title: ExactFDR: exact computation of false discovery rate estimate in case-control association studies.
abstract: Genome-wide association studies require accurate and fast statistical methods to identify relevant signals from the background noise generated by a huge number of simultaneously tested hypotheses. It is now commonly accepted that exact computations of association probability value (P-value) are preferred to chi(2) and permutation-based approximations. Following the same principle, the ExactFDR software package improves speed and accuracy of the permutation-based false discovery rate (FDR) estimation method by replacing the permutation-based estimation of the null distribution by the generalization of the algorithm used for computing individual exact P-values. It provides a quick and accurate non-conservative estimator of the proportion of false positives in a given selection of markers, and is therefore an efficient and pragmatic tool for the analysis of genome-wide association studies.
authors.affiliation: Department of Bioinformatics, Merck Serono Geneva Research Center, 1202 Geneva, Switzerland. Jerome.wojcik@merckserono.net
authors.forename: Jérôme
authors.initials: J
authors.lastname: Wojcik
authors.forename: Karl
authors.initials: K
authors.lastname: Forner
mesh_terms: D000465:Algorithms; D016022:Case-Control Studies; D019295:Computational Biology / Q000379:methods*; D003627:Data Interpretation, Statistical; D005189:False Positive Reactions; D020869:Gene Expression Profiling / Q000379:methods; D020022:Genetic Predisposition to Disease; D015894:Genome, Human; D006801:Humans; D008957:Models, Genetic; D012984:Software