.keys():
+    if not (hosts[s] in hostT.keys()):
+        print "Warning: no dates specified for host "+hosts[s]+". I will assume this host is available throghtout"
+        hostT[hosts[s]]=[-1000000000000,1000000000000]
+
+
+for h in hostT.keys():
+    found=0
+    for s in hosts.keys():
+        if hosts[s]==h:
+            found=1
+    if found==0:
+        print "Warning: no sample specified for host "+h+". I will assume this host could have been infected or not. If you are sure this host was infected, then please include a non-informative sample (all \"N\"s) from it."
+
+    
+    
+    
+    
+xml=open(args.output+".xml","w")
+xml.write("<beast version=\'2.0\' namespace=\'beast.evolution.alignment:beast.core:beast.core.parameter:beast.evolution.tree:beast.evolution.tree.coalescent:beast.core.util:beast.evolution.operators:beast.evolution.sitemodel:beast.evolution.substitutionmodel:beast.evolution.likelihood:beast.evolution.tree:beast.math.distributions:multitypetreeVolz.distributions:multitypetreeVolz.operators:multitypetreeVolz.util\'>\n\n"+"  <data id=\"alignmentVar\" dataType=\"nucleotide\">\n")
+for s in seqs.keys():
+    xml.write("    <sequence taxon=\'"+s+"\' value=\'"+seqs[s]+"\'/>\n")
+xml.write("  </data>\n")
+st=""
+if args.fixedAs>0 and args.fixedCs>0 and args.fixedGs>0 and args.fixedTs>0:
+    st="constantSiteWeights=\'"+str(args.fixedAs)+" "+str(args.fixedCs)+" "+str(args.fixedGs)+" "+str(args.fixedTs)+"\'"
+xml.write("  <data id=\'alignment\' spec=\'FilteredAlignment\' filter=\'-\' data=\'@alignmentVar\' "+st+"/>\n\n")
+
+#hosts
+xml.write("   <typeTraitSet spec=\'TraitSetWithLimits\' id=\'typeTraitSet\' traitname=\"type\" value=\"")
+hL=hosts.keys()
+for s in hL:
+    xml.write(s+"="+hosts[s])
+    if s!=hL[len(hL)-1]:
+        xml.write(",")
+xml.write("\">\n     <taxa spec=\'TaxonSet\' alignment=\'@alignment\'/>\n   </typeTraitSet>\n\n")
+
+#dates
+xml.write("   <timeTraitSet spec=\'TraitSetWithLimits\' id=\'timeTraitSet\' traitname=\"date-forward\" value=\"")
+dL=dates.keys()
+for s in range(len(dL)):
+    xml.write(dL[s]+"="+str(dates[dL[s]]))
+    if (s!=(len(dL)-1)):
+        xml.write(",")
+xml.write("\">\n     <taxa spec=\'TaxonSet\' alignment=\'@alignment\'/>\n   </timeTraitSet>\n\n")
+
+#end infectability
+xml.write("   <endInfectionsTraitSet spec=\'InfectionTraitSet\' id=\'endInfectionsTraitSet\' type=\'end\' traitname=\"date-forward\" value=\"")
+dL=hostT.keys()
+for s in dL:
+    xml.write(s+"="+str(hostT[s][1]))
+    if s!=dL[len(dL)-1]:
+        xml.write(",")
+xml.write("\">\n 	  <taxaDates idref=\'timeTraitSet\'/>\n 	  <taxaTypes idref=\'typeTraitSet\'/>\n   </endInfectionsTraitSet>\n\n")
+
+#start infectability
+xml.write("   <startInfectionsTraitSet spec=\'InfectionTraitSet\' id=\'startInfectionsTraitSet\' type=\'start\' traitname=\"date-forward\" value=\"")
+dL=hostT.keys()
+for s in dL:
+    xml.write(s+"="+str(hostT[s][0]))
+    if s!=dL[len(dL)-1]:
+        xml.write(",")
+xml.write("\">\n 	  <taxaDates idref=\'timeTraitSet\'/>\n 	  <taxaTypes idref=\'typeTraitSet\'/>\n   </startInfectionsTraitSet>\n\n")
+
+#check that times fit
+for s in seqs.keys():
+    h=hosts[s]
+    if dates[s]<=hostT[hosts[s]][0]:
+        print "Error, sampling time "+str(dates[s])+" of sample "+s+" must be after start of infectability time "+str(hostT[hosts[s]][0])+" of host "+h
+        exit()
+    if dates[s]>=hostT[hosts[s]][1]:
+        print "Error, sampling time "+str(dates[s])+" of sample "+s+" must be before end of infectiousness time "+str(hostT[hosts[s]][0])+" of host "+h
+        exit()
+
+#include mutation model
+xml.write("   <siteModel spec=\"SiteModel\" id=\"siteModel\">\n     <mutationRate spec=\'RealParameter\' id=\"mutationRate\" value=\"1.0\"/>\n     <substModel spec=\"")
+if args.mutationModel=="HKY":
+   xml.write("HKY\">\n       <kappa spec=\'RealParameter\' id=\"hky.kappa\" value=\"1.0\"/>\n")
+elif args.mutationModel=="JC":
+   xml.write("jc69\">\n")
+elif args.mutationModel=="GTR":
+   xml.write("GTR\" rateAC=\"@rateAC\" rateAG=\"@rateAG\" rateAT=\"@rateAT\" rateCG=\"@rateCG\" rateGT=\"@rateGT\" >\n       <parameter estimate=\'false\' name=\"rateCT\" lower=\"0.0\" value=\"1.0\" id=\"rateCTfixed\"/>\n")
+else:
+    print "Error, mutation model "+args.mutationModel+" not recognized."
+    exit()
+xml.write("       <frequencies estimate=\"false\" spec=\'Frequencies\'>\n	 <frequencies spec=\'RealParameter\' id=\""+args.mutationModel+".freq\" value=\"0.25 0.25 0.25 0.25\"/>\n       </frequencies>\n     </substModel>\n   </siteModel>\n\n")
+              
+#migration model
+nHos=len(hostT.keys())
+meanL=0.0
+for h in hostT.keys():
+    meanL+=hostT[h][1]-hostT[h][0]
+meanL=meanL/len(hostT.keys())
+ma=args.maxHosts
+if ma<nHos:
+    ma=nHos+5
+    print "Maximum number of hosts specified is less than the minimum number of hosts. Setting it to "+str(ma)
+if ma<(nHos+2):
+    print "Warning: the maximum number of hosts is less than "+str(nHos+2)+". If there are problems in the execution of the BEAST2 analysis, try a higher values of maxHosts."
+start=(nHos+ma)/2
+if start<(nHos+2) and ma>=(nHos+2):
+    start=nHos+2
+xml.write("   <migrationModelUniform spec=\'MigrationModelUniform\' id=\'migModel\' minDemes=\'"+str(nHos)+"\'>\n     <rate spec=\'RealParameter\' value=\""+str(1.0/(meanL*nHos))+"\" dimension=\"1\" id=\"rate\"/>\n     <popSize spec=\'RealParameter\' value=\"1.0\" dimension=\"1\" id=\"popSize\"/>\n     <numDemes spec=\'IntegerParameter\' value=\""+str(start)+"\" dimension=\"1\" id=\"numDemes\" lower=\'"+str(nHos)+"\' upper=\'"+str(ma)+"\'/>\n     <trait idref=\'startInfectionsTraitSet\' type=\'start\'/>\n     <trait idref=\'endInfectionsTraitSet\' type=\'end\'/>\n   </migrationModelUniform>\n\n")            
+
+#priors
+xml.write("   <input spec=\'CompoundDistribution\' id=\'parameterPriors\'>\n     <distribution spec=\'beast.math.distributions.Prior\' x=\"@mutationRate\">\n       <distr spec=\'LogNormalDistributionModel\' M=\"-3.0\" S=\"6.0\"/>\n     </distribution>\n     <distribution spec=\'beast.math.distributions.Prior\' x=\"@popSize\">\n       <distr spec=\"LogNormalDistributionModel\"  M=\"0.0\" S=\"6.0\"/>\n     </distribution>\n     <distribution spec=\'beast.math.distributions.Prior\' x=\"@rate\">\n       <distr spec=\'LogNormalDistributionModel\' M=\""+str(math.log(1.0/(meanL*nHos)))+"\" S=\"0.2\"/>\n     </distribution>\n")
+if args.mutationModel=="HKY":
+    xml.write("     <distribution spec=\'beast.math.distributions.Prior\' x=\"@hky.kappa\">\n       <distr spec=\'LogNormalDistributionModel\' M=\"0.0\" S=\"4.0\"/>\n     </distribution>\n   </input>\n\n")
+elif args.mutationModel=="JC":
+   xml.write("   </input>\n\n")
+elif args.mutationModel=="GTR":
+    xml.write("     <distribution spec=\'beast.math.distributions.Prior\' x=\"@rateAC\">\n       <distr spec=\'LogNormalDistributionModel\' M=\"0.0\" S=\"4.0\"/>\n     </distribution>\n     <distribution spec=\'beast.math.distributions.Prior\' x=\"@rateAG\">\n       <distr spec=\'LogNormalDistributionModel\' M=\"0.0\" S=\"4.0\"/>\n     </distribution>\n     <distribution spec=\'beast.math.distributions.Prior\' x=\"@rateAT\">\n       <distr spec=\'LogNormalDistributionModel\' M=\"0.0\" S=\"4.0\"/>\n     </distribution>\n     <distribution spec=\'beast.math.distributions.Prior\' x=\"@rateCG\">\n       <distr spec=\'LogNormalDistributionModel\' M=\"0.0\" S=\"4.0\"/>\n     </distribution>\n     <distribution spec=\'beast.math.distributions.Prior\' x=\"@rateGT\">\n       <distr spec=\'LogNormalDistributionModel\' M=\"0.0\" S=\"4.0\"/>\n     </distribution>\n   </input>\n\n")      
+              
+#Likelihoods
+xml.write("<input spec=\'TreeLikelihood\' id=\"treeLikelihood\">\n     <data idref=\"alignment\"/>\n     <tree idref=\"tree\"/>\n     <siteModel idref=\'siteModel\'/>\n   </input>\n\n   <input spec=\'StructuredCoalescentTreeDensityNew\' id=\'treePrior\' limitedLifespan=\'"+str(args.unlimLife)+"\' penalizeMigration=\'"+str(args.penalizeMigration)+"\'>\n     <multiTypeTreeConcise idref=\"tree\"/>\n     <migrationModelUniform idref=\"migModel\"/>\n   </input>\n\n   <run spec=\"MCMC\" id=\"mcmc\" chainLength=\""+str(args.numIter)+"\" storeEvery=\"10000\">\n\n")
+
+#migration model
+xml.write("     <init spec=\'StructuredCoalescentMultiTypeTreeConcise\' id=\'tree\' nTypes=\""+str(start)+"\">\n         <migrationModelUniform spec=\'MigrationModelUniform\' minDemes=\'"+str(nHos)+"\'>\n             <rate spec=\'RealParameter\' value=\""+str(1.0/(meanL*nHos))+"\" dimension=\"1\"/>\n             <popSize spec=\'RealParameter\' value=\"1.0\" dimension=\"1\"/>\n             <numDemes spec=\'IntegerParameter\' value=\""+str(start)+"\" dimension=\"1\"/>\n         </migrationModelUniform>\n         <trait idref=\'typeTraitSet\'/>\n         <trait idref=\'timeTraitSet\'/>\n     </init>\n\n")              
+              
+#state nodes              
+xml.write("     <state>\n       <stateNode idref=\"tree\"/>\n       <stateNode idref=\"rate\"/>\n       <stateNode idref=\"popSize\"/>\n       <stateNode idref=\"numDemes\"/>\n       <stateNode idref=\"mutationRate\"/>\n")
+if args.mutationModel=="HKY":
+    xml.write("       <stateNode idref=\"hky.kappa\"/>\n")
+elif args.mutationModel=="GTR":              
+    xml.write("       <stateNode idref=\"rateAC\"/>\n       <stateNode idref=\"rateAG\"/>\n       <stateNode idref=\"rateAT\"/>\n       <stateNode idref=\"rateCG\"/>\n       <stateNode idref=\"rateGT\"/>\n")
+xml.write("       <stateNode idref=\""+args.mutationModel+".freq\"/>\n     </state>\n\n")     
+              
+#compound distribution
+xml.write("     <distribution spec=\'CompoundDistribution\' id=\'posterior\'>\n       <distribution idref=\"treeLikelihood\"/>\n       <distribution idref=\'treePrior\'/>\n       <distribution idref=\"parameterPriors\"/>\n     </distribution>\n\n")
+              
+#operators
+xml.write("     <operator spec=\'ScaleOperator\' id=\'RateScaler\' parameter=\"@rate\" scaleFactor=\"0.8\" weight=\"1\"/>\n     <operator spec=\"ScaleOperator\" id=\"PopSizeScaler\" parameter=\"@popSize\" scaleFactor=\"0.8\" weight=\"1\"/>\n     <operator spec=\"ShortRangeUniformOperator\" id=\"NumDemesScaler\" parameter=\"@numDemes\" weight=\"1\"/>\n     <operator spec=\"ScaleOperator\" id=\"muRateScaler\" parameter=\"@mutationRate\" scaleFactor=\"0.8\" weight=\"1\"/>\n     <operator spec=\"DeltaExchangeOperator\" id=\"freqExchanger\" parameter=\"@"+args.mutationModel+".freq\" delta=\"0.01\" weight=\"0.1\"/>\n     <operator id=\'treeScaler.t\' spec=\'ScaleOperator\' scaleFactor=\"0.5\" weight=\"3\" tree=\"@tree\"/>\n     <operator id=\'treeRootScaler.t\' spec=\'ScaleOperator\' scaleFactor=\"0.5\" weight=\"3\" tree=\"@tree\" rootOnly=\'true\'/>\n     <operator id=\'UniformOperator.t\' spec=\'Uniform\' weight=\"30\" tree=\"@tree\"/>\n     <operator id=\'SubtreeSlide.t\' spec=\'SubtreeSlide\' weight=\"15\" gaussian=\"true\" size=\"1.0\" tree=\"@tree\"/>\n     <operator id=\'narrow.t\' spec=\'Exchange\' isNarrow=\'true\' weight=\"15\" tree=\"@tree\"/>\n     <operator id=\'wide.t\' spec=\'Exchange\' isNarrow=\'false\' weight=\"3\" tree=\"@tree\"/>\n     <operator id=\'WilsonBalding.t\' spec=\'WilsonBalding\' weight=\"3\" tree=\"@tree\"/>\n")
+if args.mutationModel=="HKY":
+    xml.write("     <operator spec=\'ScaleOperator\' id=\'kappaScaler\' parameter=\"@hky.kappa\" scaleFactor=\"0.8\" weight=\"0.1\"/>\n")
+elif args.mutationModel=="GTR": 
+    xml.write("     <operator spec=\'ScaleOperator\' id=\'ACScaler\' parameter=\"@rateAC\" scaleFactor=\"0.8\" weight=\"0.1\"/>\n     <operator spec=\'ScaleOperator\' id=\'AGScaler\' parameter=\"@rateAG\" scaleFactor=\"0.8\" weight=\"0.1\"/>\n     <operator spec=\'ScaleOperator\' id=\'ATScaler\' parameter=\"@rateAT\" scaleFactor=\"0.8\" weight=\"0.1\"/>\n     <operator spec=\'ScaleOperator\' id=\'CGScaler\' parameter=\"@rateCG\" scaleFactor=\"0.8\" weight=\"0.1\"/>\n     <operator spec=\'ScaleOperator\' id=\'GTScaler\' parameter=\"@rateGT\" scaleFactor=\"0.8\" weight=\"0.1\"/>\n")
+xml.write("\n")
+
+#loggers
+xml.write("     <logger logEvery=\""+str(args.numIter/10000)+"\" fileName=\""+args.output+".log\">\n       <model idref=\'posterior\'/>\n       <log idref=\"posterior\"/>       <log idref=\"treeLikelihood\"/>\n       <log idref=\"migModel\"/>\n       <log idref=\"mutationRate\"/>\n       <log spec=\'TreeHeightLogger\' tree=\'@tree\'/>\n       <log idref=\""+args.mutationModel+".freq\"/>\n")
+if args.mutationModel=="HKY":
+    xml.write("       <log idref=\"hky.kappa\"/>\n")
+elif args.mutationModel=="GTR":               
+    xml.write("       <log idref=\"rateAC\"/>\n       <log idref=\"rateAG\"/>\n       <log idref=\"rateAT\"/>\n       <log idref=\"rateCG\"/>\n       <log idref=\"rateGT\"/>\n")
+xml.write("     </logger>\n")
+     
+xml.write("     <logger logEvery=\""+str(args.numIter/5000)+"\" fileName=\""+args.output+".trees\" mode=\"tree\">\n       <log idref=\'treePrior\'/>\n     </logger>\n")
+
+xml.write("     <logger logEvery=\""+str(args.numIter/1000)+"\">\n       <model idref=\'posterior\'/>\n       <log idref=\"posterior\"/>\n       <log idref=\"treeLikelihood\"/>\n       <log spec=\'TreeHeightLogger\' tree=\'@tree\'/>\n       <log idref=\"migModel\"/>\n       <log idref=\"mutationRate\"/>\n       <ESS spec=\'ESS\' name=\'log\' arg=\"@treePrior\"/>\n       <ESS spec=\'ESS\' name=\'log\' arg=\"@posterior\"/>\n     </logger>\n\n   </run>\n </beast>\n\n")
+
+
+
+
+            
+      
+              
+              
+              
+              
+              
+              
+                  
+      
+			
+exit()
+
+
+
+
+
+		
\ No newline at end of file
diff --git a/modules/beast/add_invariant_sites_beast.sh b/modules/beast/add_invariant_sites_beast.sh
new file mode 100755
index 0000000..b65bff4
--- /dev/null
+++ b/modules/beast/add_invariant_sites_beast.sh
@@ -0,0 +1,14 @@
+#!/bin/bash
+
+# input: 
+# (1) beast xml file (ex. beauti output) 
+# (2) number of invariant A's, C's, G's, and T's (in that order)
+# ex. bash add_invariant_sites_beast.sh beast.xml 100 120 130 140
+
+fout=$(echo $(echo $1 | cut -d. -f1)_invSites.xml)
+dataf=$(awk 'NR==1,/data id=\"/' $1 | tail -n1 | cut -d'"' -f2)
+awk 'NR==1,/data id=\"/{sub(/data id=\"/, "data id=\"orig_")} 1' $1 > $fout
+
+sed -ibak "1,/data>/s/data>/&\n\n<data id='${dataf}' \n spec='FilteredAlignment' \n filter='-' \n data='@orig_${dataf}' \n constantSiteWeights='${2} \n ${3} ${4} ${5}'\/> <!-- A C G T -->/" $fout
+
+rm ${fout}bak
diff --git a/modules/beast/beast.py b/modules/beast/beast.py
new file mode 100644
index 0000000..3b155e0
--- /dev/null
+++ b/modules/beast/beast.py
@@ -0,0 +1,116 @@
+# PIPELINE TO RUN BEAST ON FLUX
+
+# Import modules
+import sys
+import os
+import argparse
+from subprocess import call
+import re
+
+# Get command line arguments
+parser = argparse.ArgumentParser(description='Run BEAST pipeline.')
+parser.add_argument('xmls', nargs='*', help='input BEAST xml file(s)')
+parser.add_argument('--n_reps', '-n', metavar='N', type=int, help='number of beast runs for each xml', default=3)
+parser.add_argument('--invar_sites', '-i', metavar='FILE', help='''
+                    option 1: fasta file to  get number of invariant As, Cs, Gs, and Ts not in alignment
+                    option 2: text file with number of invariant As, Cs, Gs, and Ts in alignment''')
+parser.add_argument('--gubbins_gff', '-g', metavar='GFF', help='''gubbins output GFF file to mask recombinant sites in alignment before counting invariant sites''')
+parser.add_argument('--tree', '-t', help='starting tree file in newick format')
+parser.add_argument('-scripts_dir', '-d', metavar='DIR', help='directory where all of the scripts are housed', default='/nfs/esnitkin/bin_group/pipeline/Github/variant_calling_pipeline_dev/modules/beast')
+args = parser.parse_args()
+# Rename variables
+xmls = args.xmls
+n_reps = args.n_reps
+invar_sites = args.invar_sites
+gubbins_gff = args.gubbins_gff
+tree = args.tree
+scripts_dir = args.scripts_dir
+
+# Set paths
+python = '/nfs/esnitkin/bin_group/anaconda3/bin/python'
+mask_vars_path = '/nfs/esnitkin/bin_group/pipeline/Github/variant_calling_pipeline_dev/modules/variant_diagnostics/mask_gubbins_variants.py'
+
+# Get invariant site counts
+if invar_sites is not None:
+    if not invar_sites.endswith(tuple(['fa','fasta'])):
+        # Path to file with invariant site counts
+        invar_counts_file = invar_sites
+    else:
+        # Mask recombinant regions before counting invariant sites
+        if gubbins_gff is not None:
+            call([python, mask_vars_path, invar_sites, gubbins_gff])
+            aln_file = re.split('/|\.', invar_sites)[-2] + \
+                      '_gubbins_masked.fa'
+        else:
+            aln_file = invar_sites
+        # Count invariant sites in whole genome alignment
+        call([python, scripts_dir + '/get_num_invariant_sites_v2.py', aln_file])
+        invar_counts_file = re.split('/|\.', aln_file)[-2] + \
+                          '_invar_site_counts.txt'
+    # Read file with invariant site counts
+    with open(invar_counts_file) as f:
+        invar_counts = f.readline().strip()
+
+
+# Final xmls for beast
+xmls_for_beast = []
+
+# For each xml input file, modify the xml as desired and start beast
+for xml in xmls:
+
+    print('Processing ' + xml + '.')
+
+    # Change prefixes in BEAST xml (more informative when looking at trace files in Tracer)
+    print('Adding xml file name as prefix to sequence data in BEAST xml.')
+    call([scripts_dir + '/change_prefixes_beast_xml.sh', xml])
+
+    # Get newest xml name
+    xml2 = re.split('/|\.', xml)[-2] + '_renamed.xml'
+
+    # Add starting tree, if desired
+    if tree is not None:
+        print('Adding starting tree to BEAST xml.')
+        call([scripts_dir + '/insert_starting_tree_beast.sh', xml2, tree])
+        # Get newest xml name
+        xml3 = re.split('/|\.', xml2)[-2] + '_st.xml'
+    else:
+        xml3 = xml2
+
+    # Get invariant site counts
+    if invar_sites is not None:
+        # Add invariant site counts to xml
+        call([scripts_dir + '/add_invariant_sites_beast.sh', xml3, invar_counts]) #[int(x) for x in invar_counts.split(' ')])
+        # Get newest xml name
+        xml4 = re.split('/|\.', xml3)[-2] + '_invSites.xml'
+    else:
+        xml4 = xml3
+
+    # Final xml file
+    xml_final = xml4
+    print('Final xml for input into beast: ' + xml_final + '.')
+
+    # Delete intermediate xmls
+    to_remove = []
+    for fname in os.listdir('.'):
+        b = re.search('.*_renamed_.*xml', fname)
+        s = fname == xml_final
+        if b and not s:
+            print('Removing intermediate file ' + fname + '.')
+            os.remove(fname)   
+
+    # Add xml file name to list for beast
+    xmls_for_beast.append(xml_final) 
+
+# Generate input file for beast script
+with open('input_beast.txt', 'w') as f:
+    for x in xmls_for_beast:
+        for i in range(n_reps):
+            f.write(x + '\n')
+
+#call([scripts_dir + '/generate_input_file_beast_pbs.sh', ' '.join(xmls_for_beast), n_reps])
+print('input_beast.txt generated.')
+
+# Generate PBS scripts and submit jobs to flux
+print('Generating PBS script(s) and submitting jobs to flux.')
+call(['perl', scripts_dir + '/beast_pbs_flux.pl', 'input_beast.txt'])
+
diff --git a/modules/beast/beast_pbs_flux.pl b/modules/beast/beast_pbs_flux.pl
new file mode 100755
index 0000000..afb2f2a
--- /dev/null
+++ b/modules/beast/beast_pbs_flux.pl
@@ -0,0 +1,99 @@
+#Creates and submits PBS scripts for performing BEAST analysis with desired xmls
+#
+#Takes as input:
+#		1) config_file	- A 1-column file where each line is the file name (minus the .xml extension) for a beast run
+# UPDATED 2017-09-21 from beast2/2.4.5 to beast2/2.4.7
+
+#PRINT USAGE
+if(@ARGV == 0)
+{
+
+	print "\n\nperl beast_PBS.pl config_file\n\n";
+
+	exit;
+
+}#end if
+
+
+#READ IN COMMAND LINE ARGUMENTS
+my $config_file = shift @ARGV;
+
+
+#GO THROUGH EACH LINE OF THE CONFIG FILE, CREATING AND SUBMITTING PBS FILES
+open CONFIG, $config_file;
+my $count = 1;
+
+foreach my $job (<CONFIG>)
+{
+
+	#GET CURRENT ARGUMENTS
+	chomp $job;
+	my ($fnameorig) = split /\t/, $job;
+        my ($fname) = split /\./, $fnameorig;
+
+	#CREATE OUTPUT DIRECTORY
+	my $date = `date +%Y-%m-%d-%H-%M-%S`;
+	chomp $date;
+
+	my $wd = `pwd`;
+	chomp $wd;
+	$out_dir = "$wd/$date\_beast$count\_$fname";
+	mkdir $out_dir;
+
+
+	#CREATE AND WRITE PBS FILE
+	my $rand = int(rand(10000000));
+	my $pbs_file = "beast$count\_$fname\_$rand.pbs";
+
+	open PBS, ">$pbs_file";
+
+	print PBS "#!/bin/sh\n";
+	print PBS "####  PBS preamble\n";
+	print PBS "\n";
+	print PBS "#PBS -N beast$count\_$fname\n";
+	print PBS "\n";
+	print PBS "# User info\n";
+	print PBS "#PBS -M zenalapp\@umich.edu\n";
+	print PBS "#PBS -m abe\n";
+	print PBS "\n";
+	print PBS "# Change the number of cores (ppn=1), amount of memory, and walltime:\n";
+	print PBS "#PBS -l nodes=1:ppn=12,pmem=4gb,walltime=10:00:00:00\n";
+	print PBS "#PBS -j oe\n";
+	print PBS "#PBS -V\n";
+	print PBS "\n";
+	print PBS "#PBS -A esnitkin_flux\n";
+	print PBS "#PBS -q flux\n";
+	print PBS "#PBS -l qos=flux\n";
+	print PBS "\n";
+	print PBS "####  End PBS preamble\n";
+	print PBS "\n";
+	print PBS "#  Show list of CPUs you ran on, if you're running under PBS\n";
+	print PBS "if [ -n \"\$PBS_NODEFILE\" ]; then cat \$PBS_NODEFILE; fi\n";
+	print PBS "\n";
+	print PBS "#  Change to the directory you submitted from\n";
+	print PBS "cd $out_dir";
+	print PBS "\n";
+	print PBS "#Load modules\n";
+	print PBS "module load beast2/2.4.7\n";
+        print PBS "module load beagle\n";
+        #print PBS "addonmanager -add BEAST_CLASSIC\n";
+        #print PBS "addonmanager -add SCOTTI\n";
+	print PBS "\n";
+	print PBS "#  Put your job commands here:\n";
+	print PBS "beast -beagle_SSE -instances 12 -threads 12 beast$count\_$fnameorig\n";
+	print PBS "\n";
+
+	close PBS;
+
+
+	#SUBMIT JOB
+	`mv $pbs_file $out_dir`;
+        `cp $fnameorig $out_dir/beast$count\_$fnameorig`;
+        chdir($out_dir);
+        #`/nfs/esnitkin/Zena/lib/change_prefixes_beast_xml.sh beast$count\_$fnameorig`;
+        #`mv beast$count\_$fname\_renamed.xml beast$count\_$fnameorig`;
+	`qsub $pbs_file`;
+        chdir($wd);
+	$count ++;
+
+}#end foreach
diff --git a/modules/beast/change_prefixes_beast_xml.sh b/modules/beast/change_prefixes_beast_xml.sh
new file mode 100755
index 0000000..837301d
--- /dev/null
+++ b/modules/beast/change_prefixes_beast_xml.sh
@@ -0,0 +1,24 @@
+#!/bin/bash
+
+## Changes prefixes in beast xml file
+## Specifically, adds prefixes to the sequence id name and discrete trait name based on xml file name (the prefix is the xml file name)
+## Takes as input: beast xml file
+## Usage: change_prefixes_beast.sh beast.xml 
+## Note: in example above, the prefix would be 'beast'
+
+ids=$(grep -A1 '<data' $1 | grep 'id=' | grep -o -P '(?<=").*(?=")')
+len_ids=$(echo $ids | wc -w)
+seqs=$(echo $ids | cut -d' ' -f1)
+if [ $len_ids == 2 ]; then 
+  discrete=$(echo $ids | cut -d' ' -f2)
+fi
+
+prefix=$(echo $1 | grep -o -P '.*(?=\.xml)')
+
+sed "s/${seqs}/${prefix}_${seqs}/g" $1 > ${prefix}_renamed.xml
+if [ $len_ids == 2 ]; then
+  sed -ibak "s/${discrete}/${prefix}_${discrete}/g" ${prefix}_renamed.xml
+  rm ${prefix}_renamed.xmlbak
+fi
+sed -ibak "s/EBSP/${prefix}_EBSP/g" ${prefix}_renamed.xml
+rm ${prefix}_renamed.xmlbak
diff --git a/modules/beast/countInvarSites.py b/modules/beast/countInvarSites.py
new file mode 100644
index 0000000..73a5930
--- /dev/null
+++ b/modules/beast/countInvarSites.py
@@ -0,0 +1,56 @@
+# Count invariant sites in alignment file
+
+# Import modules
+from subprocess import call
+from Bio import AlignIO
+from Bio import SeqIO
+from Bio.Seq import Seq
+from Bio.SeqRecord import SeqRecord
+import pandas as pd
+from collections import defaultdict
+import re
+import os
+
+# Set paths
+python = '/nfs/esnitkin/bin_group/anaconda3/bin/python'
+maskVarsPath = '/nfs/esnitkin/bin_group/pipeline/Github/variant_calling_pipeline_dev/modules/variant_diagnostics/mask_gubbins_variants.py'
+
+
+# Add gubbins filtered masks to full alignment.
+# Note: the full alignment should be the same one used as input to gubbins.
+# Input:
+#    (1) Whole genome alignment file in FASTA format
+#    (2) Gubbins GFF output file
+#    (3) 
+# Output:
+#    (1) Masked whole genome alignment file in FASTA format
+#    (2) Text file with list of masked positions in each genome
+#    (3) Masked variant-only alignment file in FASTA format
+def mask_positions(fasta, gff):
+
+
+
+# Count invariant sites in an alignment file (fasta format)
+# Input: 
+#    (1) Path to alignment file in fasta format
+#    (2) (optional) Path to [gubbins] GFF file to mask recombinant sites first
+#    (3)
+#    (4) (optional) Path to mask_gubbins_variants.py (default: '/nfs/esnitkin/bin_group/pipeline/Github/variant_calling_pipeline_dev/modules/variant_diagnostics/mask_gubbins_variants.py')    
+# Output: 
+#    (1) Text file (*_invar_site_counts.txt) with invariant site counts in the following order: A,C,G,T
+#    (2) If GFF path given, masked fasta file (*_gubbins_masked.fa)
+#    (3) Returns name of text file with invariant site counts (*_invar_site_counts.txt)
+def count_invar_sites(fasta,gff=None,mask_vars_path=mask_vars_path)
+    # Mask recombinant regions before counting invariant sites
+    if gff is not None:
+        call([python, mask_vars_path, fasta, gff])
+        aln_file = re.split('/|\.', fasta)[-2] + \
+                  '_gubbins_masked.fa'
+    else:
+        aln_file = fasta
+    # Count invariant sites in whole genome alignment
+    call([python, scripts_dir + '/get_num_invariant_sites_v2.py', aln_file])
+    invar_counts_file = re.split('/|\.', alnFile)[-2] + \
+                      '_invar_site_counts.txt'
+    return(invar_counts_file)
+   
diff --git a/modules/beast/fasta_functions.py b/modules/beast/fasta_functions.py
new file mode 100755
index 0000000..152fdd8
--- /dev/null
+++ b/modules/beast/fasta_functions.py
@@ -0,0 +1,246 @@
+# Functions to manipulate fasta files
+
+# Functions:
+#    subset_fasta
+#    mask_positions
+#    count_invar_sites
+
+# Import modules
+from subprocess import call
+from Bio import AlignIO
+from Bio import SeqIO
+from Bio.Seq import Seq
+from Bio.SeqRecord import SeqRecord
+import pandas as pd
+from collections import defaultdict
+from collections import Counter
+import re
+import os
+
+def subset_fasta(idnames, fastain, fastaout):
+    """Creates a new fasta file with a subset of original sequences.
+
+    Args:
+        idnames: Text file with list of names of sequences to be extracted.
+        fastain: Path to fasta file containing all sequences of interest.
+        fastaout: Name of output fasta file containing only the sequences of interest.
+
+    Output:
+        Fasta file containing only the sequences of interest.
+
+    Returns:
+        Path to subsetted fasta file.
+    """    
+
+    ids = []
+
+    for line in open(idnames, 'r'):
+        if line.strip() == 'x':
+            pass
+        else:
+            ids.append(line.strip())
+
+    with open(fastaout, 'w') as f:
+        for rec in SeqIO.parse(fastain, 'fasta'):
+            if str(rec.id) in ids:
+                f.write('>' + names[ids.index(rec.id)] + '\n')
+                f.write(str(rec.seq) + '\n')
+
+    return(fastaout)
+
+
+def rm_invar_sites(fasta, outfile=None, outfmt=['fasta','vcf'], outdir='.', 
+                   path={'snpsites':'/nfs/esnitkin/bin_group/anaconda3/bin/snp-sites'}):
+    """Removes invariant sites from a multifasta file using snp-sites.
+
+    Args:
+        fasta: Alignment fasta file from which to get variant sites.
+        outfile: (Optional) Output file name.
+        outfmt: Format of output file (fasta or vcf).
+        outdir: (Optional) Output directory (default: current working directory).
+        path: Dictionary of paths including the path to snp-sites (key: snpsites, value: path)
+
+    Output:
+        Fasta or VCF file of variant sites.
+
+    Returns:
+        Path to output file.
+    """
+
+   if len(outfmt) > 1:
+       outfmt = outfmt[0]
+
+    # Get output fasta file name
+    if outfile == None:
+        outfile = outdir + '/' + re.split('/|\.', fasta)[-2] + 'var_sites.' + outfmt
+
+    # Get output format
+    if outfmt == 'fasta':
+        flag = ' -m '
+    elif outfmt == 'vcf':
+        flag = ' -v '
+
+    # Get variant sites and write to fasta file using snp-sites
+    print('Getting variant sites using snp-sites.')
+    cmd = path['snpsites'] + ' ' + fasta + \
+          flag + ' -o ' + outfile
+
+    os.system(cmd)
+    print(outfile, 'written.')
+
+    return(outfile)
+
+
+def mask_positions(fasta, gff, outdir='.', masked_sites_file=False):
+    """Masks positions in GFF file in alignment file in fasta format.
+
+    If fasta is the whole genome alignment fasta used in gubbins 
+    and gff is the gubbins output GFF file, then recombinant 
+    regions identified by gubbins are masked (on a per-genome basis).
+    Optionally returns a text file with list of masked positions in each genome.
+
+    Args:
+        fasta: Alignment fasta file in which sites will be masked.
+        gff: GFF file containing sites that will be masked in certain genomes
+            (ex. gubbins output GFF).
+        outdir: Output file directory (default: current working directory).
+        masked_sites_file: If true, generates a text file with a list of masked positions in each genome.
+
+    Output:
+        Masked whole genome alignment file in FASTA format.
+        (Optional) Text file with list of masked positions in each genome.
+
+    Returns:
+        Path to masked fasta file.
+    """
+
+    # Read in alignment and gff file
+    print('Reading ', gff, '.', sep='')
+    gff = pd.read_csv(gff, sep='\t', skiprows=2, header=None)
+    print('Reading ', fasta, '.', sep='')
+    aln = AlignIO.read(fasta, 'fasta')
+
+    # Get indices/positions of recombinant regions identified by gubbins
+    print('Getting recombinant positions.')
+    recomb_regions = defaultdict(list)
+
+    for row in gff.iterrows():
+        start = row[1][3]
+        end = row[1][4]
+        region = list(range(start, end))
+        taxa = row[1][8].split(';')[2]
+        taxa = taxa.replace('taxa=\"', '')
+        taxa = taxa.replace('\"', '')
+        taxa = list(taxa.split())
+        for isolate in taxa:
+            for position in region:
+                recomb_regions[isolate].append(position)
+
+    # Mask indices/positions of recombinant regions identified by gubbins
+    print('Masking recombinant positions in whole genome alignment.')
+    sample_masked_indices = defaultdict(list)
+    new_aln = list()
+
+    for record in aln:
+        seq_str = list(str(record.seq))
+        masked_indices = recomb_regions.get(record.id, [])
+        for index in masked_indices:
+            seq_str[index] = 'N'
+        seq_str = ''.join(seq_str)
+        new_record = SeqRecord(Seq(seq_str), id=record.id, description='')
+        sample_masked_indices[record.id] = masked_indices
+        new_aln.append(new_record)
+
+    # Write new FASTA file with recombinant regions masked
+    fasta_outfile = outdir + '/' + re.split('/|\.', fasta)[-2] + \
+                    '_gubbins_masked.fa'
+
+    print('Writing', fasta_outfile)
+    with open(fasta_outfile, 'w') as handle:
+        SeqIO.write(new_aln, handle, 'fasta')
+
+    if masked_sites_file:
+        # Write text file with list of recombinant sites for each genome
+        text_outfile = outdir + '/' + re.split('/|\.', fasta)[-2] + \
+                       '_masked_recomb_positions.txt'
+        print('Writing', text_outfile)
+        with open(text_outfile, 'w') as handle:
+            for sample, positions in sample_masked_indices.items():
+                line = str(sample) + '\t' + ','.join(map(str, positions)) + '\n'
+                handle.write(line)
+
+    return(fasta_outfile)
+
+def count_invar_sites(fasta,gff=None,outdir='.',path={'snpsites':'/nfs/esnitkin/bin_group/anaconda3/bin/snp-sites'}):
+    """Counts invariant sites in an alignment file (fasta format).
+    
+    Gets invariant site count for As, Cs, Gs, and Ts from an alignment file. 
+    If gff is not None, positions in the GFF file will be masked before 
+    invariant sites are counted.
+
+    Args:
+        fasta: Path to alignment file in fasta format.
+        gff: [Optional] GFF file of sections of genomes to mask (ex. gubbins output GFF). 
+        outdir: Output file directory (default: current working directory).
+        path: Dictionary of paths including the path to snp-sites (key: snpsites, value: path)
+
+    Output:
+        Text file (*_invar_site_counts.txt) with invariant site counts in the following order: A,C,G,T.
+        VCF file of variants (created by snp-sites)
+        If GFF path given, masked fasta file (*_gubbins_masked.fa).
+    
+    Returns:
+        Name of text file with invariant site counts (*_invar_site_counts.txt).
+
+    """
+
+    # Mask recombinant regions before counting invariant sites
+    if gff is not None:
+        aln_file = mask_positions(fasta, gff)
+    else:
+        aln_file = fasta
+
+    # Count invariant sites in whole genome alignment
+
+    # Read in alignment
+    print('Reading ', aln_file, '.', sep='')
+    aln = AlignIO.read(aln_file, 'fasta')
+
+    # Get variant positions
+    var_site_outfile = outdir + '/' + re.split('/|\.', aln_file)[-2] + \
+                       '_snp-sites.vcf'
+    print('Getting variant positions using snp-sites.')
+    cmd = path['snpsites'] + ' ' + aln_file + \
+      ' -v ' + ' -o ' + var_site_outfile
+
+    os.system(cmd)
+
+    positions = []
+    with open(var_site_outfile) as f:
+        for line in f:
+            li=line.strip()
+            if not li.startswith("#"):
+                positions.append(line.split('\t')[1])
+
+    # Get ref allele for invariant sites
+    for record in aln:
+        seq_str = list(str(record.seq))
+        for index in positions:
+            index = int(index)
+            seq_str[index] = ''
+        invar_sites = ''.join(seq_str)
+        break
+
+    # Get invariant site count for each base
+    print('Counting bases.')
+    invar_counts = Counter(invar_sites)
+
+    # Write base counts to files
+    invar_counts_file = outdir + '/' + re.split('/|\.', aln_file)[-2] + \
+                          '_invar_site_counts.txt'
+    print('Writing ', invar_counts_file, ' (order: A C G T).', sep='')
+    with open(invar_counts_file, 'w') as f:
+        for base, count in sorted(invar_counts.items()):
+            f.write('%s ' % (count))
+
+    return(invar_counts_file)
diff --git a/modules/beast/fasta_functions.pyc b/modules/beast/fasta_functions.pyc
new file mode 100644
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diff --git a/modules/beast/generate_input_file_beast_pbs.sh b/modules/beast/generate_input_file_beast_pbs.sh
new file mode 100755
index 0000000..f39e241
--- /dev/null
+++ b/modules/beast/generate_input_file_beast_pbs.sh
@@ -0,0 +1,12 @@
+#!/bin/bash
+
+# creates file with names of certain files in directory based on what would be listed with ls
+# ex: generate_input_file_beast_pbs.sh '*.xml' 3 
+# In the example above, an input_beast.txt file would be generated with all of the xml files in the directory listed 3 times. This will cause BEAST to run in triplicate for each xml file.
+# if using wildcard, put it in quotes
+
+num=$2
+
+export num;
+
+ls $1 | perl -ne 'print $_ x $ENV{num}' > input_beast.txt
diff --git a/modules/beast/get_num_invariant_sites_v2.py b/modules/beast/get_num_invariant_sites_v2.py
new file mode 100755
index 0000000..6628f78
--- /dev/null
+++ b/modules/beast/get_num_invariant_sites_v2.py
@@ -0,0 +1,89 @@
+# Get number of invariant A's, C's, G's, and T's from a whole-genome alignment.
+# These numbers can be used in BEAST analyses.
+# V2: uses snp-sites to get VCF to find variant positions instead of SNP matrix.
+# Input:
+#   (1) Whole genome alignment file in FASTA format
+#       (Note: This should be the one used to create the variant position
+#       FASTA file used in BEAST.)
+# Output:
+#   (1) VCF file of variants (created by snp-sites)
+#   (2) Text file with number of invariant A's, C's, G's, and T's in alignment (order: A C G T)
+
+# import libraries
+import argparse
+import os
+import re
+from Bio import AlignIO
+# from Bio.SeqRecord import SeqRecord
+# from Bio.Seq import Seq
+# import os
+# from Bio import SeqIO
+from collections import Counter
+import pandas as pd
+
+# parse command line arguments (input files)
+parser = argparse.ArgumentParser(
+                description='''Get number of invariant A's, C's, G's, and T's
+                    from a whole-genome alignment.
+                    Input:
+                      (1) Whole genome alignment file in FASTA format
+                          (The one used to create the variant position
+                          FASTA file used in BEAST, or the recombination-masked version..)
+                    Output:
+		      (1) VCF file of variants (created by snp-sites)
+                      (2) Text file with number of invariant
+                          A's, C's, G's, and T's in alignment (order: A C G T)
+                    ''')
+parser.add_argument('fasta', metavar='FASTA', type=str,
+                    help='whole genome alignment file in FASTA format')
+parser.add_argument('-o', '--outdir', metavar='OUTDIR', type=str,
+                    default='.',
+                    help='''output directory
+                    (default: .)''')
+args = parser.parse_args()
+
+aln_path = args.fasta
+outdir = args.outdir
+
+# read in alignment to be able to get invariant base counts
+print('Reading ', aln_path, '.', sep='')
+aln = AlignIO.read(aln_path, 'fasta')
+
+# get variant positions
+var_site_outfile = outdir + '/' + re.split('/|\.', aln_path)[-2] + \
+                '_snp-sites.vcf'
+print('Getting variant positions using snp-sites.')
+cmd = '/nfs/esnitkin/bin_group/anaconda3/bin/snp-sites ' + aln_path + \
+      ' -v ' + ' -o ' + var_site_outfile
+
+os.system(cmd)
+
+positions = []
+with open(var_site_outfile) as f:
+    for line in f:
+        li=line.strip()
+        if not li.startswith("#"):
+            positions.append(line.split('\t')[1])
+
+# get ref allele for invariant sites
+for record in aln:
+    seq_str = list(str(record.seq))
+    for index in positions:
+        index = int(index)
+        seq_str[index] = ''
+    invar_sites = ''.join(seq_str)
+    break
+
+# get invariant site count for each base
+print('Counting bases.')
+invar_counts = Counter(invar_sites)
+
+# write base counts to files
+invar_base_counts_file = outdir + '/' + re.split('/|\.', aln_path)[-2] + \
+                '_invar_site_counts.txt'
+print('Writing ', invar_base_counts_file, ' (order: A C G T).', sep='')
+with open(invar_base_counts_file, 'w') as f:
+    for base, count in sorted(invar_counts.items()):
+        f.write('%s ' % (count))
+
+print('Done.')
diff --git a/modules/beast/insert_starting_tree_beast.sh b/modules/beast/insert_starting_tree_beast.sh
new file mode 100755
index 0000000..38b6211
--- /dev/null
+++ b/modules/beast/insert_starting_tree_beast.sh
@@ -0,0 +1,17 @@
+#!/bin/bash
+
+# Add starting tree to BEAST xml file (instead of starting with a random tree)
+# Arguments: 1) xml file
+#	     2) tree file
+
+tree=$(less $2)
+
+for i in $(ls $1); do
+
+outfile=$(echo $i | cut -d. -f1)
+outfile=${outfile}_st.xml
+echo $outfile
+
+sed -e 's/id="RandomTree/id="NewickTree/g' -e "s/evolution.tree.RandomTree\" estimate=\"false\"/util.TreeParser\" IsLabelledNewick=\"true\" offset=\"0\" newick=\""$tree"\"/g" -e '/<populationModel id="ConstantPopulation/,/populationModel>/d' $i > $outfile
+
+done
diff --git a/modules/beast/scotti.py b/modules/beast/scotti.py
new file mode 100644
index 0000000..da7ad56
--- /dev/null
+++ b/modules/beast/scotti.py
@@ -0,0 +1,31 @@
+# PIPELINE TO RUN SCOTTI ON FLUX
+
+# Import modules
+import sys
+import os
+import argparse
+from subprocess import call
+import re
+
+# Get command line arguments
+parser = argparse.ArgumentParser(description='Generate SCOTTI XMLs and run SCOTTI.')
+parser.add_argument('xmls', nargs='*', help='input SCOTTI BEAST xml file(s)')
+parser.add_argument('--nReps', '-n', metavar='N', type=int, help='number of beast runs for each xml', default=3)
+parser.add_argument('--invarSites', '-i', metavar='FILE', help='''
+                    option 1: fasta file to  get number of invariant As, Cs, Gs, and Ts not in alignment
+                    option 2: text file with number of invariant As, Cs, Gs, and Ts in alignment''')
+parser.add_argument('--gubbinsGFF', '-g', metavar='GFF', help='''gubbins output GFF file to mask recombinant sites in alignment before counting invariant sites''')
+parser.add_argument('--tree', '-t', help='starting tree file in newick format')
+parser.add_argument('-scriptsDir', '-d', metavar='DIR', help='directory where all of the scripts are housed', default='/nfs/esnitkin/bin_group/pipeline/Github/variant_calling_pipeline_dev/modules/beast')
+args = parser.parse_args()
+# Rename variables
+xmls = args.xmls
+nReps = args.nReps
+invarSites = args.invarSites
+gubbinsGFF = args.gubbinsGFF
+tree = args.tree
+scriptsDir = args.scriptsDir
+
+# Set paths
+python = '/nfs/esnitkin/bin_group/anaconda3/bin/python'
+maskVarsPath = '/nfs/esnitkin/bin_group/pipeline/Github/variant_calling_pipeline_dev/modules/variant_diagnostics/mask_gubbins_variants.py'
diff --git a/modules/phage_detection.py b/modules/phage_detection.py
index cbf5b6b..7a3e7e9 100644
--- a/modules/phage_detection.py
+++ b/modules/phage_detection.py
@@ -19,7 +19,6 @@ def run_phaster(reference_genome, outdir, logger, Config):
         keep_logging("Phaster Post Json file %s/%s_phaster_post.json already exists. Skipping Phaster Job submission. To get latest Phaster results remove this file and run core_prep step again." % (outdir, str(out_name[0])), "Phaster Post Json: %s/%s_phaster_post.json exists. Skipping Phaster Job submission. To get latest Phaster results remove this file and run core_prep step again." % (outdir, str(out_name[0])), logger,
                      'info')
 
-
 def parse_phaster(reference_genome, outdir, logger, Config):
     out_name = (os.path.basename(reference_genome)).split('.')
     if os.path.isfile("%s/%s_phaster_post.json" % (outdir, str(out_name[0]))) and os.stat("%s/%s_phaster_post.json" % (outdir, str(out_name[0]))).st_size != 0:
@@ -83,6 +82,7 @@ def parse_phaster(reference_genome, outdir, logger, Config):
                 # keep_logging('Running: %s' % phaster_unzip_cmd, 'Running: %s' % phaster_get_cmd, logger, 'debug')
                 # call(phaster_get_zip_cmd, logger)
                 # call(phaster_unzip_cmd, logger)
+
     if os.path.isfile("%s/summary.txt" % outdir):
         keep_logging('Extracting Phage region information from %s/summary.txt' % outdir, 'Extracting Phage region information from %s/summary.txt' % outdir, logger, 'info')
         get_phage_regions = "sed -n -e '/REGION/,$p' %s/summary.txt | awk 'NR>2' | awk -F' ' '{print $5}'" % outdir
@@ -100,8 +100,6 @@ def parse_phaster(reference_genome, outdir, logger, Config):
         for pos in phage_positions:
             f_open.write(str(pos) + "\n")
 
-
-
     if os.path.isfile("%s/summary.txt" % os.path.dirname(reference_genome)):
         keep_logging('Extracting Phage region information from %s/summary.txt' % os.path.dirname(reference_genome), 'Extracting Phage region information from %s/summary.txt' % os.path.dirname(reference_genome), logger, 'info')
         get_phage_regions = "sed -n -e '/REGION/,$p' %s/summary.txt | awk 'NR>2' | awk -F' ' '{print $5}'" % os.path.dirname(reference_genome)
@@ -119,7 +117,6 @@ def parse_phaster(reference_genome, outdir, logger, Config):
         for pos in phage_positions:
             f_open.write(str(pos) + "\n")
 
-
     if not os.path.isfile("%s/phage_region_positions.txt" % outdir):
         keep_logging('Phaster output file %s/summary.txt not found. Phaster job is still running or Phaster get json results were empty.' % outdir,
                      'Phaster output file %s/summary.txt not found. Phaster job is still running or Phaster get json results were empty.' % outdir, logger, 'exception')
diff --git a/modules/phage_detection.pyc b/modules/phage_detection.pyc
index 444b334bcd263258bd2a4a1f34167296bec95b3b..a7712be648aecc798e2fce533fd4928dac8c404e 100644
GIT binary patch
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Wax6-W#*AXv<(N007ZGP<<O2Y*sSD)*

diff --git a/modules/variant_diagnostics/core_pipeline.py b/modules/variant_diagnostics/core_pipeline.py
index f4b3fea..5356be7 100644
--- a/modules/variant_diagnostics/core_pipeline.py
+++ b/modules/variant_diagnostics/core_pipeline.py
@@ -2112,11 +2112,9 @@ def annotated_snp_matrix():
         files_gatk = files_gatk + " --variant " + i
     final_gatk_snp_merged_vcf = gatk_combine_variants(files_gatk.replace('_filter2_final.vcf_no_proximate_snp.vcf', '_filter2_final.vcf_no_proximate_snp.vcf_ANN.vcf.gz'), args.reference, args.filter2_only_snp_vcf_dir, merged_file_suffix, logger, Config)
 
-    # Test this merge and annote this merged file
-    merged_file_suffix = "_no_proximate_snp_1.vcf"
-    final_gatk_snp_merged_vcf_1 = gatk_combine_variants(files_gatk,
-                                                      args.reference, args.filter2_only_snp_vcf_dir, merged_file_suffix,
-                                                      logger, Config)
+    # Test this merge and annotate this merged file - Testing Mode Right now.
+    #merged_file_suffix = "_no_proximate_snp_1.vcf"
+    #final_gatk_snp_merged_vcf_1 = gatk_combine_variants(files_gatk,args.reference, args.filter2_only_snp_vcf_dir, merged_file_suffix, logger, Config)
     merged_file_suffix = "_indel.vcf"
     final_gatk_indel_merged_vcf = gatk_combine_variants(files_gatk.replace('_filter2_final.vcf_no_proximate_snp.vcf',
                                                                          '_filter2_indel_final.vcf_ANN.vcf.gz'),
@@ -2914,20 +2912,21 @@ def someOtherFunc(data, key):
         files_for_tabix = glob.glob("%s/*.vcf" % args.filter2_only_snp_vcf_dir)
         tabix(files_for_tabix, "vcf", logger, Config)
 
+        # Get the cluster option; create and run jobs based on given parameter. The jobs will parse all the intermediate vcf file to extract information such as if any unique variant position was unmapped in a sample, if it was filtered out dur to DP,MQ, FQ, proximity to indel, proximity to other SNPs and other variant filter parameters set in config file.
+        tmp_dir = "/tmp/temp_%s/" % log_unique_time
+        create_job(args.jobrun, vcf_filenames, unique_position_file, tmp_dir)
+        create_indel_job(args.jobrun, vcf_filenames, unique_indel_position_file, tmp_dir)
+
         # If Phaster Summary file doesn't exist in reference genome folder
         if not os.path.isfile("%s/summary.txt" % os.path.dirname(args.reference)):
             if ConfigSectionMap("functional_filters", Config)['apply_functional_filters'] == "yes":
-                keep_logging('Functional class filter is set to yes. Preparing Functional class filters\n', 'Functional class filter is set to yes. Preparing Functional class filters\n', logger,
+                keep_logging('Functional class filter is set to yes. Preparing Functional class filters\n',
+                             'Functional class filter is set to yes. Preparing Functional class filters\n', logger,
                              'info')
                 if ConfigSectionMap("functional_filters", Config)['find_phage_region'] == "yes":
                     # Submit Phaster jobs to find ProPhage region in reference genome.
                     run_phaster(args.reference, args.filter2_only_snp_vcf_dir, logger, Config)
 
-        # Get the cluster option; create and run jobs based on given parameter. The jobs will parse all the intermediate vcf file to extract information such as if any unique variant position was unmapped in a sample, if it was filtered out dur to DP,MQ, FQ, proximity to indel, proximity to other SNPs and other variant filter parameters set in config file.
-        tmp_dir = "/tmp/temp_%s/" % log_unique_time
-        create_job(args.jobrun, vcf_filenames, unique_position_file, tmp_dir)
-        create_indel_job(args.jobrun, vcf_filenames, unique_indel_position_file, tmp_dir)
-
         call("cp %s %s/Logs/core_prep/" % (log_file_handle, os.path.dirname(os.path.dirname(args.filter2_only_snp_vcf_dir))), logger)
 
     if "2" in args.steps:
@@ -3253,9 +3252,9 @@ def someOtherFunc(data, key):
         # # Read new allele matrix and generate fasta; generate a seperate function
         keep_logging('Generating Fasta from Variant Alleles...\n', 'Generating Fasta from Variant Alleles...\n', logger, 'info')
 
-        create_job_allele_variant_fasta(args.jobrun, vcf_filenames, args.filter2_only_snp_vcf_dir, config_file)
+        #create_job_allele_variant_fasta(args.jobrun, vcf_filenames, args.filter2_only_snp_vcf_dir, config_file)
 
-        extract_only_ref_variant_fasta_from_reference_allele_variant()
+        #extract_only_ref_variant_fasta_from_reference_allele_variant()
 
         call("cp %s %s/Logs/core/" % (
             log_file_handle, os.path.dirname(os.path.dirname(args.filter2_only_snp_vcf_dir))), logger)
diff --git a/modules/variant_diagnostics/mask_gubbins_variants.py b/modules/variant_diagnostics/mask_gubbins_variants.py
index 6c246ef..343327e 100644
--- a/modules/variant_diagnostics/mask_gubbins_variants.py
+++ b/modules/variant_diagnostics/mask_gubbins_variants.py
@@ -26,19 +26,17 @@
                     (1) Masked whole genome alignment file in FASTA format
                     (2) Text file with list of masked positions in each genome
                     ''')
-parser.add_argument('-a', '--alignment', metavar='FASTA', type=str,
-                    required=True,
+parser.add_argument('fasta', metavar='FASTA', type=str,
                     help='whole genome alignment file in FASTA format')
-parser.add_argument('-g', '--gff', metavar='GFF', type=str,
-                    required=True,
+parser.add_argument('gff', metavar='GFF', type=str,
                     help='gubbins GFF output file')
-parser.add_argument('-o', '--outdir', metavar='OUTFILE', type=str,
+parser.add_argument('-o', '--outdir', metavar='OUTDIR', type=str,
                     default='.',
                     help='''output fasta file directory
                     (default: .)''')
 args = parser.parse_args()
 
-aln_path = args.alignment
+aln_path = args.fasta
 gubbins_gff_path = args.gff
 outdir = args.outdir
 
diff --git a/variant_call.py b/variant_call.py
index cbcb23d..7fe181e 100644
--- a/variant_call.py
+++ b/variant_call.py
@@ -385,6 +385,7 @@ def run_core_prep_analysis(core_temp_dir, reference, analysis_name, log_unique_t
     #keep_logging('You can check the job status with: qstat -u USERNAME', 'You can check the job status with: qstat -u USERNAME', logger, 'info')
 
     return core_prep_pipeline
+
 def run_core_analysis(core_temp_dir, reference, analysis_name, log_unique_time, cluster, logger, core_results_dir, config_file):
     file_exists(reference)
     if args.debug_mode == "yes":
@@ -543,6 +544,7 @@ def run_tree_analysis(core_temp_dir, reference, analysis_name, log_unique_time,
         print qid.split('.')[0]
     #keep_logging('You can check the job status with: qstat -u USERNAME', 'You can check the job status with: qstat -u USERNAME', logger, 'info')
     return core_pipeline
+
 """ Start of Main Method/Pipeline """
 if __name__ == '__main__':
 
@@ -580,7 +582,7 @@ def run_tree_analysis(core_temp_dir, reference, analysis_name, log_unique_time,
     Config.read(config_file)
 
     # Run pipeline steps
-    if "core_All" not in args.steps and "core" not in args.steps and "core_prep" not in args.steps and "report" not in args.steps and "tree" not in args.steps:
+    if "core_All" not in args.steps and "core" not in args.steps and "core_prep" not in args.steps and "report" not in args.steps and "tree" not in args.steps and "2" not in args.steps:
         """ Set Up variant calling logs folder/logger object, cluster mode and copy config files to it"""
         vc_logs_folder = logs_folder + "/variant_calling"
         make_sure_path_exists(vc_logs_folder)
@@ -602,7 +604,7 @@ def run_tree_analysis(core_temp_dir, reference, analysis_name, log_unique_time,
         keep_logging('Total Time taken: {}'.format(time_taken), 'Total Time taken: {}'.format(time_taken), logger, 'info')
         keep_logging('End: Variant calling Pipeline', 'End: Variant calling Pipeline', logger, 'info')
 
-    elif "core_All" in args.steps:
+    elif "core_All" in args.steps or "2" in args.steps:
         core_All_cmds = []
         """ Set Up Core Prep logs folder/logger object, cluster mode and copy config files to it"""
         core_prep_logs_folder = logs_folder + "/core_prep"
@@ -736,9 +738,20 @@ def run_tree_analysis(core_temp_dir, reference, analysis_name, log_unique_time,
         reference = ConfigSectionMap(args.index, Config)['ref_path'] + "/" + ConfigSectionMap(args.index, Config)[
             'ref_name']
 
+        """ If Phaster Summary file doesn't exist in reference genome folder """
+        if not os.path.isfile("%s/summary.txt" % os.path.dirname(reference)):
+            if ConfigSectionMap("functional_filters", Config)['apply_functional_filters'] == "yes":
+                keep_logging('Preparing Functional class filters\n', 'Preparing Functional class filters\n', logger,
+                             'info')
+                if ConfigSectionMap("functional_filters", Config)['find_phage_region'] == "yes":
+                    # Submit Phaster jobs to find ProPhage region in reference genome.
+                    run_phaster(reference, os.path.dirname(reference), logger, Config)
+
+
+
         # Parse Phaster results file to extract phage region.
         if ConfigSectionMap("functional_filters", Config)['apply_functional_filters'] == "yes":
-            keep_logging('Preparing Functional class filters\n', 'Preparing Functional class filters\n', logger,
+            keep_logging('Parsing Functional class filters\n', 'Parsing Functional class filters\n', logger,
                          'info')
             functional_class_filter_positions = "%s/Functional_class_filter_positions.txt" % core_temp_dir
             f1 = open(functional_class_filter_positions, 'w+')
diff --git a/variant_calling_pipeline_dev/other b/variant_calling_pipeline_dev/other
deleted file mode 160000
index 94bdeca..0000000
--- a/variant_calling_pipeline_dev/other
+++ /dev/null
@@ -1 +0,0 @@
-Subproject commit 94bdecadd29c5e18779717f69dbda8fe3f00f9da