Question: Recommended approach: gene set analysis of small transcriptome experiments?
gravatar for Nick
4.7 years ago by
United Kingdom
Nick60 wrote:

We have RNA-seq data for a small experiment, which compares the transcriptome of a treated vs untreated cell line (3 biological replicates for each condition, 6 samples in total).

So far we have obtained lists of differentially expressed genes using DESeq. We want to perform gene set analysis to identify pathways which are dysregulated (enriched for differentially expressed genes). However, I have read (e.g. here) that many established gene set enrichment methods work by permuting sample labels to generate a null distribution.

Given our very small number of samples, this is presumably not an option. Are there gene set analysis methods specifically able to cope with such small sample sizes?

ADD COMMENTlink modified 4.7 years ago by Benn8.1k • written 4.7 years ago by Nick60
gravatar for Benn
4.7 years ago by
Benn8.1k wrote:

You can try goseq, it is meant for RNA-seq data and uses length-bias correction with a Wallenius distribution (as default).

ADD COMMENTlink written 4.7 years ago by Benn8.1k
Please log in to add an answer.


Use of this site constitutes acceptance of our User Agreement and Privacy Policy.
Powered by Biostar version 2.3.0
Traffic: 1804 users visited in the last hour