Reliably determining which genes have a high posterior probability of differential expression: A microarray application of decision-theoretic multiple testing

Simple item page
dc.creatorBickel, David R.
dc.date2004-02-29
dc.date.accessioned2026-07-07T05:58:15Z
dc.date.available2026-07-07T05:58:15Z
dc.descriptionMicroarray data are often used to determine which genes are differentially expressed between groups, for example, between treatment and control groups. There are methods of determining which genes have a high probability of differential expression, but those methods depend on the estimation of probability densities. Theoretical results have shown such estimation to be unreliable when high-probability genes are identified. The genes that are probably differentially expressed can be found using decision theory instead of density estimation. Simulations show that the proposed decision-theoretic method is much more reliable than a density-estimation method. The proposed method is used to determine which genes to consider differentially expressed between patients with different types of cancer. The proposed method determines which genes have a high probability of differential expression. It can be applied to data sets that have replicate microarrays in each of two or more groups of patients or experiments.
dc.descriptionSubmitted for publication on 8/14/03
dc.identifierhttps://arxiv.org/abs/q-bio/0402048
dc.identifierhttp://arxiv.org/abs/q-bio/0402048
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/88292
dc.subjectQuantitative Methods
dc.subjectMolecular Networks
dc.subject62-07; 62P10
dc.titleReliably determining which genes have a high posterior probability of differential expression: A microarray application of decision-theoretic multiple testing
dc.typetext

Files

Collections

arXiv