OUTRIDER analysis

This is the accompanying analysis repository of the paper: OUTRIDER: A statistical method for detecting aberrantly expressed genes in RNA sequencing data

The paper can be found here. A full copy of the resulting files can be found on our webserver https://i12g-gagneurweb.in.tum.de/public/paper/OUTRIDER/.

This repository contains the full pipeline and code to reproduce the results published in the paper.

Project structure

This project is setup as a wBuild. This is an automatic build tool for R reports based on snakemake.

• The Scripts folder contains scripts which will be rendered as HTML reports
• The src folder contains additional helper functions and scripts
• The Output folder will contain all files produced in the analysis pipeline
  • Output/data has all raw RDS output files
  • Output/html contains the final HTML report
  • Output/paper_figures has all paper figures

Dependencies

This project depends on the python package wBuild and the R package OUTRIDER. The data will be downloaded automatically. Since the genotypes are not publicly shareable one has to apply for the data at dbGaP. We included a fake VCF to run the full pipeline. Please replace the path to the VCF files in the wbuild.yaml file to include the real enrichment data.

Repository setup

First download the repo and its dependencies:

git clone https://github.com/gagneurlab/OUTRIDER OUTRIDER
git clone https://github.com/gagneurlab/OUTRIDER-analysis OUTRIDER-analysis
cd OUTRIDER-analysis

and install wbuild using pip by running.

pip install wBuild
wBuild init

Since wBuild init will reset the current Snakefile, readme.md, and wbuild.yaml we have to revert them again with git.

git checkout Snakefile
git checkout wbuild.yaml
git checkout readme.md

To make sure all packages needed in the analysis are installed source the following file in R

Rscript ./src/r/install_dependencies.R

Run the full pipeline

To run the full pipeline, execute the following command with 10 cores in parallel:

snakemake -j 10

or to run it on the cluster with SLUM installed:

snakemake -k --restart-times 4 --cluster "sbatch -N 1 -n 10 --mem 30G" --jobs 16