BRC_Organoid_Joana

Transcriptomic changes in organoid small intestinal epithelial cells upon interaction with lymphocytes

DB ID Project.id=6, Data.id=11

Scripts

1. header.R

• header file with global variables and settings

2. 01_createDbEntry.R

• create database entries for the samples

3. 02_fastQC.R

• QA checks on the FASTQ files using the class CFastqQuality

4. 03_trimmomatic_array_job.R

• writes a batch array job for hpc to use trimmomatic for read trimming

5. 04_fastQC_trimmed.R

• QA checks on the trimmed FASTQ files using the class CFastqQuality

6. 05_hisat2_array_job.R

• create a parameter file and shell script to run array job on hpc

7. 06_samtools_array_job.R

• create a parameter file and shell script to run array job on hpc

8. 07_bam_files_qa.R

• quality checks on the bam files

9. 08_counts_from_bams.R

• generate count tables for transcripts from bam files

10. 09_clustering_counts_matrix.R

• cluster the samples based on count table

11. 10_de_analysis.R

• DE analysis for the count data using DESeq2

12. 11_de_analysis_MCMC.R

• DE analysis for the count data using a Bayesian approach by writing a log posterior function and optimizing the function using LearnBayes::laplace. The second half of the script has the option to use Stan to generate MCMC samples from the posterior.
• nb_glm.stan Stan script, similar to the log posterior function. Can be used for genes that do not converge using optimizer.