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DC Field | Value | Language |
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dc.citation.endPage | 1260 | - |
dc.citation.number | 3 | - |
dc.citation.startPage | 1248 | - |
dc.citation.title | STATISTICAL METHODS IN MEDICAL RESEARCH | - |
dc.citation.volume | 26 | - |
dc.contributor.author | Nam, Dougu | - |
dc.date.accessioned | 2023-12-21T22:12:56Z | - |
dc.date.available | 2023-12-21T22:12:56Z | - |
dc.date.created | 2016-01-12 | - |
dc.date.issued | 2017-06 | - |
dc.description.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. | - |
dc.identifier.bibliographicCitation | STATISTICAL METHODS IN MEDICAL RESEARCH, v.26, no.3, pp.1248 - 1260 | - |
dc.identifier.doi | 10.1177/0962280215574014 | - |
dc.identifier.issn | 0962-2802 | - |
dc.identifier.scopusid | 2-s2.0-85020752150 | - |
dc.identifier.uri | https://scholarworks.unist.ac.kr/handle/201301/18147 | - |
dc.identifier.url | http://smm.sagepub.com/content/early/2015/02/27/0962280215574014.abstract | - |
dc.identifier.wosid | 000403319000012 | - |
dc.language | 영어 | - |
dc.publisher | SAGE PUBLICATIONS LTD | - |
dc.title | Effect of the absolute statistic on gene-sampling gene-set analysis methods | - |
dc.type | Article | - |
dc.description.isOpenAccess | FALSE | - |
dc.relation.journalWebOfScienceCategory | Health Care Sciences & Services; Mathematical & Computational Biology; Medical Informatics; Statistics & Probability | - |
dc.relation.journalResearchArea | Health Care Sciences & Services; Mathematical & Computational Biology; Medical Informatics; Mathematics | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.subject.keywordAuthor | Gene-set analysis | - |
dc.subject.keywordAuthor | absolute statistic | - |
dc.subject.keywordAuthor | microarray analysis | - |
dc.subject.keywordAuthor | false-positive control | - |
dc.subject.keywordAuthor | genome-wide association study | - |
dc.subject.keywordPlus | ENRICHMENT ANALYSIS | - |
dc.subject.keywordPlus | MICROARRAY DATA | - |
dc.subject.keywordPlus | EXPRESSION DATA | - |
dc.subject.keywordPlus | FRAMEWORK | - |
dc.subject.keywordPlus | PATHWAYS | - |
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