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Author

Nam, Dougu
Statistical Genomics Lab
Research Interests
  • Gene network, pathway analysis, biclustering, disease classification

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Effect of the absolute statistic on gene-sampling gene-set analysis methods

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Title
Effect of the absolute statistic on gene-sampling gene-set analysis methods
Author
Nam, Dougu
Keywords
Gene-set analysis, absolute statistic, microarray analysis, false-positive control, genome-wide association study
Issue Date
201706
Publisher
SAGE PUBLICATIONS LTD
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.
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DOI
http://dx.doi.org/10.1177/0962280215574014
ISSN
0962-2802
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