Today’s goal:
In this session, we will use the feature counts table generated by the star_salmon job to run a statistical analysis to identify differentially expressed genes.
Log into the HPC
ssh userID@lyra.qut.edu.au
To go to a shared directory for your project, for example: “kenna_team”. Type the following command and hit enter:
cd /work/kenna_team/
Go to the results of the previous Session 3:
cd jess/session3/
Changing the folder permission for other members in the group to access the ‘results’ and ‘work’ folders:
chmod -R g+rwX results chmod -R g+rwX work
Go to the folder with the feature counts generated by star_salmon:
cd run1_star_salmon/results/star_salmon
Various ‘salmon.merged.*’ files are generated for all the samples processed in the experiment. Let’s look for the file that contains the feature counts for genes:
head -25 salmon.merged.gene_counts.tsv
To browse the whole file type the following:
less salmon.merged.gene_counts.tsv
Copy the “salmon.merged.gene_counts.tsv” to your laptop and we will use it for statistical analysis using BioJupies (see below)
Differential gene expression analysis
Differential expression analysis using https://maayanlab.cloud/biojupies/analyze
From session 2, we will use the feature counts generated using the ‘star_salmon’ parameter setting. Either copy the relevant files (see below) to your laptop from the HPC or download the files below.
File | File name | File |
|---|---|---|
Gene feature counts | salmon_merged.gene_counts.tsv |
|
Transcript feature counts | salmon_merged.transcript_counts.tsv |
|
Reading: