R package for carrying out Network-based Gene Set Analysis
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How to install?


Reference manual is available on CRAN. More details about the method implemented can be found here.

Why should someone use netgsa?

  • NetGSA incorporates the rich network information curated in public databases (e.g. KEGG) or learned from high-throughput sequencing data, thereby gaining power in pathway enrichment analysis.

How does it compare to other existing solutions?

  • NetGSA tests the self-contained null and compares the set of genes in a given pathway with itself.
  • NetGSA allows users to complement potentially misspecified information in public databases with high-throughput sequencing data.
  • In contrast to existing pathway topology based methods, NetGSA can be particularly powerful in learning from e.g. metabolomic data where the pathway size is relatively small and available metabolic network information is sparse.


  • Current implementation may be slow for large data sets. We are working on a new version which will be released soon.