De-correlating expression in gene-set analysis.

Citation data:

Bioinformatics (Oxford, England), ISSN: 1367-4811, Vol: 26, Issue: 18, Page: i511-6

Publication Year:
2010
Usage 77
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Citations 13
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Repository URL:
http://scholarworks.unist.ac.kr/handle/201301/3140
PMID:
20823315
DOI:
10.1093/bioinformatics/btq380
PMCID:
PMC2935420
Author(s):
Nam, Dougu
Publisher(s):
Oxford University Press (OUP); OXFORD UNIV PRESS
Tags:
Mathematics; Biochemistry, Genetics and Molecular Biology; Computer Science; Medicine; ENRICHMENT ANALYSIS; PROFILES; PATHWAYS
article description
Group-wise pattern analysis of genes, known as gene-set analysis (GSA), addresses the differential expression pattern of biologically pre-defined gene sets. GSA exhibits high statistical power and has revealed many novel biological processes associated with specific phenotypes. In most cases, however, GSA relies on the invalid assumption that the members of each gene set are sampled independently, which increases false predictions.