Epistasis Blog

From the Artificial Intelligence Innovation Lab at Cedars-Sinai Medical Center (www.epistasis.org)

Wednesday, July 15, 2009

GWAS Analysis Using Gene Ontology

Peter Holmans has published a very nice paper in the American Journal of Human Genetics on using Gene Ontology to analyze genome-wide association study (GWAS) data. See also my Dec. 6, 2008 post on our paper by Askland et al. that approaches the problem in the same way.

Holmans P, Green EK, Pahwa JS, Ferreira MA, Purcell SM, Sklar P; Wellcome Trust Case-Control Consortium, Owen MJ, O'Donovan MC, Craddock N. Gene ontology analysis of GWA study data sets provides insights into the biology of bipolar disorder. Am J Hum Genet. 2009 Jul;85(1):13-24. [PubMed]

Abstract

We present a method for testing overrepresentation of biological pathways, indexed by gene-ontology terms, in lists of significant SNPs from genome-wide association studies. This method corrects for linkage disequilibrium between SNPs, variable gene size, and multiple testing of nonindependent pathways. The method was applied to the Wellcome Trust Case-Control Consortium Crohn disease (CD) data set. At a general level, the biological basis of CD is relatively well known for a complex genetic trait, and it thus acted as a test of the method. The method, known as ALIGATOR (Association LIst Go AnnoTatOR), successfully detected biological pathways implicated in CD. The method was also applied to a meta-analysis of bipolar disorder, and it implicated the modulation of transcription and cellular activity, including that which occurs via hormonal action, as an important player in pathogenesis.

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