Journal Article

GWAS Analyzer: integrating genotype, phenotype and public annotation data for genome-wide association study analysis

Christine Fong, Dennis C. Ko, Michael Wasnick, Matthew Radey, Samuel I. Miller and Mitchell Brittnacher

in Bioinformatics

Volume 26, issue 4, pages 560-564
Published in print February 2010 | ISSN: 1367-4803
Published online January 2010 | e-ISSN: 1460-2059 | DOI: https://dx.doi.org/10.1093/bioinformatics/btp714

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Motivation: Genome-wide association studies are beginning to elucidate how our genetic differences contribute to susceptibility and severity of disease. While computational tools have previously been developed to support various aspects of genome-wide association studies, there is currently a need for informatics solutions that facilitate the integration of data from multiple sources.

Results: Here we present GWAS Analyzer, a database driven web-based tool that integrates genotype and phenotype data, association analysis results and genomic annotations from multiple public resources. GWAS Analyzer contains features for browsing these interrelated data, exploring phenotypic values by family or genotype, and filtering association results based on multiple criteria. The utility of the tool has been demonstrated by a genome-wide association study of human in vitro susceptibility to bacterial infection. GWAS Analyzer facilitated management of large sets of phenotype and genotype data, analysis of phenotypic variation and heritability, and most importantly, generation of a refined set of candidate single nucleotide polymorphisms (SNPs). The tool revealed a SNP that was experimentally validated to be associated with increased cell death among Salmonella infected HapMap cell lines.

Availability: http://www.nwrce.org/gwas-analyzer

Contact: mbrittna@u.washington.edu

Supplementary Information: Supplementary data are available at Bioinformatics online.

Journal Article.  3826 words.  Illustrated.

Subjects: Bioinformatics and Computational Biology

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