Visualization and Functional Analysis of Genome-Wide Association Results

Genome-wide association studies (GWAS) provide a new and powerful approach to investigate the effect of inherited genetic variation on risks of complex diseases. With recent advances in genotyping technology, genome-wide association studies are now becoming a reality. Within the past two years, scientists have successfully replicated genetic risks of several complex diseases including cancers, obesity, and type 2 diabetes using GWAS. And more data from GWAS are expected in an accelerated rate. However, management, analysis, visualization, and interpretation of genome wide association data are particularly difficult, primarily because GWAS may consists of hundreds of thousands SNPs (single nucleotide polymorphisms) from thousands individuals. This paper describes the features and implementation of a web application tool named MAVEN for Management, Analysis, Visualization and rEsults shariNg of GWA data using cutting edge technologies. In addition, MAVEN seamlessly integrates users own data with databases at the National Center for Biotechnology Information (NCBI), which allows users to directly obtain functional annotations of SNPs and genes that are relevant to their own research interests. Therefore, MAVEN can effectively facilitate the functional analysis of GWAS.