Journal Article

ExactFDR: exact computation of false discovery rate estimate in case-control association studies

Jérôme Wojcik and Karl Forner

in Bioinformatics

Volume 24, issue 20, pages 2407-2408
Published in print October 2008 | ISSN: 1367-4803
Published online July 2008 | e-ISSN: 1460-2059 | DOI: http://dx.doi.org/10.1093/bioinformatics/btn379
ExactFDR: exact computation of false discovery rate estimate in case-control association studies

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Summary: 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 χ2 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.

Availability: A Java 1.6 (1.5-compatible) version is available on SourceForge: http://sourceforge.net/projects/exactfdr.

Contact: Jerome.wojcik@merckserono.net

Supplementary information: Supplementary data are available at Bioinformatics online.

Journal Article.  1114 words.  Illustrated.

Subjects: Bioinformatics and Computational Biology

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