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Dependencies

Reads were aligned to reference (GRCh38) with ‘STAR’ (v2.7.2b).

Gene counts were quantified with ‘FeatureCounts’ (v1.6.4).

Differential gene expression analysis was performed using the R package ‘DEseq2’(v1.26).

GSEA statistical analysis was carried out with the R package ‘fgsea’ (v1.14.0).

Updates:

12/08/2020: Added handling of short read alignment 03/02/2021: Added STAR gene counts 06/29/2021: Clarified documentation in a number of places 01/25/2022: Writing stderr and stdout to job folders

In this folder

design4expression.py -> job_expression.pl (expression.pl) -> summarize4expression.py -> DE.r


File: example.sh

Description: This shell script is an example job submission script to be used by job_expression.pl


File: design4expression.py

Description: This python3 script take samples from manifest file, and create two design files, one for job_expression.pl, another for summarize4expression.py


File: job_expression.pl

Description: This perl script is a wrapper around expression.pl for easy submission of the expression analysis jobs


File: expression.pl

Description: This perl script executes QC, alignment, and counting for raw RNA-seq data


File: summarize4expression.py

Description: This python3 script examines the output from expression.pl for all analyzed samples, and summarizes the expression data into a matrix table


File: DE.r

Description: This R script takes the output of summarize4expression.py and performs regular RNA differential analyses


Folder: script

Description: This folder stores dependency scripts for the main scripts


Folder: example_data

Description: This folder stores example input data for the pipeline


Folder: results

Description: This folder stores the example output of the pipeline

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  • Perl 14.0%
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