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Updated: May 22, 2026

A Protocol for Using Gene Set Enrichment Analysis to Identify the Appropriate Animal Model for Translational Research
Published on: August 16, 2017
Gowinda: unbiased analysis of gene set enrichment for genome-wide association studies
Robert Kofler1, Christian Schlötterer
1Institut für Populationsgenetik, Vetmeduni Vienna, Veterinärplatz 1, A-1210 Wien, Austria.
Summary:
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.
Availability And Implementation:
Gowinda is implemented in Java (v1.6) and freely available on http://code.google.com/p/gowinda/
Contact:
christian.schloetterer@vetmeduni.ac.at
Supplementary Information:
Manual: http://code.google.com/p/gowinda/wiki/Manual. Test data and tutorial: http://code.google.com/p/gowinda/wiki/Tutorial.
Validation:
http://code.google.com/p/gowinda/wiki/VALIDATION.
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