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Methods and Resources

WGAViewer: A Software for Genomic Annotation of Whole Genome Association Studies

¹ Duke University; ² University of Lausanne, Switzerland; ³ Swiss Institute of Bioinformatics

To meet the immediate need for a framework of post-whole genome association (WGA) annotation, we have developed WGAViewer, a suite of JAVA software tools that provides a user-friendly interface to automatically annotate, visualize, and interpret the set of P values emerging from a WGA study. Most valuably, it can be used to highlight possible functional mechanisms in an automatic manner, for example by directly or indirectly implicating a polymorphism with an apparent link to gene expression, and help to generate hypotheses concerning the possible biological basis of observed associations. The easily interpretable diagrams can then be used to identify the associations that seem most likely to be biologically relevant, and to select genomic regions that may need to be resequenced in a search for candidate causal variants. In this report, we used our recently completed study on host control of HIV-1 viral load during the asymptomatic set point period (Fellay et al. 2007) as an illustration for the heuristic annotation of this software and its contributive role in a successful WGA project.

E-mail d.goldstein{at}duke.edu

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