Molecular signatures database (MSigDB) 3.0
Open accessAbstract
MOTIVATION: Well-annotated gene sets representing the universe of the biological processes are critical for meaningful and insightful interpretation of large-scale genomic data. The Molecular Signatures Database (MSigDB) is one of the most widely used repositories of such sets. RESULTS: We report the availability of a new version of the database, MSigDB 3.0, with over 6700 gene sets, a complete revision of the collection of canonical pathways and experimental signatures from publications, enhanced annotations and upgrades to the web site. AVAILABILITY AND IMPLEMENTATION: MSigDB is freely available for non-commercial use at http://www.broadinstitute.org/msigdb.
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Transcription factor activities can be estimated using enrichment of their downstream targets.
“Transcription factor activities can be estimated using enrichment of their downstream targets26,27.”
From Positive selection of somatically mutated clones identifies adaptive pathways in metabolic liver disease (2023) · cites this paper as [27]
The Introduction says MSigDB provides gene sets for enrichment analysis, and Results §2 identifies a collection of transcription-factor target gene sets. Together, these support enriching target genes, but the paper does not say that the enrichment estimates transcription-factor activity. Page numbers are unavailable in our copy. (LLM, conf=0.82)
Experimental — accuracy not yet measuredGene location ground truth is annotated according to Ensembl Release 110, as collected in the MSigDB C1 gene set.
“Ground truth is annotated according to Ensembl Release 110 [13], as collected in the MSigDB [29] C1 gene set (c1.all.v2023.2.Hs.symbols.gmt).”
From LAB-Bench: Measuring Capabilities of Language Models for Biology Research (2024) · cites this paper as [29]
Transcription factor gene expression levels do not always reflect their functional importance.
“Since transcription factor gene expression levels do not always reflect their functional importance, we chose those with the highest or lowest activities based on the induction or suppression of their downstream targets (See methods for details)26,27.”
From Positive selection of somatically mutated clones identifies adaptive pathways in metabolic liver disease (2023) · cites this paper as [27]
The Introduction discusses gene-expression signatures, and Results section 2 describes gene sets of transcription-factor targets, but neither says whether a transcription factor’s expression reflects its functional importance. Searches for the quoted claim and for activity inferred from downstream targets found no passage addressing that comparison. (LLM, conf=0.72)
Experimental — accuracy not yet measuredThe limma authors maintain mouse and human versions of the Molecular Signatures Database collections in R binary format that can be conveniently used with camera, mroast or romer.
“The limma authors maintain mouse and human versions of the Molecular Signatures Database collections (64) in R binary format that can be conveniently used with camera, mroast or romer”
From limma powers differential expression analyses for RNA-sequencing and microarray studies (2015) · cites this paper as [64]
The OXTR/CD38 module is enriched in genesets reported in the Molecular Signatures Database associated with feeding behavior (p = 5.83 × 10−3), cognition (p = 7.44 × 10−3), and behavioral response to stimuli (p = 1.05 × 10−2).
“This OXTR/CD38 module was also enriched in genesets reported in the Molecular Signatures Database34 that are associated with several behavioral and cognitive state processes including feeding behavior (p = 5.83 × 10−3), cognition (p = 7.44 × 10−3), and behavioral response to stimuli (p = 1.05 × 10−2).”
From Oxytocin pathway gene networks in the human brain (2019) · cites this paper as [34]
Biological process labels are stored in databases such as MSigDB, the Gene Ontology, or the pathway databases KEGG and Reactome.
“Biological process labels are stored in databases such as MSigDB (Liberzon et al, 2011), the Gene Ontology (Ashburner et al, 2000; The Gene Ontology Consortium, 2017), or the pathway databases KEGG (Kanehisa et al, 2017) and Reactome (Fabregat et al, 2018).”
From Current best practices in single-cell RNA-seq analysis: a tutorial (2019) · cites this paper as Liberzon et al, 2011
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- Authors
- Liberzon, A., Subramanian, A., Pinchback, R., Thorvaldsdóttir, H., Tamayo, P., & Mesirov, J. P.
- Affiliations
- Broad Institute (US)
- Venue
- Bioinformatics
- Publisher
- Oxford University Press (OUP)
- Published
- 2011-05-05
- Volume
- 27
- Issue
- 12
- Pages
- 1739-1740
- ISSN
- 1367-4803 (ISSN-L)
- 1367-4811
- PMC
- PMC3106198
- OpenAlex
- W2010457001
- Cited by
- 7,111
- References
- 2
- Citations by year
- 2026: 675 · 2025: 1003 · 2024: 1086 · 2023: 942 · 2022: 825 · 2021: 774 · 2020: 602 · 2019: 374 · 2018: 203 · 2017: 151 · 2016: 141 · 2015: 117 · 2014: 102 · 2013: 64 · 2012: 38
- FWCI
- 27.81
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Bioinformatics (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- HighWire Press Open Archive (submittedVersion)
- Funders
- National Cancer Institute (R01CA121941)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Biomedical Text Mining and Ontologies
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
- Keywords
- MSigDB, gene sets, canonical pathways, experimental signatures, gene set annotation, biological process annotation, genomic data interpretation, molecular signatures
- MeSH terms
- Internet, Genomics, Databases, Genetic, Molecular Sequence Annotation
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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