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

Autor:	Maleki F; Department of Computer Science, University of Saskatchewan, Saskatoon, SK, Canada., Ovens K; Department of Computer Science, University of Saskatchewan, Saskatoon, SK, Canada., Hogan DJ; Department of Computer Science, University of Saskatchewan, Saskatoon, SK, Canada., Kusalik AJ; Department of Computer Science, University of Saskatchewan, Saskatoon, SK, Canada.
Jazyk:	angličtina
Zdroj:	Frontiers in genetics [Front Genet] 2020 Jun 30; Vol. 11, pp. 654. Date of Electronic Publication: 2020 Jun 30 (Print Publication: 2020).
DOI:	10.3389/fgene.2020.00654
Abstrakt:	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. (Copyright © 2020 Maleki, Ovens, Hogan and Kusalik.)
Databáze:	MEDLINE
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