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rdf:type |
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lifeskim:mentions |
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pubmed:issue |
2
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pubmed:dateCreated |
2010-3-23
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pubmed:abstractText |
Gene expression microarrays are powerful tools for global comparison and estimation of gene expression. Many microarray studies have demonstrated biologically plausible results with only a few arrays, leading to a misperception that a handful of hybridized arrays can always find something meaningful. From a statistical point of view, it is important to prospectively estimate required sample sizes prior to undertaking a microarray experiment. However, all sample size calculations need to directly or indirectly estimate the unknown distribution of the effect sizes of gene expression intensities. A parametric mixture model has been developed for relating the sample size directly to the false discovery rate (FDR), the most popular multiple-comparison control criteria. In this paper, we extend the parametric mixture model and propose a robust semiparametric Dirichlet process mixture model, where the parametric distribution of gene expressions is no longer specified. This analysis is performed in a Bayesian inference framework using Markov-chain Monte Carlo steps. The usefulness of the method is illustrated by simulations and a real murine lung study.
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pubmed:grant |
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pubmed:commentsCorrections |
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pubmed:language |
eng
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pubmed:journal |
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pubmed:citationSubset |
IM
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pubmed:status |
MEDLINE
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pubmed:month |
Mar
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pubmed:issn |
1520-5711
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pubmed:author |
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pubmed:issnType |
Electronic
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pubmed:volume |
20
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pubmed:owner |
NLM
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pubmed:authorsComplete |
Y
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pubmed:pagination |
267-80
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pubmed:dateRevised |
2011-10-28
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pubmed:meshHeading |
pubmed-meshheading:20309758-Animals,
pubmed-meshheading:20309758-Bayes Theorem,
pubmed-meshheading:20309758-Computer Simulation,
pubmed-meshheading:20309758-Data Interpretation, Statistical,
pubmed-meshheading:20309758-Disease Models, Animal,
pubmed-meshheading:20309758-Gene Expression Profiling,
pubmed-meshheading:20309758-Gene Expression Regulation,
pubmed-meshheading:20309758-Genetic Predisposition to Disease,
pubmed-meshheading:20309758-Markov Chains,
pubmed-meshheading:20309758-Mice,
pubmed-meshheading:20309758-Mice, Inbred BALB C,
pubmed-meshheading:20309758-Mice, Inbred C57BL,
pubmed-meshheading:20309758-Models, Statistical,
pubmed-meshheading:20309758-Monte Carlo Method,
pubmed-meshheading:20309758-Oligonucleotide Array Sequence Analysis,
pubmed-meshheading:20309758-Pulmonary Fibrosis,
pubmed-meshheading:20309758-Reproducibility of Results,
pubmed-meshheading:20309758-Sample Size,
pubmed-meshheading:20309758-Species Specificity
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pubmed:year |
2010
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pubmed:articleTitle |
A semiparametric Bayesian approach for estimating the gene expression distribution.
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pubmed:affiliation |
Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA. fzou@bios.unc.edu
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pubmed:publicationType |
Journal Article,
Research Support, N.I.H., Extramural
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