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Type of publication: Journal Article
Type of document: Full Paper

Year: 2012

Authors: Kofler, R; Schlötterer, C

Title: Gowinda: unbiased analysis of gene set enrichment for genome-wide association studies.

Source: Bioinformatics. 2012; 28(15):2084-2085

Authors Vetmeduni Vienna:

Kofler Robert
Schlötterer Christian

Vetmed Research Units
Institute of Population Genetics

Project(s): Local selective sweeps in Drosophila melanogaster

An analysis of gene set [e.g. Gene Ontology (GO)] enrichment assumes that all genes are sampled independently from each other with the same probability. These assumptions are violated in genome-wide association (GWA) studies since (i) longer genes typically have more single-nucleotide polymorphisms resulting in a higher probability of being sampled and (ii) overlapping genes are sampled in clusters. Herein, we introduce Gowinda, a software specifically designed to test for enrichment of gene sets in GWA studies. We show that GO tests on GWA data could result in a substantial number of false-positive GO terms. Permutation tests implemented in Gowinda eliminate these biases, but maintain sufficient power to detect enrichment of GO terms. Since sufficient resolution for large datasets requires millions of permutations, we use multi-threading to keep computation times reasonable.

Keywords Pubmed: Animals
Computational Biology/methods*
Drosophila melanogaster/genetics
Genome-Wide Association Study/methods*
Linkage Disequilibrium
Polymorphism, Single Nucleotide*

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