Gene Sets from Community Contributors

This page contains references to gene sets and collections from community contributors. These are not part of MSigDB but may be useful for certain analyses. The descriptions and all other information given below are courtesy of the contributors. Note that these contributions are under copyright and license terms as specified by the authors rather than the MSigDB license terms.

If you have gene sets to contribute that might benefit others, feel free to contact us at

SysMyo Muscle Gene Sets

SysMyo has contributed a collection of Muscle Gene Sets:

"More than ten thousand samples of muscle transcriptomic data have been uploaded to the public Gene Expression Omnibus in the past ten years, representing many millions of dollars of research expenditure and incalculable hours of research effort. These data ought to serve as a massive reference set for ongoing and future studies of neuromuscular disorders. One way to distil the data and render them more accessible to bench researchers is to extract from each study lists of genes ("gene sets") that were differentially expressed. With careful curation, each transcriptomic dataset may yield multiple comparisons, not only relating to the primary focus of that study, such as a pathology or an experimental treatment, but also more general comparisons not necessarily envisaged by the study's authors, but relating to factors such as age, sex, and muscle group."

See their website for more information.


Nicolaas Van Renne et al. have contributed PorSignDB:

"The Porcine Signature Database (PorSignDB) is a collection of annotated gene sets for use with GSEA software. These gene sets were mostly derived from in vivo derived transcriptomic data, and describe a wide spectrum of (patho)physiological states of different tissue types. Only a minority of gene sets describe cell culture systems. Although the original data stems from pigs (Sus Scrofa), gene identifiers were adapted to human homologs in order to fit into the MSigDB collection and facilitate its application to data from any mammalian species..."

See their website for more information.


Megan Hastings Hagenauer et al. have contributed the BrainCortex_CellTypeSpecificGenes gene sets, described in (preprint). From the Abstract:

"Psychiatric illness is unlikely to arise from pathology occurring uniformly across all cell types in affected brain regions. Despite this, transcriptomic analyses of the human brain have typically been conducted using macro-dissected tissue due to the difficulty of performing single-cell type analyses with donated post-mortem brains. To address this issue statistically, we compiled a database of several thousand transcripts that were specifically-enriched in one of 10 primary cortical cell types, as identified in previous publications... "

See their website for more information.