Multiple testing and its applications to microarrays.
The large-scale multiple testing problems resulting from the measurement of thousands of genes in microarray experiments have received increasing interest during the past several years. This article describes some commonly used criteria for controlling false positive errors, including familywise err...
| Publicado en: | Statistical Methods in Medical Research Vol. 18; no. 6; pp. 543 - 564 |
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| Autores principales: | , , , , , |
| Formato: | research Journal Article |
| Publicado: |
Sage Publications Inc.
Dec2009
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=105277340&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 105277340 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 09622802 31F jtl: Statistical Methods in Medical Research issn: 09622802 maglogo: Y pubinfo: dt: Dec2009 vid: 18 iid: 6 pid: 344 pub: Sage Publications Inc. place: Thousand Oaks, California artinfo: ui: 105277340 NLM20048384 2010519331 10.1177/0962280209351899 NLM20048384 PMC4131454 105277340 ppf: 543 ppct: 21 formats: tig: atl: Multiple testing and its applications to microarrays. aug: au: Ge Y Sealfon SC Speed TP Ge, Yongchao Sealfon, Stuart C Speed, Terence P affil: Department of Neurology and Center for Translational Systems Biology, Mount Sinai School of Medicine, New York, NY 10029, USA sug: subj: Algorithms False Positive Results Biochips Data Analysis, Statistical Genetic Techniques Methods Models, Statistical ab: The large-scale multiple testing problems resulting from the measurement of thousands of genes in microarray experiments have received increasing interest during the past several years. This article describes some commonly used criteria for controlling false positive errors, including familywise error rates, false discovery rates and false discovery proportion rates. Various statistical methods controlling these error rates are described. The advantages and disadvantages of these methods are discussed. These methods are applied to gene expression data from two microarray studies and the properties of these multiple testing procedures are compared. pubtype: Academic Journal doctype: research Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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