| pubmed-article:15145810 | rdf:type | pubmed:Citation | lld:pubmed |
| pubmed-article:15145810 | lifeskim:mentions | umls-concept:C0026336 | lld:lifeskim |
| pubmed-article:15145810 | lifeskim:mentions | umls-concept:C0439962 | lld:lifeskim |
| pubmed-article:15145810 | lifeskim:mentions | umls-concept:C0205276 | lld:lifeskim |
| pubmed-article:15145810 | lifeskim:mentions | umls-concept:C1522053 | lld:lifeskim |
| pubmed-article:15145810 | lifeskim:mentions | umls-concept:C1880720 | lld:lifeskim |
| pubmed-article:15145810 | pubmed:issue | 16 | lld:pubmed |
| pubmed-article:15145810 | pubmed:dateCreated | 2004-11-1 | lld:pubmed |
| pubmed-article:15145810 | pubmed:abstractText | Statistical methods based on controlling the false discovery rate (FDR) or positive false discovery rate (pFDR) are now well established in identifying differentially expressed genes in DNA microarray. Several authors have recently raised the important issue that FDR or pFDR may give misleading inference when specific genes are of interest because they average the genes under consideration with genes that show stronger evidence for differential expression. The paper proposes a flexible and robust mixture model for estimating the local FDR which quantifies how plausible each specific gene expresses differentially. | lld:pubmed |
| pubmed-article:15145810 | pubmed:grant | http://linkedlifedata.com/r... | lld:pubmed |
| pubmed-article:15145810 | pubmed:language | eng | lld:pubmed |
| pubmed-article:15145810 | pubmed:journal | http://linkedlifedata.com/r... | lld:pubmed |
| pubmed-article:15145810 | pubmed:citationSubset | IM | lld:pubmed |
| pubmed-article:15145810 | pubmed:status | MEDLINE | lld:pubmed |
| pubmed-article:15145810 | pubmed:month | Nov | lld:pubmed |
| pubmed-article:15145810 | pubmed:issn | 1367-4803 | lld:pubmed |
| pubmed-article:15145810 | pubmed:author | pubmed-author:LiaoJ GJG | lld:pubmed |
| pubmed-article:15145810 | pubmed:author | pubmed-author:ShihWeichung... | lld:pubmed |
| pubmed-article:15145810 | pubmed:author | pubmed-author:LinYongY | lld:pubmed |
| pubmed-article:15145810 | pubmed:author | pubmed-author:SelvanayagamZ... | lld:pubmed |
| pubmed-article:15145810 | pubmed:issnType | Print | lld:pubmed |
| pubmed-article:15145810 | pubmed:day | 1 | lld:pubmed |
| pubmed-article:15145810 | pubmed:volume | 20 | lld:pubmed |
| pubmed-article:15145810 | pubmed:owner | NLM | lld:pubmed |
| pubmed-article:15145810 | pubmed:authorsComplete | Y | lld:pubmed |
| pubmed-article:15145810 | pubmed:pagination | 2694-701 | lld:pubmed |
| pubmed-article:15145810 | pubmed:dateRevised | 2009-11-19 | lld:pubmed |
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| pubmed-article:15145810 | pubmed:year | 2004 | lld:pubmed |
| pubmed-article:15145810 | pubmed:articleTitle | A mixture model for estimating the local false discovery rate in DNA microarray analysis. | lld:pubmed |
| pubmed-article:15145810 | pubmed:affiliation | Biometrics Division, School of Public Health and The Cancer Institute of New Jersey, University of Medicine and Dentistry of New Jersey, 683 Hoes Lane West, Piscataway, NJ 08854, USA. liaojg@umdnj.edu | lld:pubmed |
| pubmed-article:15145810 | pubmed:publicationType | Journal Article | lld:pubmed |
| pubmed-article:15145810 | pubmed:publicationType | Clinical Trial | lld:pubmed |
| pubmed-article:15145810 | pubmed:publicationType | Comparative Study | lld:pubmed |
| pubmed-article:15145810 | pubmed:publicationType | Research Support, U.S. Gov't, P.H.S. | lld:pubmed |
| pubmed-article:15145810 | pubmed:publicationType | Controlled Clinical Trial | lld:pubmed |
| pubmed-article:15145810 | pubmed:publicationType | Validation Studies | lld:pubmed |
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