rnaseq

RNAseq

Purpose

The purpose of the RNA-seq pipeline is to map short-reads (Illumina) transcripts onto reference Staph aureus genomes, count transcripts across the different treatments. The data is processed using DESeq2 to identify differentially expressed genes between treatments.

Cyberinfrastructure & Implementation

The RNA sequence processing was done using HTCondor on CHTC using submit and executable files available under ./scripts. Apptainer definition files are available under ./recipes. After the data was processed in the form of a gene count matrix, the data was exported and analysed using R and Rstudio using the code under ./Rcode.

Workflow steps

CHTC

1. Mapping reads to reference genomes
2. Count transcripts mapping to gene features
3. Use mmseqs2 to find protein similarity between the two reference genomes.

R

1. Perform DEseq2 analysis on both genomes
2. Combine and merge results to compare up-regulated and down-regulated genomes between the two genomes.

Repository files

This repository contains 2 folders: recipes and scripts. The recipes folder contains the Apptainer definition files needed to create the Apptainer sif files. The scripts folder contains the HTcondor .sh and .sub files.

Input folder set-up

Expected output directory structure

Building containers

To build the software containers, you will need to start an interactive job, build the container, test it, and move it to a location accessible by the working nodes (e.g. staging, not home). For detailed instructions, visit https://github.com/UW-Madison-Bacteriology-Bioinformatics/chtc-containers.

brief instructions:

cd recipes
nano build.sub
# change the file listed in the transfer_input_files line
condor_submit -i build.sub
# replace "container" with the name of your choice
apptainer build container.sif container.def
apptainer shell -e container.sif
# test container by typing the -h --help command.
exit
mv container.sif /staging/netid/apptainer/.
exit
cd ..

Run code

condor_submit 01_mapping.sub
# wait for job to complete
condor_submit 02_featureCount.sub
# wait for job to complete
etc. 

Next steps

This workflow will create transcripts count files for each sample. I recommend using Globus.org to transfer files to your ResearchDrive or to your personal endpoint. For instructions, please visit: https://chtc.cs.wisc.edu/uw-research-computing/globus

Importing to R / Rstudio for analysis with DESeq2

An Rscript is available at ./Rcode showing how the data was processed for the paper.

References

This pipeline uses the following tools:

• Bowtie2 v.2.5.4: https://github.com/BenLangmead/bowtie2
• FeatureCount v.2.0.8 : https://subread.sourceforge.net/featureCounts.html
• R v.4.4.0 : https://cran.r-project.org/bin/macosx/base/
• DESeq v.1.44.0: https://bioconductor.org/packages/release/bioc/html/DESeq2.html
• Tidyverse 2.0.0: https://www.tidyverse.org/
• EnhancedVolcanoPlots (version 1.22.0): https://github.com/kevinblighe/EnhancedVolcano