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The Molecular Signatures Database Hallmark Gene Set Collection

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Liberzon, Arthur, Birger, Chet, Thorvaldsdóttir, Helga, Ghandi, Mahmoud, Mesirov, Jill P., Tamayo, Pablo·2015·Cell Systems

DOI 10.1016/j.cels.2015.12.004PMC PMC4707969

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Abstract

The Molecular Signatures Database (MSigDB) is one of the most widely used and comprehensive databases of gene sets for performing gene set enrichment analysis. Since its creation, MSigDB has grown beyond its roots in metabolic disease and cancer to include >10,000 gene sets. These better represent a wider range of biological processes and diseases, but the utility of the database is reduced by increased redundancy across, and heterogeneity within, gene sets. To address this challenge, here we use a combination of automated approaches and expert curation to develop a collection of "hallmark" gene sets as part of MSigDB. Each hallmark in this collection consists of a "refined" gene set, derived from multiple "founder" sets, that conveys a specific biological state or process and displays coherent expression. The hallmarks effectively summarize most of the relevant information of the original founder sets and, by reducing both variation and redundancy, provide more refined and concise inputs for gene set enrichment analysis.

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Influential
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“…analyses: (1) To identify smaller, focused pathways associated with drug sensitivity or resistance, we performed GSEA analysis on genes ranked by ρ phenotype and defined minimum and maximum thresholds for gene set size when running the `gsea` function (`min_size = 15` and `max_size = 150`) 31,73 .”
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Authors: Liberzon, A., Birger, C., Thorvaldsdóttir, H., Ghandi, M., Mesirov, J. P., & Tamayo, P.
Affiliations: Broad Institute (US)
Corresponding author: Mesirov, Jill P.
Tamayo, Pablo
ORCID: Ghandi, Mahmoud
Mesirov, Jill P.
Tamayo, Pablo
Venue: Cell Systems
Publisher: Elsevier BV
Published: 2015-12
Volume: 1
Issue: 6
Pages: 417-425
ISSN: 2405-4712 (ISSN-L)
DOI: 10.1016/j.cels.2015.12.004
PMC: PMC4707969
OpenAlex: W2214074259
Cited by: 13,807
References: 37
Citations by year: 2026: 2174 · 2025: 2294 · 2024: 2415 · 2023: 1982 · 2022: 1708 · 2021: 1298 · 2020: 926 · 2019: 534 · 2018: 270 · 2017: 154 · 2016: 44
FWCI: 68.21
Type: journal article
Language: en
Open access: bronze
doi.org
Licence: www.elsevier.com/tdm/userlicense/1.0/ (tdm)
www.elsevier.com/open-access/userlicense/1.0/ (vor, 388 d)
Locations: Cell Systems (publishedVersion)
PubMed (publishedVersion)
Europe PMC (PubMed Central) (acceptedVersion)
PubMed Central (acceptedVersion)
eScholarship (California Digital Library) (submittedVersion)
Funders: National Institutes of Health
National Cancer Institute (R01CA154480, U54CA112962, R01CA121941)
National Institute of General Medical Sciences (R01GM074024)
Topics: Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
Health Sciences › Medicine › Health Informatics › Biomedical Text Mining and Ontologies
Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
Keywords: Hallmark gene sets, gene set enrichment analysis, biological processes, cancer hallmarks

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