Department of Immunology, University of Washington, Seattle, Washington 98195, USA.
Bioinformatics. 2010 Feb 15;26(4):560-4. doi: 10.1093/bioinformatics/btp714. Epub 2010 Jan 6.
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.
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.
全基因组关联研究开始阐明我们的遗传差异如何导致疾病的易感性和严重程度。虽然以前已经开发了计算工具来支持全基因组关联研究的各个方面，但目前需要信息学解决方案来促进来自多个来源的数据的整合。
在这里，我们提出了 GWAS Analyzer，这是一个基于数据库的网络工具，它集成了基因型和表型数据、来自多个公共资源的关联分析结果和基因组注释。GWAS Analyzer 包含用于浏览这些相关数据的功能，通过家族或基因型探索表型值，并根据多个标准过滤关联结果。该工具的实用性已通过人类体外对细菌感染易感性的全基因组关联研究得到证明。GWAS Analyzer 方便了大量表型和基因型数据的管理、表型变异和遗传力的分析，最重要的是，生成了一组经过精炼的候选单核苷酸多态性（SNP）。该工具揭示了一个 SNP，该 SNP 经实验验证与沙门氏菌感染 HapMap 细胞系中细胞死亡增加有关。
