%0 Journal Article
%T A unified approach to false discovery rate estimation
%A Korbinian Strimmer
%J BMC Bioinformatics
%D 2008
%I BioMed Central
%R 10.1186/1471-2105-9-303
%X A unifying algorithm for simultaneous estimation of both local FDR and tail area-based FDR is presented that can be applied to a diverse range of test statistics, including p-values, correlations, z- and t-scores. This approach is semipararametric and is based on a modified Grenander density estimator. For test statistics other than p-values it allows for empirical null modeling, so that dependencies among tests can be taken into account. The inference of the underlying model employs truncated maximum-likelihood estimation, with the cut-off point chosen according to the false non-discovery rate.The proposed procedure generalizes a number of more specialized algorithms and thus offers a common framework for FDR estimation consistent across test statistics and types of FDR. In comparative study the unified approach performs on par with the best competing yet more specialized alternatives. The algorithm is implemented in R in the "fdrtool" package, available under the GNU GPL from http://strimmerlab.org/software/fdrtool/ webcite and from the R package archive CRAN.The false discovery rate (FDR) plays a prominent role in many high-dimensional testing and model selection procedures. Consequently, FDR methodologies are ubiquitous in the analysis of high-throughput data, such as in differential gene expression, SNP biomarker selection, peak detection in proteomic mass spectrometry data, or inference of edges in a network.False discovery rate analysis starts with the seminal works by Schweder and Spj£¿tvoll [1] and by Benjamini and Hochberg [2]. Many others have followed suite, so that to date an impressive number of different algorithms for controlling and estimating false discovery rates have appeared in the literature.In a nutshell, FDR estimation algorithms may be broadly categorized by the type of£¿ FDR,£¿ input test statistic, and£¿ employed inference procedures.There are two main types of FDR, the "classic" tail area-based FDR (= Fdr) and local FDR (= fdr). Most FDR proc
%U http://www.biomedcentral.com/1471-2105/9/303