diff --git a/unravel/cluster_stats/cluster_summary.py b/unravel/cluster_stats/cluster_summary.py index 9bc212a3..a01e19ee 100755 --- a/unravel/cluster_stats/cluster_summary.py +++ b/unravel/cluster_stats/cluster_summary.py @@ -5,11 +5,19 @@ Usage if running directly after ``cluster_validation``: ------------------------------------------------------- - cluster_summary -c -e -cvd '*' -vd -sk --groups -v + cluster_summary -c -e -cvd 'psilocybin_v_saline_tstat1_q' -vd -sk --groups -hg -v + +Note: + - The current working directory should not have other directories when running this script for the first time. Directories from cluster_org_data are ok though. Usage if running after ``cluster_validation`` and ``cluster_org_data``: ----------------------------------------------------------------------- - cluster_summary -c -sk --groups -v + cluster_summary -c -sk --groups -hg -v + +Note: + - For the second usage, the ``-e``, ``-cvd``, and ``-vd`` arguments are not needed because the data is already in the working directory. + - Only process one comparison at a time. If you have multiple comparisons, run this script separately for each comparison in separate directories. + - Then aggregate the results as needed (e.g. to make a legend with all relevant abbeviations, copy the .xlsx files to a central location and run ``cluster_legend``). The current working directory should not have other directories when running this script for the first time. Directories from cluster_org_data are ok though. @@ -28,6 +36,9 @@ dir_name,condition sample01,control sample02,treatment + +If you need to rerun this script, delete the following directories and files in the current working directory: +find . -name _valid_clusters -exec rm -rf {} \; -o -name cluster_validation_summary_t-test.csv -exec rm -f {} \; -o -name cluster_validation_summary_tukey.csv -exec rm -f {} \; -o -name 3D_brains -exec rm -rf {} \; -o -name valid_clusters_tables_and_legend -exec rm -rf {} \; -o -name _valid_clusters_stats -exec rm -rf {} \; """ import argparse @@ -59,6 +70,7 @@ def parse_args(): # cluster_stats --groups parser.add_argument('--groups', help='List of group prefixes. 2 groups --> t-test. >2 --> Tukey\'s tests (The first 2 groups reflect the main comparison for validation rates; for cluster_stats)', nargs='+') parser.add_argument('-cp', '--condition_prefixes', help='Condition prefixes to group related data (optional for cluster_stats)', nargs='*', default=None, action=SM) + parser.add_argument('-hg', '--higher_group', help='Specify the group that is expected to have a higher mean based on the direction of the p value map', required=True) parser.add_argument('-v', '--verbose', help='Increase verbosity. Default: False', action='store_true', default=False) parser.epilog = __doc__ @@ -67,6 +79,7 @@ def parse_args(): # TODO: Could add a progress bar that advances after each subdir, but need to adapt running of the first few scripts for this. Include check for completeness (all samples have csvs [from both hemis]). Review outputs and output folders and consider consolidating them. Could make cells vs. labels are arg. Could add a raw data output organized for the SI table. # The valid cluster sunburst could have the val dir name and be copied to a central location # TODO: Consider moving find_and_copy_files() to unravel/unravel/utils.py # TODO: Move cell vs. label arg from config back to argparse and make it a required arg to prevent accidentally using the wrong metric +# TODO: Add a reset option to delete all output files and directories from the current working directory def run_script(script_name, script_args): """Run a command/script using subprocess that respects the system's PATH and captures output.""" @@ -116,7 +129,8 @@ def main(): stats_args = [ '--groups', *args.groups, '-alt', cfg.stats.alternate, - '-pvt', cfg.org_data.p_val_txt + '-pvt', cfg.org_data.p_val_txt, + '-hg', args.higher_group ] if args.condition_prefixes: stats_args.append(['-cp', *args.condition_prefixes]) diff --git a/unravel/cluster_stats/stats.py b/unravel/cluster_stats/stats.py index 4b359a1a..9f54476e 100755 --- a/unravel/cluster_stats/stats.py +++ b/unravel/cluster_stats/stats.py @@ -5,14 +5,18 @@ T-test usage: ------------- - cluster_stats --groups + cluster_stats --groups -hg Tukey's test usage: ------------------- - cluster_stats --groups ... + cluster_stats --groups ... -hg -Input subdirs: - +Note: + - Organize data in directories for each comparison (e.g., psilocybin > saline, etc.) + - This script will loop through all directories in the current working dir and process the data in each subdir. + - Each subdir should contain .csv files with the density data for each cluster. + - The first 2 groups reflect the main comparison for validation rates. + - Clusters are not considered valid if the effect direction does not match the expected direction. Input files: _density_data.csv from ``cluster_validation`` (e.g., in each subdir named after the rev_cluster_index.nii.gz file) @@ -64,12 +68,14 @@ def parse_args(): parser = argparse.ArgumentParser(formatter_class=SuppressMetavar) parser.add_argument('--groups', help='List of group prefixes. 2 groups --> t-test. >2 --> Tukey\'s tests (The first 2 groups reflect the main comparison for validation rates)', nargs='+', required=True) parser.add_argument('-cp', '--condition_prefixes', help='Condition prefixes to group data (e.g., see info for examples)', nargs='*', default=None, action=SM) + parser.add_argument('-hg', '--higher_group', help='Specify the group that is expected to have a higher mean based on the direction of the p value map', required=True) parser.add_argument('-alt', "--alternate", help="Number of tails and direction ('two-sided' [default], 'less' [group1 < group2], or 'greater')", default='two-sided', action=SM) parser.add_argument('-pvt', '--p_val_txt', help='Name of the file w/ the corrected p value thresh (e.g., from cluster_fdr). Default: p_value_threshold.txt', default='p_value_threshold.txt', action=SM) parser.add_argument('-v', '--verbose', help='Increase verbosity. Default: False', action='store_true', default=False) parser.epilog = __doc__ return parser.parse_args() + # TODO: Test grouping of conditions. Test w/ label densities data. Could set up dunnett's tests and/or holm sidak tests. @@ -265,8 +271,18 @@ def main(): args = parse_args() current_dir = Path.cwd() + # Check for subdirectories in the current working directory + subdirs = [d for d in current_dir.iterdir() if d.is_dir()] + if not subdirs: + print(f" [red1]No directories found in the current working directory: {current_dir}") + return + if subdirs[0].name == '_valid_clusters_stats': + print(f" [red1]Only the '_valid_clusters_stats' directory found in the current working directory: {current_dir}") + print(" [red1]The script was likely run from a subdirectory instead of a directory containing subdirectories.") + return + # Iterate over all subdirectories in the current working directory - for subdir in [d for d in current_dir.iterdir() if d.is_dir()]: + for subdir in subdirs: print(f"\nProcessing directory: [default bold]{subdir.name}[/]") # Load all .csv files in the current subdirectory @@ -300,7 +316,7 @@ def main(): # Aggregate the data from all .csv files and pool the data if hemispheres are present data_df = cluster_validation_data_df(density_col, has_hemisphere, csv_files, args.groups, data_col, data_col_pooled, args.condition_prefixes) if data_df.empty: - print("No data files match the specified groups. The prefixes of the csv files must match the group names.") + print(" [red1]No data files match the specified groups. The prefixes of the csv files must match the group names.") continue # Check the number of groups and perform the appropriate statistical test @@ -319,24 +335,36 @@ def main(): print(f"Running [gold1 bold]Tukey's tests") stats_df = perform_tukey_test(data_df, args.groups, density_col) - # Save the results to a .csv file - stats_results_csv = output_dir / 't-test_results.csv' if len(args.groups) == 2 else output_dir / 'tukey_results.csv' - stats_df.to_csv(stats_results_csv, index=False) + # Validate the clusters based on the expected direction of the effect + if args.higher_group not in args.groups: + print(f" [red1]Error: The specified higher group '{args.higher_group}' is not one of the groups.") + return + expected_direction = '>' if args.higher_group == args.groups[0] else '<' + incongruent_clusters = stats_df[(stats_df['higher_mean_group'] != args.higher_group) & (stats_df['significance'] != 'n.s.')]['cluster_ID'].tolist() - # Get the overall mean density for each condition and determine the effect direction - group_one_mean = data_df[data_df['condition'] == args.groups[0]][density_col].mean() - group_two_mean = data_df[data_df['condition'] == args.groups[1]][density_col].mean() - if group_one_mean > group_two_mean: - effect_direction = '>' - elif group_one_mean < group_two_mean: - effect_direction = '<' - elif group_one_mean == group_two_mean: - effect_direction = '==' + with open(output_dir / 'incongruent_clusters.txt', 'w') as f: + f.write('\n'.join(map(str, incongruent_clusters))) + + print(f"Expected effect direction: [green bold]{args.groups[0]} {expected_direction} {args.groups[1]}") - if len(args.groups) == 2: - print(f"Effect direction: [green bold]{args.groups[0]} {effect_direction} {args.groups[1]}") + if not incongruent_clusters: + print("All significant clusters are congruent with the expected direction") else: - print(f"Effect direction of interest: [green bold]{args.groups[0]} {effect_direction} {args.groups[1]}") + print(f"{len(incongruent_clusters)} of {total_clusters} clusters are incongruent with the expected direction.") + print (f"Although they had a significant difference, they not considered valid.") + print (f"'incongruent_clusters.txt' lists cluster IDs for incongruent clusters.") + + # Invalidate clusters that are incongruent with the expected direction + stats_df['significance'] = stats_df.apply(lambda row: 'n.s.' if row['cluster_ID'] in incongruent_clusters else row['significance'], axis=1) + + # Remove invalidated clusters from the list of significant clusters + significant_clusters = stats_df[stats_df['significance'] != 'n.s.']['cluster_ID'] + significant_cluster_ids = significant_clusters.unique().tolist() + significant_cluster_ids_str = ' '.join(map(str, significant_cluster_ids)) + + # Save the results to a .csv file + stats_results_csv = output_dir / 't-test_results.csv' if len(args.groups) == 2 else output_dir / 'tukey_results.csv' + stats_df.to_csv(stats_results_csv, index=False) # Extract the FDR q value from the first csv file (float after 'FDR' or 'q' in the file name) first_csv_name = csv_files[0] @@ -347,7 +375,7 @@ def main(): p_val_txt = next(Path(subdir).glob('**/*' + args.p_val_txt), None) if p_val_txt is None: # If no file is found, print an error message and skip further processing for this directory - print(f"No p-value file found matching '{args.p_val_txt}' in directory {subdir}. Please check the file name and path.") + print(f" [red1]No p-value file found matching '{args.p_val_txt}' in directory {subdir}. Please check the file name and path.") import sys ; sys.exit() with open(p_val_txt, 'r') as f: p_value_thresh = float(f.read()) @@ -358,10 +386,7 @@ def main(): # Print validation info: print(f"FDR q: [cyan bold]{fdr_q}[/] == p-value threshold: [cyan bold]{p_value_thresh}") - significant_clusters = stats_df[stats_df['p-value'] < 0.05]['cluster_ID'] - significant_cluster_ids = significant_clusters.unique().tolist() - significant_cluster_ids_str = ' '.join(map(str, significant_cluster_ids)) - print(f"Valid cluster IDs: [blue bold]{significant_cluster_ids_str}") + print(f"Valid cluster IDs: {significant_cluster_ids_str}") print(f"[default]# of valid / total #: [bright_magenta]{len(significant_cluster_ids)} / {total_clusters}") validation_rate = len(significant_cluster_ids) / total_clusters * 100 print(f"Cluster validation rate: [purple bold]{validation_rate:.2f}%") @@ -376,7 +401,7 @@ def main(): # Save the # of sig. clusters, total clusters, and cluster validation rate to a .txt file validation_inf_txt = output_dir / 'cluster_validation_info_t-test.txt' if len(args.groups) == 2 else output_dir / 'cluster_validation_info_tukey.txt' with open(validation_inf_txt, 'w') as f: - f.write(f"Direction: {args.groups[0]} {effect_direction} {args.groups[1]}\n") + f.write(f"Direction: {args.groups[0]} {expected_direction} {args.groups[1]}\n") f.write(f"FDR q: {fdr_q} == p-value threshold {p_value_thresh}\n") f.write(f"Valid cluster IDs: {significant_cluster_ids_str}\n") f.write(f"# of valid / total #: {len(significant_cluster_ids)} / {total_clusters}\n") @@ -389,7 +414,7 @@ def main(): # Save cluster validation info for ``cluster_summary`` data_df = pd.DataFrame({ - 'Direction': [f"{args.groups[0]} {effect_direction} {args.groups[1]}"], + 'Direction': [f"{args.groups[0]} {expected_direction} {args.groups[1]}"], 'FDR q': [fdr_q], 'P value thresh': [p_value_thresh], 'Valid clusters': [significant_cluster_ids_str], diff --git a/unravel/docs/_build/doctrees/environment.pickle b/unravel/docs/_build/doctrees/environment.pickle index 53295fa0..cc7cdb5c 100644 Binary files a/unravel/docs/_build/doctrees/environment.pickle and b/unravel/docs/_build/doctrees/environment.pickle differ diff --git a/unravel/docs/_build/doctrees/unravel/cluster_stats/cluster_summary.doctree b/unravel/docs/_build/doctrees/unravel/cluster_stats/cluster_summary.doctree index 12258fb4..947360c1 100644 Binary files a/unravel/docs/_build/doctrees/unravel/cluster_stats/cluster_summary.doctree and b/unravel/docs/_build/doctrees/unravel/cluster_stats/cluster_summary.doctree differ diff --git a/unravel/docs/_build/doctrees/unravel/cluster_stats/stats.doctree b/unravel/docs/_build/doctrees/unravel/cluster_stats/stats.doctree index aa9587db..5684fe48 100644 Binary files a/unravel/docs/_build/doctrees/unravel/cluster_stats/stats.doctree and b/unravel/docs/_build/doctrees/unravel/cluster_stats/stats.doctree differ diff --git a/unravel/docs/_build/html/_modules/unravel/cluster_stats/cluster_summary.html b/unravel/docs/_build/html/_modules/unravel/cluster_stats/cluster_summary.html index df3a3a40..a97935df 100644 --- a/unravel/docs/_build/html/_modules/unravel/cluster_stats/cluster_summary.html +++ b/unravel/docs/_build/html/_modules/unravel/cluster_stats/cluster_summary.html @@ -356,11 +356,19 @@

Source code for unravel.cluster_stats.cluster_summary

Usage if running directly after ``cluster_validation``: ------------------------------------------------------- - cluster_summary -c <path/config.ini> -e <exp dir paths> -cvd '*' -vd <path/vstats_dir> -sk <path/sample_key.csv> --groups <group1> <group2> -v + cluster_summary -c <path/config.ini> -e <exp dir paths> -cvd 'psilocybin_v_saline_tstat1_q<asterisk>' -vd <path/vstats_dir> -sk <path/sample_key.csv> --groups <group1> <group2> -hg <higher_group> -v + +Note: + - The current working directory should not have other directories when running this script for the first time. Directories from cluster_org_data are ok though. Usage if running after ``cluster_validation`` and ``cluster_org_data``: ----------------------------------------------------------------------- - cluster_summary -c <path/config.ini> -sk <path/sample_key.csv> --groups <group1> <group2> -v + cluster_summary -c <path/config.ini> -sk <path/sample_key.csv> --groups <group1> <group2> -hg <higher_group> -v + +Note: + - For the second usage, the ``-e``, ``-cvd``, and ``-vd`` arguments are not needed because the data is already in the working directory. + - Only process one comparison at a time. If you have multiple comparisons, run this script separately for each comparison in separate directories. + - Then aggregate the results as needed (e.g. to make a legend with all relevant abbeviations, copy the .xlsx files to a central location and run ``cluster_legend``). The current working directory should not have other directories when running this script for the first time. Directories from cluster_org_data are ok though. @@ -379,6 +387,9 @@

Source code for unravel.cluster_stats.cluster_summary

dir_name,condition sample01,control sample02,treatment + +If you need to rerun this script, delete the following directories and files in the current working directory: +find . -name _valid_clusters -exec rm -rf {} \; -o -name cluster_validation_summary_t-test.csv -exec rm -f {} \; -o -name cluster_validation_summary_tukey.csv -exec rm -f {} \; -o -name 3D_brains -exec rm -rf {} \; -o -name valid_clusters_tables_and_legend -exec rm -rf {} \; -o -name _valid_clusters_stats -exec rm -rf {} \; """ import argparse @@ -412,6 +423,7 @@

Source code for unravel.cluster_stats.cluster_summary

# cluster_stats --groups <group1> <group2> parser.add_argument('--groups', help='List of group prefixes. 2 groups --> t-test. >2 --> Tukey\'s tests (The first 2 groups reflect the main comparison for validation rates; for cluster_stats)', nargs='+') parser.add_argument('-cp', '--condition_prefixes', help='Condition prefixes to group related data (optional for cluster_stats)', nargs='*', default=None, action=SM) + parser.add_argument('-hg', '--higher_group', help='Specify the group that is expected to have a higher mean based on the direction of the p value map', required=True) parser.add_argument('-v', '--verbose', help='Increase verbosity. Default: False', action='store_true', default=False) parser.epilog = __doc__ @@ -421,6 +433,7 @@

Source code for unravel.cluster_stats.cluster_summary

# TODO: Could add a progress bar that advances after each subdir, but need to adapt running of the first few scripts for this. Include check for completeness (all samples have csvs [from both hemis]). Review outputs and output folders and consider consolidating them. Could make cells vs. labels are arg. Could add a raw data output organized for the SI table. # The valid cluster sunburst could have the val dir name and be copied to a central location # TODO: Consider moving find_and_copy_files() to unravel/unravel/utils.py # TODO: Move cell vs. label arg from config back to argparse and make it a required arg to prevent accidentally using the wrong metric +# TODO: Add a reset option to delete all output files and directories from the current working directory
[docs] @@ -475,7 +488,8 @@

Source code for unravel.cluster_stats.cluster_summary

stats_args = [ '--groups', *args.groups, '-alt', cfg.stats.alternate, - '-pvt', cfg.org_data.p_val_txt + '-pvt', cfg.org_data.p_val_txt, + '-hg', args.higher_group ] if args.condition_prefixes: stats_args.append(['-cp', *args.condition_prefixes]) diff --git a/unravel/docs/_build/html/_modules/unravel/cluster_stats/stats.html b/unravel/docs/_build/html/_modules/unravel/cluster_stats/stats.html index 7b7275aa..5cade26e 100644 --- a/unravel/docs/_build/html/_modules/unravel/cluster_stats/stats.html +++ b/unravel/docs/_build/html/_modules/unravel/cluster_stats/stats.html @@ -356,14 +356,18 @@

Source code for unravel.cluster_stats.stats

 
 T-test usage:  
 ------------- 
-    cluster_stats --groups <group1> <group2>
+    cluster_stats --groups <group1> <group2> -hg <group1|group2>
 
 Tukey's test usage: 
 -------------------
-    cluster_stats --groups <group1> <group2> <group3> <group4> ...
+    cluster_stats --groups <group1> <group2> <group3> <group4> ... -hg <group1|group2>
 
-Input subdirs: 
-    <asterisk> 
+Note: 
+    - Organize data in directories for each comparison (e.g., psilocybin > saline, etc.)
+    - This script will loop through all directories in the current working dir and process the data in each subdir.
+    - Each subdir should contain .csv files with the density data for each cluster.
+    - The first 2 groups reflect the main comparison for validation rates.
+    - Clusters are not considered valid if the effect direction does not match the expected direction.
 
 Input files: 
     <asterisk>_density_data.csv from ``cluster_validation`` (e.g., in each subdir named after the rev_cluster_index.nii.gz file)    
@@ -417,6 +421,7 @@ 
Source code for unravel.cluster_stats.stats
     parser = argparse.ArgumentParser(formatter_class=SuppressMetavar)
     parser.add_argument('--groups', help='List of group prefixes. 2 groups --> t-test. >2 --> Tukey\'s tests (The first 2 groups reflect the main comparison for validation rates)',  nargs='+', required=True)
     parser.add_argument('-cp', '--condition_prefixes', help='Condition prefixes to group data (e.g., see info for examples)',  nargs='*', default=None, action=SM)
+    parser.add_argument('-hg', '--higher_group', help='Specify the group that is expected to have a higher mean based on the direction of the p value map', required=True)
     parser.add_argument('-alt', "--alternate", help="Number of tails and direction ('two-sided' [default], 'less' [group1 < group2], or 'greater')", default='two-sided', action=SM)
     parser.add_argument('-pvt', '--p_val_txt', help='Name of the file w/ the corrected p value thresh (e.g., from cluster_fdr). Default: p_value_threshold.txt', default='p_value_threshold.txt', action=SM)
     parser.add_argument('-v', '--verbose', help='Increase verbosity. Default: False', action='store_true', default=False)
@@ -424,6 +429,7 @@ 
Source code for unravel.cluster_stats.stats
     return parser.parse_args()

 
 
+
 # TODO: Test grouping of conditions. Test w/ label densities data. Could set up dunnett's tests and/or holm sidak tests.
 
 
@@ -633,8 +639,18 @@ 
Source code for unravel.cluster_stats.stats
     args = parse_args()
     current_dir = Path.cwd()
 
+    # Check for subdirectories in the current working directory
+    subdirs = [d for d in current_dir.iterdir() if d.is_dir()]
+    if not subdirs:
+        print(f"    [red1]No directories found in the current working directory: {current_dir}")
+        return
+    if subdirs[0].name == '_valid_clusters_stats':
+        print(f"    [red1]Only the '_valid_clusters_stats' directory found in the current working directory: {current_dir}")
+        print("    [red1]The script was likely run from a subdirectory instead of a directory containing subdirectories.")
+        return
+
     # Iterate over all subdirectories in the current working directory
-    for subdir in [d for d in current_dir.iterdir() if d.is_dir()]:
+    for subdir in subdirs:
         print(f"\nProcessing directory: [default bold]{subdir.name}[/]")
 
         # Load all .csv files in the current subdirectory
@@ -668,7 +684,7 @@ 
Source code for unravel.cluster_stats.stats
         # Aggregate the data from all .csv files and pool the data if hemispheres are present
         data_df = cluster_validation_data_df(density_col, has_hemisphere, csv_files, args.groups, data_col, data_col_pooled, args.condition_prefixes)
         if data_df.empty:
-            print("No data files match the specified groups. The prefixes of the csv files must match the group names.")
+            print("    [red1]No data files match the specified groups. The prefixes of the csv files must match the group names.")
             continue
 
         # Check the number of groups and perform the appropriate statistical test
@@ -687,24 +703,36 @@ 
Source code for unravel.cluster_stats.stats
             print(f"Running [gold1 bold]Tukey's tests")
             stats_df = perform_tukey_test(data_df, args.groups, density_col)
 
-        # Save the results to a .csv file
-        stats_results_csv = output_dir / 't-test_results.csv' if len(args.groups) == 2 else output_dir / 'tukey_results.csv'
-        stats_df.to_csv(stats_results_csv, index=False)
+        # Validate the clusters based on the expected direction of the effect
+        if args.higher_group not in args.groups:
+            print(f"    [red1]Error: The specified higher group '{args.higher_group}' is not one of the groups.")
+            return
+        expected_direction = '>' if args.higher_group == args.groups[0] else '<'
+        incongruent_clusters = stats_df[(stats_df['higher_mean_group'] != args.higher_group) & (stats_df['significance'] != 'n.s.')]['cluster_ID'].tolist()
 
-        # Get the overall mean density for each condition and determine the effect direction
-        group_one_mean = data_df[data_df['condition'] == args.groups[0]][density_col].mean()
-        group_two_mean = data_df[data_df['condition'] == args.groups[1]][density_col].mean()
-        if group_one_mean > group_two_mean:
-            effect_direction = '>'
-        elif group_one_mean < group_two_mean:
-            effect_direction = '<'
-        elif group_one_mean == group_two_mean: 
-            effect_direction = '=='
+        with open(output_dir / 'incongruent_clusters.txt', 'w') as f:
+            f.write('\n'.join(map(str, incongruent_clusters)))
+        
+        print(f"Expected effect direction: [green bold]{args.groups[0]} {expected_direction} {args.groups[1]}")
 
-        if len(args.groups) == 2:
-            print(f"Effect direction: [green bold]{args.groups[0]} {effect_direction} {args.groups[1]}")
+        if not incongruent_clusters:
+            print("All significant clusters are congruent with the expected direction")
         else:
-            print(f"Effect direction of interest: [green bold]{args.groups[0]} {effect_direction} {args.groups[1]}")
+            print(f"{len(incongruent_clusters)} of {total_clusters} clusters are incongruent with the expected direction.")
+            print (f"Although they had a significant difference, they not considered valid.")
+            print (f"'incongruent_clusters.txt' lists cluster IDs for incongruent clusters.")
+
+        # Invalidate clusters that are incongruent with the expected direction
+        stats_df['significance'] = stats_df.apply(lambda row: 'n.s.' if row['cluster_ID'] in incongruent_clusters else row['significance'], axis=1)
+
+        # Remove invalidated clusters from the list of significant clusters
+        significant_clusters = stats_df[stats_df['significance'] != 'n.s.']['cluster_ID']
+        significant_cluster_ids = significant_clusters.unique().tolist()
+        significant_cluster_ids_str = ' '.join(map(str, significant_cluster_ids))
+
+        # Save the results to a .csv file
+        stats_results_csv = output_dir / 't-test_results.csv' if len(args.groups) == 2 else output_dir / 'tukey_results.csv'
+        stats_df.to_csv(stats_results_csv, index=False)
 
         # Extract the FDR q value from the first csv file (float after 'FDR' or 'q' in the file name)
         first_csv_name = csv_files[0]
@@ -715,7 +743,7 @@ 
Source code for unravel.cluster_stats.stats
             p_val_txt = next(Path(subdir).glob('**/*' + args.p_val_txt), None)
             if p_val_txt is None:
                 # If no file is found, print an error message and skip further processing for this directory
-                print(f"No p-value file found matching '{args.p_val_txt}' in directory {subdir}. Please check the file name and path.")
+                print(f"    [red1]No p-value file found matching '{args.p_val_txt}' in directory {subdir}. Please check the file name and path.")
                 import sys ; sys.exit()
             with open(p_val_txt, 'r') as f:
                 p_value_thresh = float(f.read())
@@ -726,10 +754,7 @@ 
Source code for unravel.cluster_stats.stats
 
         # Print validation info: 
         print(f"FDR q: [cyan bold]{fdr_q}[/] == p-value threshold: [cyan bold]{p_value_thresh}")
-        significant_clusters = stats_df[stats_df['p-value'] < 0.05]['cluster_ID']
-        significant_cluster_ids = significant_clusters.unique().tolist()
-        significant_cluster_ids_str = ' '.join(map(str, significant_cluster_ids))
-        print(f"Valid cluster IDs: [blue bold]{significant_cluster_ids_str}")
+        print(f"Valid cluster IDs: {significant_cluster_ids_str}")
         print(f"[default]# of valid / total #: [bright_magenta]{len(significant_cluster_ids)} / {total_clusters}")
         validation_rate = len(significant_cluster_ids) / total_clusters * 100
         print(f"Cluster validation rate: [purple bold]{validation_rate:.2f}%")
@@ -744,7 +769,7 @@ 
Source code for unravel.cluster_stats.stats
         # Save the # of sig. clusters, total clusters, and cluster validation rate to a .txt file
         validation_inf_txt = output_dir / 'cluster_validation_info_t-test.txt' if len(args.groups) == 2 else output_dir / 'cluster_validation_info_tukey.txt'
         with open(validation_inf_txt, 'w') as f:
-            f.write(f"Direction: {args.groups[0]} {effect_direction} {args.groups[1]}\n")
+            f.write(f"Direction: {args.groups[0]} {expected_direction} {args.groups[1]}\n")
             f.write(f"FDR q: {fdr_q} == p-value threshold {p_value_thresh}\n")
             f.write(f"Valid cluster IDs: {significant_cluster_ids_str}\n")
             f.write(f"# of valid / total #: {len(significant_cluster_ids)} / {total_clusters}\n")
@@ -757,7 +782,7 @@ 
Source code for unravel.cluster_stats.stats
         
         # Save cluster validation info for ``cluster_summary`` 
         data_df = pd.DataFrame({
-            'Direction': [f"{args.groups[0]} {effect_direction} {args.groups[1]}"],
+            'Direction': [f"{args.groups[0]} {expected_direction} {args.groups[1]}"],
             'FDR q': [fdr_q],
             'P value thresh': [p_value_thresh],
             'Valid clusters': [significant_cluster_ids_str],
diff --git a/unravel/docs/_build/html/searchindex.js b/unravel/docs/_build/html/searchindex.js
index 0942646c..e007fb4d 100644
--- a/unravel/docs/_build/html/searchindex.js
+++ b/unravel/docs/_build/html/searchindex.js
@@ -1 +1 @@
-Search.setIndex({"alltitles": {"3 letter orientation code": [[0, null]], "Add images to sample?? dirs": [[0, "add-images-to-sample-dirs"]], "Additional contributions from": [[1, "additional-contributions-from"]], "All commands": [[0, null]], "Allen brain atlas coloring": [[0, null]], "Analysis steps": [[0, "analysis-steps"]], "Automatic logging of scripts": [[0, null]], "Back up raw data": [[0, "back-up-raw-data"]], "Background subtraction": [[0, null]], "Batch stitching settings": [[0, null]], "CLI usage:": [[96, "cli-usage"]], "Cluster correction": [[0, "cluster-correction"]], "Cluster validation": [[0, "cluster-validation"]], "Common commands": [[0, "common-commands"]], "Contact us": [[1, "contact-us"]], "Contents:": [[1, null]], "Data can be distributed across multiple drives": [[0, null]], "Define common variables in a shell script": [[0, "define-common-variables-in-a-shell-script"]], "Developers": [[1, "developers"]], "Editing .bashrc or .zshrc": [[2, "editing-bashrc-or-zshrc"]], "Example experiment folder structure after analysis": [[0, "example-experiment-folder-structure-after-analysis"]], "Example sample?? folder structure after analysis": [[0, "example-sample-folder-structure-after-analysis"]], "Getting started": [[1, "getting-started"]], "Guide": [[0, "guide"]], "Help on commands": [[0, "help-on-commands"]], "Helper Functions:": [[28, "helper-functions"]], "If sample orientations vary": [[0, null]], "Indices": [[1, "indices"]], "Installation": [[2, "installation"]], "Installing UNRAVEL on Linux or WSL": [[2, "installing-unravel-on-linux-or-wsl"]], "Listing commands": [[0, "listing-commands"]], "Log exp paths, commands, etc.": [[0, "log-exp-paths-commands-etc"]], "Main Functions:": [[28, "main-functions"]], "Main dependencies": [[1, "main-dependencies"]], "Make a sample_key.csv:": [[0, "make-a-sample-key-csv"]], "Make an exp_notes.txt": [[0, null]], "Make sample folders": [[0, "make-sample-folders"]], "Module contents": [[75, "module-contents"]], "More info on commands": [[0, null]], "Name sample folders like sample01, sample02, \u2026": [[0, null]], "Note x/y and z voxel sizes": [[0, "note-x-y-and-z-voxel-sizes"]], "Open source options for stitching": [[0, null]], "Optional: clean tifs": [[0, "optional-clean-tifs"]], "Overview and steps for voxel-wise stats": [[0, null]], "Python usage:": [[65, "python-usage"], [96, "python-usage"]], "Region-wise stats": [[0, "region-wise-stats"]], "Registration": [[0, "registration"]], "Running batch stitching": [[0, null]], "Segmentation": [[0, "segmentation"]], "Set up": [[0, "set-up"]], "Setting Up Windows Subsystem for Linux (WSL)": [[2, "setting-up-windows-subsystem-for-linux-wsl"]], "Sorting by hierarchy and volume:": [[23, "sorting-by-hierarchy-and-volume"]], "Stitch z-stacks": [[0, "stitch-z-stacks"]], "Subpackages": [[75, "subpackages"]], "Support is welcome for": [[1, "support-is-welcome-for"]], "Syntax": [[0, null]], "T-test usage:": [[20, "t-test-usage"]], "Todo": [[0, "id1"], [0, "id2"], [0, "id5"], [2, "id1"]], "Train an Ilastik project": [[0, "train-an-ilastik-project"], [0, null]], "Tukey\u2019s test usage:": [[20, "tukey-s-test-usage"]], "Typical workflow": [[0, "typical-workflow"]], "UN-biased high-Resolution Analysis and Validation of Ensembles using Light sheet images": [[1, "un-biased-high-resolution-analysis-and-validation-of-ensembles-using-light-sheet-images"]], "UNRAVEL visualizer": [[1, "unravel-visualizer"]], "Usage": [[3, "usage"], [6, "usage"], [7, "usage"], [9, "usage"], [11, "usage"], [12, "usage"], [13, "usage"], [14, "usage"], [15, "usage"], [17, "usage"], [18, "usage"], [19, "usage"], [61, "usage"]], "Usage for Tukey\u2019s tests w/ reordering and renaming of conditions:": [[62, "usage-for-tukey-s-tests-w-reordering-and-renaming-of-conditions"]], "Usage for activating sample?? dirs for certain conditions:": [[83, "usage-for-activating-sample-dirs-for-certain-conditions"]], "Usage for checking which clusters are present if the min cluster size was 100 voxels:": [[58, "usage-for-checking-which-clusters-are-present-if-the-min-cluster-size-was-100-voxels"]], "Usage for forward warping atlas to tissue space:": [[98, "usage-for-forward-warping-atlas-to-tissue-space"]], "Usage for inverse warping tissue to atlas space:": [[98, "usage-for-inverse-warping-tissue-to-atlas-space"]], "Usage for printing all non-zero intensities:": [[58, "usage-for-printing-all-non-zero-intensities"]], "Usage for printing the number of voxels for each intensity that is present:": [[58, "usage-for-printing-the-number-of-voxels-for-each-intensity-that-is-present"]], "Usage for renaming directories:": [[81, "usage-for-renaming-directories"]], "Usage for renaming files:": [[81, "usage-for-renaming-files"]], "Usage for t-tests:": [[62, "usage-for-t-tests"]], "Usage for toggling all sample?? dirs to active:": [[83, "usage-for-toggling-all-sample-dirs-to-active"]], "Usage for when metadata is extractable:": [[36, "usage-for-when-metadata-is-extractable"]], "Usage for when metadata is not extractable:": [[36, "usage-for-when-metadata-is-not-extractable"]], "Usage for when sample?? is already in the name of files being copied:": [[77, "usage-for-when-sample-is-already-in-the-name-of-files-being-copied"]], "Usage for z-score scaling (if 8 bit is needed):": [[35, "usage-for-z-score-scaling-if-8-bit-is-needed"]], "Usage if running after cluster_validation and cluster_org_data:": [[4, "usage-if-running-after-cluster-validation-and-cluster-org-data"]], "Usage if running directly after cluster_validation:": [[4, "usage-if-running-directly-after-cluster-validation"]], "Usage if the atlas is already in native space from warp_to_native:": [[59, "usage-if-the-atlas-is-already-in-native-space-from-warp-to-native"]], "Usage if the native atlas is not available; it is not saved (faster):": [[59, "usage-if-the-native-atlas-is-not-available-it-is-not-saved-faster"]], "Usage to prep for seg_brain_mask (if \u2013mask_dir  and -e  were not specified in reg_prep):": [[72, "usage-to-prep-for-seg-brain-mask-if-mask-dir-path-mask-dir-and-e-exp-dir-paths-were-not-specified-in-reg-prep"]], "Usage to prep for seg_ilastik to segment full resolution immunofluorescence images:": [[72, "usage-to-prep-for-seg-ilastik-to-segment-full-resolution-immunofluorescence-images"]], "Usage to prepend sample?? to the name of files being copied:": [[77, "usage-to-prepend-sample-to-the-name-of-files-being-copied"]], "Usage to print all commands and module names:": [[76, "usage-to-print-all-commands-and-module-names"]], "Usage to print common commands and descriptions:": [[76, "usage-to-print-common-commands-and-descriptions"]], "Usage to replace voxels in image with the mean intensity in the brain where mask > 0:": [[84, "usage-to-replace-voxels-in-image-with-the-mean-intensity-in-the-brain-where-mask-0"]], "Usage to zero out voxels in image where mask < 1 (e.g., to preserve signal from segmented microglia clusters):": [[84, "usage-to-zero-out-voxels-in-image-where-mask-1-e-g-to-preserve-signal-from-segmented-microglia-clusters"]], "Usage to zero out voxels in image where mask > 0 (e.g., to exclude voxels representing artifacts):": [[84, "usage-to-zero-out-voxels-in-image-where-mask-0-e-g-to-exclude-voxels-representing-artifacts"]], "Usage w/ a tissue mask (warped to atlas space):": [[94, "usage-w-a-tissue-mask-warped-to-atlas-space"]], "Usage w/ an atlas mask (warped to atlas space):": [[94, "usage-w-an-atlas-mask-warped-to-atlas-space"]], "Usage w/ both masks for side-specific z-scoring:": [[94, "usage-w-both-masks-for-side-specific-z-scoring"]], "Usage with a custom atlas:": [[62, "usage-with-a-custom-atlas"]], "Usage:": [[5, "usage"], [16, "usage"], [21, "usage"], [22, "usage"], [23, "usage"], [32, "usage"], [33, "usage"], [34, "usage"], [35, "usage"], [37, "usage"], [38, "usage"], [39, "usage"], [40, "usage"], [41, "usage"], [42, "usage"], [44, "usage"], [45, "usage"], [46, "usage"], [48, "usage"], [49, "usage"], [50, "usage"], [52, "usage"], [53, "usage"], [54, "usage"], [55, "usage"], [57, "usage"], [60, "usage"], [63, "usage"], [65, "usage"], [66, "usage"], [67, "usage"], [68, "usage"], [69, "usage"], [71, "usage"], [73, "usage"], [78, "usage"], [79, "usage"], [80, "usage"], [85, "usage"], [86, "usage"], [87, "usage"], [88, "usage"], [91, "usage"], [93, "usage"], [95, "usage"]], "Voxel-wise stats": [[0, "voxel-wise-stats"]], "cluster_fdr": [[0, "cluster-fdr"]], "cluster_fdr_range": [[0, "cluster-fdr-range"]], "cluster_mirror_indices": [[0, "cluster-mirror-indices"]], "cluster_summary": [[0, "cluster-summary"]], "cluster_validation": [[0, "id4"]], "env_var.sh": [[0, null]], "img_avg": [[0, "img-avg"]], "reg": [[0, "reg"]], "reg_check": [[0, "reg-check"]], "reg_prep": [[0, "reg-prep"]], "rstats": [[0, "rstats"]], "rstats_summary": [[0, "rstats-summary"]], "seg_brain_mask": [[0, "seg-brain-mask"]], "seg_copy_tifs": [[0, "seg-copy-tifs"], [0, "id3"]], "seg_ilastik": [[0, "seg-ilastik"]], "unravel package": [[75, "unravel-package"]], "unravel.cluster_stats package": [[24, "unravel-cluster-stats-package"]], "unravel.cluster_stats.brain_model module": [[3, "module-unravel.cluster_stats.brain_model"]], "unravel.cluster_stats.cluster_summary module": [[4, "module-unravel.cluster_stats.cluster_summary"]], "unravel.cluster_stats.cluster_validation module": [[5, "module-unravel.cluster_stats.cluster_validation"]], "unravel.cluster_stats.crop module": [[6, "module-unravel.cluster_stats.crop"]], "unravel.cluster_stats.effect_sizes package": [[10, "unravel-cluster-stats-effect-sizes-package"]], "unravel.cluster_stats.effect_sizes.effect_sizes module": [[7, "module-unravel.cluster_stats.effect_sizes.effect_sizes"]], "unravel.cluster_stats.effect_sizes.effect_sizes_by_sex__absolute module": [[8, "module-unravel.cluster_stats.effect_sizes.effect_sizes_by_sex__absolute"]], "unravel.cluster_stats.effect_sizes.effect_sizes_by_sex__relative module": [[9, "module-unravel.cluster_stats.effect_sizes.effect_sizes_by_sex__relative"]], "unravel.cluster_stats.fdr module": [[11, "module-unravel.cluster_stats.fdr"]], "unravel.cluster_stats.fdr_range module": [[12, "module-unravel.cluster_stats.fdr_range"]], "unravel.cluster_stats.find_incongruent_clusters module": [[13, "module-unravel.cluster_stats.find_incongruent_clusters"]], "unravel.cluster_stats.group_bilateral_data module": [[14, "module-unravel.cluster_stats.group_bilateral_data"]], "unravel.cluster_stats.index module": [[15, "module-unravel.cluster_stats.index"]], "unravel.cluster_stats.legend module": [[16, "module-unravel.cluster_stats.legend"]], "unravel.cluster_stats.org_data module": [[17, "module-unravel.cluster_stats.org_data"]], "unravel.cluster_stats.prism module": [[18, "module-unravel.cluster_stats.prism"]], "unravel.cluster_stats.recursively_mirror_rev_cluster_indices module": [[19, "module-unravel.cluster_stats.recursively_mirror_rev_cluster_indices"]], "unravel.cluster_stats.stats module": [[20, "module-unravel.cluster_stats.stats"]], "unravel.cluster_stats.stats_table module": [[21, "module-unravel.cluster_stats.stats_table"]], "unravel.cluster_stats.sunburst module": [[22, "module-unravel.cluster_stats.sunburst"]], "unravel.cluster_stats.table module": [[23, "module-unravel.cluster_stats.table"]], "unravel.core package": [[30, "unravel-core-package"]], "unravel.core.argparse_utils module": [[25, "module-unravel.core.argparse_utils"]], "unravel.core.argparse_utils_rich module": [[26, "module-unravel.core.argparse_utils_rich"]], "unravel.core.config module": [[27, "module-unravel.core.config"]], "unravel.core.img_io module": [[28, "module-unravel.core.img_io"]], "unravel.core.img_tools module": [[29, "module-unravel.core.img_tools"]], "unravel.core.utils module": [[31, "module-unravel.core.utils"]], "unravel.image_io package": [[43, "unravel-image-io-package"]], "unravel.image_io.h5_to_tifs module": [[32, "module-unravel.image_io.h5_to_tifs"]], "unravel.image_io.img_to_npy module": [[33, "module-unravel.image_io.img_to_npy"]], "unravel.image_io.io_img module": [[34, "module-unravel.image_io.io_img"]], "unravel.image_io.io_nii module": [[35, "module-unravel.image_io.io_nii"]], "unravel.image_io.metadata module": [[36, "module-unravel.image_io.metadata"]], "unravel.image_io.nii_hd module": [[37, "module-unravel.image_io.nii_hd"]], "unravel.image_io.nii_info module": [[38, "module-unravel.image_io.nii_info"]], "unravel.image_io.nii_to_tifs module": [[39, "module-unravel.image_io.nii_to_tifs"]], "unravel.image_io.nii_to_zarr module": [[40, "module-unravel.image_io.nii_to_zarr"]], "unravel.image_io.reorient_nii module": [[41, "module-unravel.image_io.reorient_nii"]], "unravel.image_io.tif_to_tifs module": [[42, "module-unravel.image_io.tif_to_tifs"]], "unravel.image_io.zarr_to_nii module": [[44, "module-unravel.image_io.zarr_to_nii"]], "unravel.image_tools package": [[56, "unravel-image-tools-package"]], "unravel.image_tools.DoG module": [[45, "module-unravel.image_tools.DoG"]], "unravel.image_tools.atlas package": [[47, "unravel-image-tools-atlas-package"]], "unravel.image_tools.atlas.relabel_nii module": [[46, "module-unravel.image_tools.atlas.relabel_nii"]], "unravel.image_tools.atlas.wireframe module": [[48, "module-unravel.image_tools.atlas.wireframe"]], "unravel.image_tools.avg module": [[49, "module-unravel.image_tools.avg"]], "unravel.image_tools.bbox module": [[50, "module-unravel.image_tools.bbox"]], "unravel.image_tools.extend module": [[51, "module-unravel.image_tools.extend"]], "unravel.image_tools.max module": [[52, "module-unravel.image_tools.max"]], "unravel.image_tools.pad module": [[53, "module-unravel.image_tools.pad"]], "unravel.image_tools.rb module": [[54, "module-unravel.image_tools.rb"]], "unravel.image_tools.spatial_averaging module": [[55, "module-unravel.image_tools.spatial_averaging"]], "unravel.image_tools.transpose_axes module": [[57, "module-unravel.image_tools.transpose_axes"]], "unravel.image_tools.unique_intensities module": [[58, "module-unravel.image_tools.unique_intensities"]], "unravel.region_stats package": [[64, "unravel-region-stats-package"]], "unravel.region_stats.rstats module": [[59, "module-unravel.region_stats.rstats"]], "unravel.region_stats.rstats_mean_IF module": [[60, "module-unravel.region_stats.rstats_mean_IF"]], "unravel.region_stats.rstats_mean_IF_in_segmented_voxels module": [[61, "module-unravel.region_stats.rstats_mean_IF_in_segmented_voxels"]], "unravel.region_stats.rstats_mean_IF_summary module": [[62, "module-unravel.region_stats.rstats_mean_IF_summary"]], "unravel.region_stats.rstats_summary module": [[63, "module-unravel.region_stats.rstats_summary"]], "unravel.register package": [[70, "unravel-register-package"]], "unravel.register.affine_initializer module": [[65, "module-unravel.register.affine_initializer"]], "unravel.register.reg module": [[66, "module-unravel.register.reg"]], "unravel.register.reg_check module": [[67, "module-unravel.register.reg_check"]], "unravel.register.reg_check_brain_mask module": [[68, "module-unravel.register.reg_check_brain_mask"]], "unravel.register.reg_prep module": [[69, "module-unravel.register.reg_prep"]], "unravel.segment package": [[74, "unravel-segment-package"]], "unravel.segment.brain_mask module": [[71, "module-unravel.segment.brain_mask"]], "unravel.segment.copy_tifs module": [[72, "module-unravel.segment.copy_tifs"]], "unravel.segment.ilastik_pixel_classification module": [[73, "module-unravel.segment.ilastik_pixel_classification"]], "unravel.unravel_commands module": [[76, "module-unravel.unravel_commands"]], "unravel.utilities package": [[82, "unravel-utilities-package"]], "unravel.utilities.aggregate_files_from_sample_dirs module": [[77, "module-unravel.utilities.aggregate_files_from_sample_dirs"]], "unravel.utilities.aggregate_files_w_recursive_search module": [[78, "module-unravel.utilities.aggregate_files_w_recursive_search"]], "unravel.utilities.clean_tif_dirs module": [[79, "module-unravel.utilities.clean_tif_dirs"]], "unravel.utilities.prepend_conditions module": [[80, "module-unravel.utilities.prepend_conditions"]], "unravel.utilities.rename module": [[81, "module-unravel.utilities.rename"]], "unravel.utilities.toggle_samples module": [[83, "module-unravel.utilities.toggle_samples"]], "unravel.voxel_stats package": [[90, "unravel-voxel-stats-package"]], "unravel.voxel_stats.apply_mask module": [[84, "module-unravel.voxel_stats.apply_mask"]], "unravel.voxel_stats.hemi_to_LR_avg module": [[85, "module-unravel.voxel_stats.hemi_to_LR_avg"]], "unravel.voxel_stats.mirror module": [[86, "module-unravel.voxel_stats.mirror"]], "unravel.voxel_stats.other package": [[89, "unravel-voxel-stats-other-package"]], "unravel.voxel_stats.other.IF_outliers module": [[87, "module-unravel.voxel_stats.other.IF_outliers"]], "unravel.voxel_stats.other.r_to_p module": [[88, "module-unravel.voxel_stats.other.r_to_p"]], "unravel.voxel_stats.vstats module": [[91, "module-unravel.voxel_stats.vstats"]], "unravel.voxel_stats.vstats_prep module": [[92, "module-unravel.voxel_stats.vstats_prep"]], "unravel.voxel_stats.whole_to_LR_avg module": [[93, "module-unravel.voxel_stats.whole_to_LR_avg"]], "unravel.voxel_stats.z_score module": [[94, "module-unravel.voxel_stats.z_score"]], "unravel.warp package": [[97, "unravel-warp-package"]], "unravel.warp.to_atlas module": [[95, "module-unravel.warp.to_atlas"]], "unravel.warp.to_native module": [[96, "module-unravel.warp.to_native"]], "unravel.warp.warp module": [[98, "module-unravel.warp.warp"]], "utils_agg_files": [[0, "utils-agg-files"]], "utils_clean_tifs": [[0, null]], "utils_prepend": [[0, "utils-prepend"]], "vstats": [[0, "vstats"]], "vstats_prep": [[0, "vstats-prep"]], "vstats_whole_to_avg": [[0, "vstats-whole-to-avg"]], "vstats_z_score": [[0, "vstats-z-score"]]}, "docnames": ["guide", "index", 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\ No newline at end of file
+Search.setIndex({"alltitles": {"3 letter orientation code": [[0, null]], "Add images to sample?? dirs": [[0, "add-images-to-sample-dirs"]], "Additional contributions from": [[1, "additional-contributions-from"]], "All commands": [[0, null]], "Allen brain atlas coloring": [[0, null]], "Analysis steps": [[0, "analysis-steps"]], "Automatic logging of scripts": [[0, null]], "Back up raw data": [[0, "back-up-raw-data"]], "Background subtraction": [[0, null]], "Batch stitching settings": [[0, null]], "CLI usage:": [[96, "cli-usage"]], "Cluster correction": [[0, "cluster-correction"]], "Cluster validation": [[0, "cluster-validation"]], "Common commands": [[0, "common-commands"]], "Contact us": [[1, "contact-us"]], "Contents:": [[1, null]], "Data can be distributed across multiple drives": [[0, null]], "Define common variables in a shell script": [[0, "define-common-variables-in-a-shell-script"]], "Developers": [[1, "developers"]], "Editing .bashrc or .zshrc": [[2, "editing-bashrc-or-zshrc"]], "Example experiment folder structure after analysis": [[0, "example-experiment-folder-structure-after-analysis"]], "Example sample?? folder structure after analysis": [[0, "example-sample-folder-structure-after-analysis"]], "Getting started": [[1, "getting-started"]], "Guide": [[0, "guide"]], "Help on commands": [[0, "help-on-commands"]], "Helper Functions:": [[28, "helper-functions"]], "If sample orientations vary": [[0, null]], "Indices": [[1, "indices"]], "Installation": [[2, "installation"]], "Installing UNRAVEL on Linux or WSL": [[2, "installing-unravel-on-linux-or-wsl"]], "Listing commands": [[0, "listing-commands"]], "Log exp paths, commands, etc.": [[0, "log-exp-paths-commands-etc"]], "Main Functions:": [[28, "main-functions"]], "Main dependencies": [[1, "main-dependencies"]], "Make a sample_key.csv:": [[0, "make-a-sample-key-csv"]], "Make an exp_notes.txt": [[0, null]], "Make sample folders": [[0, "make-sample-folders"]], "Module contents": [[75, "module-contents"]], "More info on commands": [[0, null]], "Name sample folders like sample01, sample02, \u2026": [[0, null]], "Note x/y and z voxel sizes": [[0, "note-x-y-and-z-voxel-sizes"]], "Open source options for stitching": [[0, null]], "Optional: clean tifs": [[0, "optional-clean-tifs"]], "Overview and steps for voxel-wise stats": [[0, null]], "Python usage:": [[65, "python-usage"], [96, "python-usage"]], "Region-wise stats": [[0, "region-wise-stats"]], "Registration": [[0, "registration"]], "Running batch stitching": [[0, null]], "Segmentation": [[0, "segmentation"]], "Set up": [[0, "set-up"]], "Setting Up Windows Subsystem for Linux (WSL)": [[2, "setting-up-windows-subsystem-for-linux-wsl"]], "Sorting by hierarchy and volume:": [[23, "sorting-by-hierarchy-and-volume"]], "Stitch z-stacks": [[0, "stitch-z-stacks"]], "Subpackages": [[75, "subpackages"]], "Support is welcome for": [[1, "support-is-welcome-for"]], "Syntax": [[0, null]], "T-test usage:": [[20, "t-test-usage"]], "Todo": [[0, "id1"], [0, "id2"], [0, "id5"], [2, "id1"]], "Train an Ilastik project": [[0, "train-an-ilastik-project"], [0, null]], "Tukey\u2019s test usage:": [[20, "tukey-s-test-usage"]], "Typical workflow": [[0, "typical-workflow"]], "UN-biased high-Resolution Analysis and Validation of Ensembles using Light sheet images": [[1, "un-biased-high-resolution-analysis-and-validation-of-ensembles-using-light-sheet-images"]], "UNRAVEL visualizer": [[1, "unravel-visualizer"]], "Usage": [[3, "usage"], [6, "usage"], [7, "usage"], [9, "usage"], [11, "usage"], [12, "usage"], [13, "usage"], [14, "usage"], [15, "usage"], [17, "usage"], [18, "usage"], [19, "usage"], [61, "usage"]], "Usage for Tukey\u2019s tests w/ reordering and renaming of conditions:": [[62, "usage-for-tukey-s-tests-w-reordering-and-renaming-of-conditions"]], "Usage for activating sample?? dirs for certain conditions:": [[83, "usage-for-activating-sample-dirs-for-certain-conditions"]], "Usage for checking which clusters are present if the min cluster size was 100 voxels:": [[58, "usage-for-checking-which-clusters-are-present-if-the-min-cluster-size-was-100-voxels"]], "Usage for forward warping atlas to tissue space:": [[98, "usage-for-forward-warping-atlas-to-tissue-space"]], "Usage for inverse warping tissue to atlas space:": [[98, "usage-for-inverse-warping-tissue-to-atlas-space"]], "Usage for printing all non-zero intensities:": [[58, "usage-for-printing-all-non-zero-intensities"]], "Usage for printing the number of voxels for each intensity that is present:": [[58, "usage-for-printing-the-number-of-voxels-for-each-intensity-that-is-present"]], "Usage for renaming directories:": [[81, "usage-for-renaming-directories"]], "Usage for renaming files:": [[81, "usage-for-renaming-files"]], "Usage for t-tests:": [[62, "usage-for-t-tests"]], "Usage for toggling all sample?? dirs to active:": [[83, "usage-for-toggling-all-sample-dirs-to-active"]], "Usage for when metadata is extractable:": [[36, "usage-for-when-metadata-is-extractable"]], "Usage for when metadata is not extractable:": [[36, "usage-for-when-metadata-is-not-extractable"]], "Usage for when sample?? is already in the name of files being copied:": [[77, "usage-for-when-sample-is-already-in-the-name-of-files-being-copied"]], "Usage for z-score scaling (if 8 bit is needed):": [[35, "usage-for-z-score-scaling-if-8-bit-is-needed"]], "Usage if running after cluster_validation and cluster_org_data:": [[4, "usage-if-running-after-cluster-validation-and-cluster-org-data"]], "Usage if running directly after cluster_validation:": [[4, "usage-if-running-directly-after-cluster-validation"]], "Usage if the atlas is already in native space from warp_to_native:": [[59, "usage-if-the-atlas-is-already-in-native-space-from-warp-to-native"]], "Usage if the native atlas is not available; it is not saved (faster):": [[59, "usage-if-the-native-atlas-is-not-available-it-is-not-saved-faster"]], "Usage to prep for seg_brain_mask (if \u2013mask_dir  and -e  were not specified in reg_prep):": [[72, "usage-to-prep-for-seg-brain-mask-if-mask-dir-path-mask-dir-and-e-exp-dir-paths-were-not-specified-in-reg-prep"]], "Usage to prep for seg_ilastik to segment full resolution immunofluorescence images:": [[72, "usage-to-prep-for-seg-ilastik-to-segment-full-resolution-immunofluorescence-images"]], "Usage to prepend sample?? to the name of files being copied:": [[77, "usage-to-prepend-sample-to-the-name-of-files-being-copied"]], "Usage to print all commands and module names:": [[76, "usage-to-print-all-commands-and-module-names"]], "Usage to print common commands and descriptions:": [[76, "usage-to-print-common-commands-and-descriptions"]], "Usage to replace voxels in image with the mean intensity in the brain where mask > 0:": [[84, "usage-to-replace-voxels-in-image-with-the-mean-intensity-in-the-brain-where-mask-0"]], "Usage to zero out voxels in image where mask < 1 (e.g., to preserve signal from segmented microglia 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"seg_ilastik": [[0, "seg-ilastik"]], "unravel package": [[75, "unravel-package"]], "unravel.cluster_stats package": [[24, "unravel-cluster-stats-package"]], "unravel.cluster_stats.brain_model module": [[3, "module-unravel.cluster_stats.brain_model"]], "unravel.cluster_stats.cluster_summary module": [[4, "module-unravel.cluster_stats.cluster_summary"]], "unravel.cluster_stats.cluster_validation module": [[5, "module-unravel.cluster_stats.cluster_validation"]], "unravel.cluster_stats.crop module": [[6, "module-unravel.cluster_stats.crop"]], "unravel.cluster_stats.effect_sizes package": [[10, "unravel-cluster-stats-effect-sizes-package"]], "unravel.cluster_stats.effect_sizes.effect_sizes module": [[7, "module-unravel.cluster_stats.effect_sizes.effect_sizes"]], "unravel.cluster_stats.effect_sizes.effect_sizes_by_sex__absolute module": [[8, "module-unravel.cluster_stats.effect_sizes.effect_sizes_by_sex__absolute"]], "unravel.cluster_stats.effect_sizes.effect_sizes_by_sex__relative module": 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"websit": 2, "well": 36, "were": [0, 1, 74, 75], "weslei": 1, "weszhao": 1, "wget": 2, "what": 81, "whatev": 0, "wheel": 0, "when": [4, 43, 75, 76, 82, 86], "where": [0, 2, 7, 8, 9, 13, 20, 23, 31, 48, 72, 75, 76, 90, 98], "whether": [20, 28, 81], "which": [56, 75, 76], "whole": [11, 94], "whole_to_lr_avg": [0, 1, 75, 90], "whose": [7, 8, 9, 20], "wide": 1, "width": [25, 26], "window": [0, 1], "wirefram": [0, 47, 56, 75], "wireframe_imag": 48, "wireframe_image_id": 48, "wise": [1, 91, 93, 94], "within": [0, 23, 29, 31, 62], "without": 81, "withs": 62, "word": [0, 18, 20, 62], "work": [0, 4, 16, 18, 20, 23, 26, 62, 67, 68], "workflow": [1, 76], "worksheet": 16, "write": [29, 60, 61], "write_to_csv": [60, 61, 64, 75], "wsl": 1, "x": [1, 6, 23, 28, 29, 36, 41, 51, 59, 66, 69, 84, 88, 92, 95, 96], "x_dim": 28, "xjf": 2, "xlsx": [4, 16], "xmax": [5, 28, 29], "xmin": [5, 28, 29], "xy": [0, 6, 28, 55], "xy_r": [5, 6, 28, 29, 32, 42, 59, 69, 96], "xy_voxel_s": [32, 42], "xyz": [28, 32, 42, 66], "xyz_res_in_um": 15, "xz": 2, "y": [1, 2, 28, 29, 36, 41, 59, 66, 69, 84, 96], "y_dim": 28, "yeild": [0, 12], "yellow": 0, "yield": 0, "ymax": [5, 28, 29], "ymin": [5, 28, 29], "you": [0, 1, 2, 4, 45, 76], "your": [0, 1, 2, 31, 76], "z": [1, 6, 13, 28, 29, 36, 41, 43, 55, 59, 66, 69, 75, 84, 88, 90, 92, 93, 95, 96], "z_dim": 28, "z_map": 88, "z_re": [5, 6, 28, 29, 32, 42, 59, 69, 96], "z_score": [0, 1, 75, 90], "z_to_p": [88, 89, 90], "z_voxel_s": [32, 42], "zarr": [0, 28, 34, 40, 44, 55, 84, 92, 95, 96], "zarr_path": 28, "zarr_to_ndarrai": [43, 44, 75], "zarr_to_nii": [1, 43, 75], "zeiss": 0, "zen": 0, "zero": [0, 12, 41, 55, 56, 75, 90], "zero_origin": 41, "zetastitch": 0, "zhao": 1, "zlib1g": 2, "zmax": [5, 28, 29], "zmin": [5, 28, 29], "zoom": [0, 29, 69], "zoom_ord": [29, 69, 96], "zscore": 35, "zscore_rang": 35, "zshrc": [0, 1, 76], "zyx": [32, 42], "\u00b5m": 0}, "titles": ["Guide", "UN-biased high-Resolution Analysis and Validation of Ensembles using Light sheet images", "Installation", "unravel.cluster_stats.brain_model module", "unravel.cluster_stats.cluster_summary module", "unravel.cluster_stats.cluster_validation module", "unravel.cluster_stats.crop module", "unravel.cluster_stats.effect_sizes.effect_sizes module", "unravel.cluster_stats.effect_sizes.effect_sizes_by_sex__absolute module", "unravel.cluster_stats.effect_sizes.effect_sizes_by_sex__relative module", "unravel.cluster_stats.effect_sizes package", "unravel.cluster_stats.fdr module", "unravel.cluster_stats.fdr_range module", "unravel.cluster_stats.find_incongruent_clusters module", "unravel.cluster_stats.group_bilateral_data module", "unravel.cluster_stats.index module", "unravel.cluster_stats.legend module", "unravel.cluster_stats.org_data module", "unravel.cluster_stats.prism module", "unravel.cluster_stats.recursively_mirror_rev_cluster_indices module", "unravel.cluster_stats.stats module", "unravel.cluster_stats.stats_table module", "unravel.cluster_stats.sunburst module", "unravel.cluster_stats.table module", "unravel.cluster_stats package", "unravel.core.argparse_utils module", "unravel.core.argparse_utils_rich module", "unravel.core.config module", "unravel.core.img_io module", "unravel.core.img_tools module", "unravel.core package", "unravel.core.utils module", "unravel.image_io.h5_to_tifs module", "unravel.image_io.img_to_npy module", "unravel.image_io.io_img module", "unravel.image_io.io_nii module", "unravel.image_io.metadata module", "unravel.image_io.nii_hd module", "unravel.image_io.nii_info module", "unravel.image_io.nii_to_tifs module", "unravel.image_io.nii_to_zarr module", "unravel.image_io.reorient_nii module", "unravel.image_io.tif_to_tifs module", "unravel.image_io package", "unravel.image_io.zarr_to_nii module", "unravel.image_tools.DoG module", "unravel.image_tools.atlas.relabel_nii module", "unravel.image_tools.atlas package", "unravel.image_tools.atlas.wireframe module", "unravel.image_tools.avg module", "unravel.image_tools.bbox module", "unravel.image_tools.extend module", "unravel.image_tools.max module", "unravel.image_tools.pad module", "unravel.image_tools.rb module", "unravel.image_tools.spatial_averaging module", "unravel.image_tools package", "unravel.image_tools.transpose_axes module", "unravel.image_tools.unique_intensities module", "unravel.region_stats.rstats module", "unravel.region_stats.rstats_mean_IF module", "unravel.region_stats.rstats_mean_IF_in_segmented_voxels module", "unravel.region_stats.rstats_mean_IF_summary module", "unravel.region_stats.rstats_summary module", "unravel.region_stats package", "unravel.register.affine_initializer module", "unravel.register.reg module", "unravel.register.reg_check module", "unravel.register.reg_check_brain_mask module", "unravel.register.reg_prep module", "unravel.register package", "unravel.segment.brain_mask module", "unravel.segment.copy_tifs module", "unravel.segment.ilastik_pixel_classification module", "unravel.segment package", "unravel package", "unravel.unravel_commands module", "unravel.utilities.aggregate_files_from_sample_dirs module", "unravel.utilities.aggregate_files_w_recursive_search module", "unravel.utilities.clean_tif_dirs module", "unravel.utilities.prepend_conditions module", "unravel.utilities.rename module", "unravel.utilities package", "unravel.utilities.toggle_samples module", "unravel.voxel_stats.apply_mask module", "unravel.voxel_stats.hemi_to_LR_avg module", "unravel.voxel_stats.mirror module", "unravel.voxel_stats.other.IF_outliers module", "unravel.voxel_stats.other.r_to_p module", "unravel.voxel_stats.other package", "unravel.voxel_stats package", "unravel.voxel_stats.vstats module", "unravel.voxel_stats.vstats_prep module", "unravel.voxel_stats.whole_to_LR_avg module", "unravel.voxel_stats.z_score module", "unravel.warp.to_atlas module", "unravel.warp.to_native module", "unravel.warp package", "unravel.warp.warp module"], "titleterms": {"": [20, 62], "0": 84, "1": 84, "100": 58, "3": 0, "8": 35, "If": 0, "across": 0, "activ": 83, "add": 0, "addit": 1, "affine_initi": 65, "after": [0, 4], "aggregate_files_from_sample_dir": 77, "aggregate_files_w_recursive_search": 78, "all": [0, 58, 76, 83], "allen": 0, "alreadi": [59, 77], "an": [0, 94], "analysi": [0, 1], "apply_mask": 84, "ar": 58, "argparse_util": 25, "argparse_utils_rich": 26, "artifact": 84, "atla": [0, 46, 47, 48, 59, 62, 94, 98], "automat": 0, "avail": 59, "avg": 49, "back": 0, "background": 0, "bashrc": 2, "batch": 0, "bbox": 50, "being": 77, "bias": 1, "bit": 35, "both": 94, "brain": [0, 84], "brain_mask": 71, "brain_model": 3, "can": 0, "certain": 83, "check": 58, "clean": 0, "clean_tif_dir": 79, "cli": 96, "cluster": [0, 58, 84], "cluster_fdr": 0, "cluster_fdr_rang": 0, "cluster_mirror_indic": 0, "cluster_org_data": 4, "cluster_stat": [3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24], "cluster_summari": [0, 4], "cluster_valid": [0, 4, 5], "code": 0, "color": 0, "command": [0, 76], "common": [0, 76], "condit": [62, 83], "config": 27, "contact": 1, "content": [1, 75], "contribut": 1, "copi": 77, "copy_tif": 72, "core": [25, 26, 27, 28, 29, 30, 31], "correct": 0, "crop": 6, "csv": 0, "custom": 62, "data": 0, "defin": 0, "depend": 1, "descript": 76, "develop": 1, "dir": [0, 72, 83], "directli": 4, "directori": 81, "distribut": 0, "dog": 45, "drive": 0, "e": [72, 84], "each": 58, "edit": 2, "effect_s": [7, 8, 9, 10], "effect_sizes_by_sex__absolut": 8, "effect_sizes_by_sex__rel": 9, "ensembl": 1, "env_var": 0, "etc": 0, "exampl": 0, "exclud": 84, "exp": [0, 72], "exp_not": 0, "experi": 0, "extend": 51, "extract": 36, "faster": 59, "fdr": 11, "fdr_rang": 12, "file": [77, 81], "find_incongruent_clust": 13, "folder": 0, "forward": 98, "from": [1, 59, 84], "full": 72, "function": 28, "g": 84, "get": 1, "group_bilateral_data": 14, "guid": 0, "h5_to_tif": 32, "help": 0, "helper": 28, "hemi_to_lr_avg": 85, "hierarchi": 23, "high": 1, "i": [1, 35, 36, 58, 59, 77], "if_outli": 87, "ilastik": 0, "ilastik_pixel_classif": 73, "imag": [0, 1, 72, 84], "image_io": [32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44], "image_tool": [45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58], "img_avg": 0, "img_io": 28, "img_to_npi": 33, "img_tool": 29, "immunofluoresc": 72, "index": 15, "indic": 1, "info": 0, "instal": 2, "intens": [58, 84], "invers": 98, "io_img": 34, "io_nii": 35, "legend": 16, "letter": 0, "light": 1, "like": 0, "linux": 2, "list": 0, "log": 0, "main": [1, 28], "make": 0, "mask": [84, 94], "mask_dir": 72, "max": 52, "mean": 84, "metadata": 36, "microglia": 84, "min": 58, "mirror": 86, "modul": [3, 4, 5, 6, 7, 8, 9, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 25, 26, 27, 28, 29, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 44, 45, 46, 48, 49, 50, 51, 52, 53, 54, 55, 57, 58, 59, 60, 61, 62, 63, 65, 66, 67, 68, 69, 71, 72, 73, 75, 76, 77, 78, 79, 80, 81, 83, 84, 85, 86, 87, 88, 91, 92, 93, 94, 95, 96, 98], "more": 0, "multipl": 0, "name": [0, 76, 77], "nativ": 59, "need": 35, "nii_hd": 37, "nii_info": 38, "nii_to_tif": 39, "nii_to_zarr": 40, "non": 58, "note": 0, "number": 58, "open": 0, "option": 0, "org_data": 17, "orient": 0, "other": [87, 88, 89], "out": 84, "overview": 0, "packag": [10, 24, 30, 43, 47, 56, 64, 70, 74, 75, 82, 89, 90, 97], "pad": 53, "path": [0, 72], "prep": 72, "prepend": 77, "prepend_condit": 80, "present": 58, "preserv": 84, "print": [58, 76], "prism": 18, "project": 0, "python": [65, 96], "r_to_p": 88, "raw": 0, "rb": 54, "recursively_mirror_rev_cluster_indic": 19, "reg": [0, 66], "reg_check": [0, 67], "reg_check_brain_mask": 68, "reg_prep": [0, 69, 72], "region": 0, "region_stat": [59, 60, 61, 62, 63, 64], "regist": [65, 66, 67, 68, 69, 70], "registr": 0, "relabel_nii": 46, "renam": [62, 81], "reorder": 62, "reorient_nii": 41, "replac": 84, "repres": 84, "resolut": [1, 72], "rstat": [0, 59], "rstats_mean_if": 60, "rstats_mean_if_in_segmented_voxel": 61, "rstats_mean_if_summari": 62, "rstats_summari": [0, 63], "run": [0, 4], "sampl": [0, 77, 83], "sample01": 0, "sample02": 0, "sample_kei": 0, "save": 59, "scale": 35, "score": [35, 94], "script": 0, "seg_brain_mask": [0, 72], "seg_copy_tif": 0, "seg_ilastik": [0, 72], "segment": [0, 71, 72, 73, 74, 84], "set": [0, 2], "sh": 0, "sheet": 1, "shell": 0, "side": 94, "signal": 84, "size": [0, 58], "sort": 23, "sourc": 0, "space": [59, 94, 98], "spatial_averag": 55, "specif": 94, "specifi": 72, "stack": 0, "start": 1, "stat": [0, 20], "stats_tabl": 21, "step": 0, "stitch": 0, "structur": 0, "subpackag": 75, "subsystem": 2, "subtract": 0, "sunburst": 22, "support": 1, "syntax": 0, "t": [20, 62], "tabl": 23, "test": [20, 62], "tif": 0, "tif_to_tif": 42, "tissu": [94, 98], "to_atla": 95, "to_n": 96, "todo": [0, 2], "toggl": 83, "toggle_sampl": 83, "train": 0, "transpose_ax": 57, "tukei": [20, 62], "txt": 0, "typic": 0, "u": 1, "un": 1, "unique_intens": 58, "unravel": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98], "unravel_command": 76, "up": [0, 2], "us": 1, "usag": [3, 4, 5, 6, 7, 9, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 44, 45, 46, 48, 49, 50, 52, 53, 54, 55, 57, 58, 59, 60, 61, 62, 63, 65, 66, 67, 68, 69, 71, 72, 73, 76, 77, 78, 79, 80, 81, 83, 84, 85, 86, 87, 88, 91, 93, 94, 95, 96, 98], "util": [31, 77, 78, 79, 80, 81, 82, 83], "utils_agg_fil": 0, "utils_clean_tif": 0, "utils_prepend": 0, "valid": [0, 1], "vari": 0, "variabl": 0, "visual": 1, "volum": 23, "voxel": [0, 58, 84], "voxel_stat": [84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94], "vstat": [0, 91], "vstats_prep": [0, 92], "vstats_whole_to_avg": 0, "vstats_z_scor": 0, "w": [62, 94], "wa": 58, "warp": [94, 95, 96, 97, 98], "warp_to_n": 59, "welcom": 1, "were": 72, "when": [36, 77], "where": 84, "which": 58, "whole_to_lr_avg": 93, "window": 2, "wirefram": 48, "wise": 0, "workflow": 0, "wsl": 2, "x": 0, "y": 0, "z": [0, 35, 94], "z_score": 94, "zarr_to_nii": 44, "zero": [58, 84], "zshrc": 2}})
\ No newline at end of file
diff --git a/unravel/docs/_build/html/unravel/cluster_stats/cluster_summary.html b/unravel/docs/_build/html/unravel/cluster_stats/cluster_summary.html
index 87964026..9271273c 100644
--- a/unravel/docs/_build/html/unravel/cluster_stats/cluster_summary.html
+++ b/unravel/docs/_build/html/unravel/cluster_stats/cluster_summary.html
@@ -492,14 +492,28 @@
 

 
Usage if running directly after cluster_validation:#

 

-
cluster_summary -c <path/config.ini> -e <exp dir paths> -cvd ‘*’ -vd <path/vstats_dir> -sk <path/sample_key.csv> –groups <group1> <group2> -v

+
cluster_summary -c <path/config.ini> -e <exp dir paths> -cvd ‘psilocybin_v_saline_tstat1_q<asterisk>’ -vd <path/vstats_dir> -sk <path/sample_key.csv> –groups <group1> <group2> -hg <higher_group> -v

 

+

+
Note

+
    
+
  • The current working directory should not have other directories when running this script for the first time. Directories from cluster_org_data are ok though.
    • 
+

+

 

 

 
Usage if running after cluster_validation and cluster_org_data:#

 

-
cluster_summary -c <path/config.ini> -sk <path/sample_key.csv> –groups <group1> <group2> -v

+
cluster_summary -c <path/config.ini> -sk <path/sample_key.csv> –groups <group1> <group2> -hg <higher_group> -v

 

+

+
Note

+
    
+
  • For the second usage, the -e, -cvd, and -vd arguments are not needed because the data is already in the working directory.
    • 
+
  • Only process one comparison at a time. If you have multiple comparisons, run this script separately for each comparison in separate directories.
    • 
+
  • Then aggregate the results as needed (e.g. to make a legend with all relevant abbeviations, copy the .xlsx files to a central location and run cluster_legend).
    • 
+

+

 
The current working directory should not have other directories when running this script for the first time. Directories from cluster_org_data are ok though.

 

 
Runs commands in this order:
    
@@ -519,6 +533,8 @@ 
    Usage if running after 
 

 

+
If you need to rerun this script, delete the following directories and files in the current working directory:
+find . -name _valid_clusters -exec rm -rf {} ; -o -name cluster_validation_summary_t-test.csv -exec rm -f {} ; -o -name cluster_validation_summary_tukey.csv -exec rm -f {} ; -o -name 3D_brains -exec rm -rf {} ; -o -name valid_clusters_tables_and_legend -exec rm -rf {} ; -o -name _valid_clusters_stats -exec rm -rf {} ;

 

 

 

diff --git a/unravel/docs/_build/html/unravel/cluster_stats/stats.html b/unravel/docs/_build/html/unravel/cluster_stats/stats.html
index cb152b18..f173e759 100644
--- a/unravel/docs/_build/html/unravel/cluster_stats/stats.html
+++ b/unravel/docs/_build/html/unravel/cluster_stats/stats.html
@@ -492,17 +492,25 @@
 

 
T-test usage:#

 

-
cluster_stats –groups <group1> <group2>

+
cluster_stats –groups <group1> <group2> -hg <group1|group2>

 

 

 

 
Tukey’s test usage:#

 

-
cluster_stats –groups <group1> <group2> <group3> <group4> …

+
cluster_stats –groups <group1> <group2> <group3> <group4> … -hg <group1|group2>

 

+

+
Note

+
    
+
  • Organize data in directories for each comparison (e.g., psilocybin > saline, etc.)
    • 
+
  • This script will loop through all directories in the current working dir and process the data in each subdir.
    • 
+
  • Each subdir should contain .csv files with the density data for each cluster.
    • 
+
  • The first 2 groups reflect the main comparison for validation rates.
    • 
+
  • Clusters are not considered valid if the effect direction does not match the expected direction.
    • 
+

+

 

-
Input subdirs:
<asterisk>

-

 
Input files:
<asterisk>_density_data.csv from cluster_validation (e.g., in each subdir named after the rev_cluster_index.nii.gz file)

 

 
CSV naming conventions: