Gene Set Enrichment Analysis with RNA-seq data

Question

[deepak18]

I have TCGA data for RNA expression for breast cancer samples (log2 normalised fpkm values) and I want to perform GSEA on it to look which gene sets are enriched in cancer samples vs normal samples. Which is the best platform to perform GSEA with RNA-seq software? Which will better, the software by Broad Institute (http://software.broadinstitute.org/gsea/index.jsp) or the R package fgsea (https://bioconductor.org/packages/release/bioc/html/fgsea.html)?

[Jean-Karim Heriche]

Define what you mean by 'better'. Without objective criteria, this ends up being a matter of personal preference.

[deepak18]

Actually I am facing problems with both. For analysis of RNA-seq data with the software we need to filter out low count measurements. What cut off should I put for this filter step and do I need to do some more pre-processing before I can go with the analysis?

[Jean-Karim Heriche]

You should update your question title to attract more knowledgeable people. Usually filtering is already done by the software/code used to infer DE (e.g. DESeq2).

[deepak18]

Thank you for the comments. I was able to perform GSEA using the software successfully without any pre-processing.

[Mahdiar Sadeghi]

Pre-processing and quality control of the data is necessary because of many reasons. Your results might change if you do it.

[Hamid Ghaedi]

See this post: Tutorial: Gene Set Enrichment Analysis, its a gene set enrichment analysis using fsgea package - a free implementation of the Broad’s GSEA software