Gene Set Analysis: Challenges, Opportunities, and Future Research.

gene expression gene set analysis gene set database gene set enrichment sensitivity specificity

Journal

Frontiers in genetics
ISSN: 1664-8021
Titre abrégé: Front Genet
Pays: Switzerland
ID NLM: 101560621

Informations de publication

Date de publication:
2020
Historique:
received: 01 02 2020
accepted: 29 05 2020
entrez: 23 7 2020
pubmed: 23 7 2020
medline: 23 7 2020
Statut: epublish

Résumé

Gene set analysis methods are widely used to provide insight into high-throughput gene expression data. There are many gene set analysis methods available. These methods rely on various assumptions and have different requirements, strengths and weaknesses. In this paper, we classify gene set analysis methods based on their components, describe the underlying requirements and assumptions for each class, and provide directions for future research in developing and evaluating gene set analysis methods.

Identifiants

pubmed: 32695141
doi: 10.3389/fgene.2020.00654
pmc: PMC7339292
doi:

Types de publication

Journal Article Review

Langues

eng

Pagination

654

Informations de copyright

Copyright © 2020 Maleki, Ovens, Hogan and Kusalik.

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Auteurs

Farhad Maleki (F)

Department of Computer Science, University of Saskatchewan, Saskatoon, SK, Canada.

Katie Ovens (K)

Department of Computer Science, University of Saskatchewan, Saskatoon, SK, Canada.

Daniel J Hogan (DJ)

Department of Computer Science, University of Saskatchewan, Saskatoon, SK, Canada.

Anthony J Kusalik (AJ)

Department of Computer Science, University of Saskatchewan, Saskatoon, SK, Canada.

Classifications MeSH