Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
4
pubmed:dateCreated
2008-4-2
pubmed:abstractText
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.
pubmed:commentsCorrections
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Apr
pubmed:issn
1088-9051
pubmed:author
pubmed:issnType
Print
pubmed:volume
18
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
640-3
pubmed:dateRevised
2009-11-18
pubmed:meshHeading
pubmed:year
2008
pubmed:articleTitle
WGAViewer: software for genomic annotation of whole genome association studies.
pubmed:affiliation
Center for Population Genomics & Pharmacogenetics, Institute for Genome Sciences & Policy, Duke University, Durham, North Carolina 27708, USA. d.ge@duke.edu
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't, Evaluation Studies