I wrote a command line Rscript to perform differential expression analysis:
The script uses the R packages DESeq2, edgeR and limma-voom. It's available on github. There is still room for improvement, so if you would be interested in contributing I'd definitely welcome that.
- Performs counting using featureCounts
- Allows specification of covariates
- Rigorous checking of input data
- Creates various plots
- Creates detailed tables and lists of differentially expressed genes
DEA.R < sample info file > < annotation.gtf >
- sampleInfoFile: file specifying samples with additional covariates
- annotation.gtf An annotation file in gtf format matching the reference genome used for alignment
More information can be found in the README on github
The script performs a few sanity checks on input data and then executes differential expression analysis with DESeq2, edgeR and limma-voom. The results are written to tab delimited files and the script saves all potential useful plots in image files.
2017-05-20: major update in code and usage, added readme
2017-05-27: minor update in code and usage