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題名 Estimation of False Discovery Rates in Multiple Testing: Application to Gene Microarray Data
作者 Hsueh,Huey-miin;Tsai,Chen-An ;Chen J. J.
薛慧敏;蔡政安
關鍵詞 Bayesian Type I error;
     Comparison-wise error rate (CWE);
     False discovery rate (FDR);
     Number of rejections;
     Number of true null hypotheses;
     q-value
日期 2003-12
上傳時間 19-Dec-2008 14:51:16 (UTC+8)
摘要 Testing for significance with gene expression data from DNA microarray experiments involves simultaneous comparisons of hundreds or thousands of genes. If R denotes the number of rejections (declared significant genes) and V denotes the number of false rejections, then V/R, if R > 0, is the proportion of false rejected hypotheses. This paper proposes a model for the distribution of the number of rejections and the conditional distribution of V given R, V | R. Under the independence assumption, the distribution of R is a convolution of two binomials and the distribution of V | R has a noncentral hypergeometric distribution. Under an equicorrelated model, the distributions are more complex and are also derived. Five false discovery rate probability error measures are considered: FDR = E(V/R), pFDR = E(V/R | R > 0) (positive FDR), cFDR = E(V/R | R = r) (conditional FDR), mFDR = E(V)/E(R) (marginal FDR), and eFDR = E(V)/r (empirical FDR). The pFDR, cFDR, and mFDR are shown to be equivalent under the Bayesian framework, in which the number of true null hypotheses is modeled as a random variable. We present a parametric and a bootstrap procedure to estimate the FDRs. Monte Carlo simulations were conducted to evaluate the performance of these two methods. The bootstrap procedure appears to perform reasonably well, even when the alternative hypotheses are correlated (ρ = .25). An example from a toxicogenomic microarray experiment is presented for illustration.
關聯 Biometrics, 59(4),1073-1083
資料類型 article
DOI http://dx.doi.org/10.1111/j.0006-341X.2003.00123.x
dc.creator (作者) Hsueh,Huey-miin;Tsai,Chen-An ;Chen J. J.en_US
dc.creator (作者) 薛慧敏;蔡政安-
dc.date (日期) 2003-12en_US
dc.date.accessioned 19-Dec-2008 14:51:16 (UTC+8)-
dc.date.available 19-Dec-2008 14:51:16 (UTC+8)-
dc.date.issued (上傳時間) 19-Dec-2008 14:51:16 (UTC+8)-
dc.identifier.uri (URI) https://nccur.lib.nccu.edu.tw/handle/140.119/18152-
dc.description.abstract (摘要) Testing for significance with gene expression data from DNA microarray experiments involves simultaneous comparisons of hundreds or thousands of genes. If R denotes the number of rejections (declared significant genes) and V denotes the number of false rejections, then V/R, if R > 0, is the proportion of false rejected hypotheses. This paper proposes a model for the distribution of the number of rejections and the conditional distribution of V given R, V | R. Under the independence assumption, the distribution of R is a convolution of two binomials and the distribution of V | R has a noncentral hypergeometric distribution. Under an equicorrelated model, the distributions are more complex and are also derived. Five false discovery rate probability error measures are considered: FDR = E(V/R), pFDR = E(V/R | R > 0) (positive FDR), cFDR = E(V/R | R = r) (conditional FDR), mFDR = E(V)/E(R) (marginal FDR), and eFDR = E(V)/r (empirical FDR). The pFDR, cFDR, and mFDR are shown to be equivalent under the Bayesian framework, in which the number of true null hypotheses is modeled as a random variable. We present a parametric and a bootstrap procedure to estimate the FDRs. Monte Carlo simulations were conducted to evaluate the performance of these two methods. The bootstrap procedure appears to perform reasonably well, even when the alternative hypotheses are correlated (ρ = .25). An example from a toxicogenomic microarray experiment is presented for illustration.-
dc.format application/en_US
dc.language enen_US
dc.language en-USen_US
dc.language.iso en_US-
dc.relation (關聯) Biometrics, 59(4),1073-1083en_US
dc.subject (關鍵詞) Bayesian Type I error;
     Comparison-wise error rate (CWE);
     False discovery rate (FDR);
     Number of rejections;
     Number of true null hypotheses;
     q-value		-
dc.title (題名) Estimation of False Discovery Rates in Multiple Testing: Application to Gene Microarray Dataen_US
dc.type (資料類型) articleen
dc.identifier.doi (DOI) 10.1111/j.0006-341X.2003.00123.xen_US
dc.doi.uri (DOI) http://dx.doi.org/10.1111/j.0006-341X.2003.00123.xen_US