Linked Life Data

17047687

Source:http://linkedlifedata.com/resource/pubmed/id/17047687

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
11
pubmed:dateCreated
2006-10-18
pubmed:abstractText
Genic variants are more likely to alter gene function and affect disease risk than those that occur outside genes. Variants in genes, however, might not be sufficiently covered by the existing approaches to genome-wide association studies. Our analysis of the HapMap ENCODE data indicates that this concern is valid, and that an alternative approach that focuses on genic variants provides a more complete coverage of functionally important regions and a greater genotyping efficiency. We therefore argue that resources should be developed to make gene-centric genome-wide association studies feasible.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Nov
pubmed:issn
1471-0056
pubmed:author
pubmed:issnType
Print
pubmed:volume
7
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
885-91
pubmed:dateRevised
2008-11-21
pubmed:meshHeading
pubmed:year
2006
pubmed:articleTitle
A gene-centric approach to genome-wide association studies.
pubmed:affiliation
Department of Epidemiology and Biostatistics, and Center for Human Genetics, University of California, San Francisco, California 94143-0794, USA. Eric.Jorgenson@ucsf.edu
pubmed:publicationType
Journal Article, Review, Research Support, N.I.H., Extramural