WGAViewer: Software for genomic annotation of whole genome association studies

@article{citeulike:2758775, abstract = {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 bases 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 as an illustration for the heuristic annotation of this software and its contributive role in a successful WGA project. 10.1101/gr.071571.107}, author = {Ge, Dongliang and Zhang, Kunlin and Need, Anna C. and Martin, Olivier and Fellay, Jacques and Urban, Thomas J. and Telenti, Amalio and Goldstein, David B. }, citeulike-article-id = {2758775}, doi = {10.1101/gr.071571.107}, journal = {Genome Res.}, month = {April}, number = {4}, pages = {640--643}, posted-at = {2008-05-10 09:48:51}, priority = {2}, title = {WGAViewer: Software for genomic annotation of whole genome association studies}, url = {http://dx.doi.org/10.1101/gr.071571.107}, volume = {18}, year = {2008} }

TY - JOUR ID - citeulike:2758775 TI - WGAViewer: Software for genomic annotation of whole genome association studies JF - Genome Res. VL - 18 IS - 4 SP - 640 EP - 643 N2 - 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 bases 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 as an illustration for the heuristic annotation of this software and its contributive role in a successful WGA project. 10.1101/gr.071571.107 AU - Ge, Dongliang AU - Zhang, Kunlin AU - Need, Anna AU - Martin, Olivier AU - Fellay, Jacques AU - Urban, Thomas AU - Telenti, Amalio AU - Goldstein, David PY - 2008/04/01/ UR - http://dx.doi.org/10.1101/gr.071571.107 ER -