About

This depository contains scripts to re-do analyses and figures for Janusova et al. paper:

ABIN1 is a negative regulator of effector functions in cytotoxic T cells

Link: Here.

Data Accession: GSE245397

The files Paper_I1_cluster.csv, Paper_I2_cluster.csv, Paper_I3_cluster.csv and Paper_I6_cluster.csv contain lists of genes that were obtained from paper of Zhao et al. (2006).

Running these scripts

1. Clone this project. You'll end up with ABIN_KO_project directory.

2. Download file Mus_musculus.GRCm39.106.gtf from Ensembl in ABIN_KO_project directory. The file can be obtained here.

3. Create Fastqs directory in ABIN_KO_project, go in it (cd ABIN_KO_project) and download all .fastq files from GSE245397 accession number to it.

4. In ABIN_KO_project, create indices for STAR 2.7.10a aligner form GRCm39 v106 mouse assembly (Ensembl). Files needed can be downloaded here (navigate to gtf and fasta directories and download files mendtioned in command). The command to generate indices stored in directory GRCm39 is: STAR --runThreadN 20 --runMode genomeGenerate --genomeDir GRCm39 v106 --genomeFastaFiles Mus_musculus.GRCm39.dna.primary_assembly.fa --sjdbGTFfile Mus_musculus.GRCm39.106.gtf

5. Return to ABIN_KO_project directory (cd ..) and successively run following files. This will merge fastq files from the same samples and then align them :

• • exp01_merge_fastq_QC.sh
• • exp01_run_STAR.sh
• • exp02_merge_fastq_QC.sh
• • exp02_run_STAR.sh

6. The above should create bamfiles (directories Bamfiles1 and Bamfiles2) needed for analyses. The analyses are contained in files exp1_RNAseq.Rmd, exp2_RNAseq.Rmd, exp1_exp2_combined_analysis.Rmd and GSEA_NFkB_analysis_finalized.Rmd. These analyses need to be run in this order, ideally in RStudio or another program allowing exectuion of Rmarkdown files.

Now you should have files with complete analyses. Notably, tehre should be directories Figures (including subdirectory NFkB_Figures_Finalized), Rds_data, Tables and GSEA_tables that respectively contain figures, rds files with DESeq (result) objects, count tables and list of genes used for GSEA.