Is there a library in Python for doing gene set enrichment analysis (GSEA, http://www.broadinstitute.org/gsea/index.jsp)? A library/tool that takes a foreground set of genes, a background set, a gene sets database like the one available from Broad and does the analysis without relying on microarray-specific items like probe IDs? All the tools I found are made for microarrays but I want to do this for rna-seq. If there's no library in Python, is there a command line tool that can do this again without relying on probe IDs?
4 answers
There's nothing about gene set analysis that is dependent on array probe Ids; once you have gene level expression measurements (ie. indexed by gene symbol or entrez gene id) you can use any of the existing tools (eg GSEA). Some of them do have features to convert from probesets to gene symbols, but you don't need to use that feature.
It's also pretty straightforward to roll your own simple enrichment analysis in python. A python library would be nice though; I have some code for this that I've been meaning to tidy up..
Maybe contrary to the spirit of your question, but there are many great tools for this available for R from Bioconductor. I can see advantages of a python native library, but it might be faster to call R from python.
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johnstantongeddes
The top two results for googling "GSEA python" were these libraries: pygsa and geseabase, and as Adrian already told you the analysis is independent of probeids. You will find the data format guides for GSEA and for pygsa library here: GSEA data format guide
What about 'GSEAPY: Gene Set Enrichment Analysis in Python'?
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Difference between gseapy and gsea
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Suggestion for enrichment analysis for small microarray set.
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GSEA RNASeq
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GSEA Pre-ranked for an Overlapped Gene Set
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*.rnk file preparation for GSEA analysis
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GSEA on preranked list with weighted enrichment statistic (exponent=1) in R
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pathway analysis tools and KEGG gene sets from MSigDB
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Assigning Go Identifiers To Gsea Msigdb Gene Sets
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Selection Of Background Gene Set In Enrichment Analysis
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Gene Set Enrichment Analysis For One Cell Type
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