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Nam, Dougu
Bioinformatics Lab.
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Effect of the absolute statistic on gene-sampling gene-set analysis methods

Author(s)
Nam, Dougu
Issued Date
2017-06
DOI
10.1177/0962280215574014
URI
https://scholarworks.unist.ac.kr/handle/201301/18147
Fulltext
http://smm.sagepub.com/content/early/2015/02/27/0962280215574014.abstract
Citation
STATISTICAL METHODS IN MEDICAL RESEARCH, v.26, no.3, pp.1248 - 1260
Abstract
Gene-set enrichment analysis and its modified versions have commonly been used for identifying altered functions or pathways in disease from microarray data. In particular, the simple gene-sampling gene-set analysis methods have been heavily used for datasets with only a few sample replicates. The biggest problem with this approach is the highly inflated false-positive rate. In this paper, the effect of absolute gene statistic on gene-sampling gene-set analysis methods is systematically investigated. Thus far, the absolute gene statistic has merely been regarded as a supplementary method for capturing the bidirectional changes in each gene set. Here, it is shown that incorporating the absolute gene statistic in gene-sampling gene-set analysis substantially reduces the false-positive rate and improves the overall discriminatory ability. Its effect was investigated by power, false-positive rate, and receiver operating curve for a number of simulated and real datasets. The performances of gene-set analysis methods in one-tailed (genome-wide association study) and two-tailed (gene expression data) tests were also compared and discussed.
Publisher
SAGE PUBLICATIONS LTD
ISSN
0962-2802
Keyword (Author)
Gene-set analysisabsolute statisticmicroarray analysisfalse-positive controlgenome-wide association study
Keyword
ENRICHMENT ANALYSISMICROARRAY DATAEXPRESSION DATAFRAMEWORKPATHWAYS

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