Linked Life Data

12831322

Source:http://linkedlifedata.com/resource/pubmed/id/12831322

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
4
pubmed:dateCreated
2003-7-1
pubmed:abstractText
Population substructure and recent admixture may confound the results of genetic association studies in unrelated individuals, leading to a potential excess of both false positive and false negative results. The possibility of false associations depends on the population sampled, the trait being studied and the marker being tested. Although family based tests of association avoid the possibility of confounding due to population substructure and admixture, association studies in unrelated individuals may be preferred in many situations due to their feasibility. Unlinked genetic markers may be used to detect confounding in association studies. In addition, the information from unlinked markers may be used to adjust genetic associations.
pubmed:grant
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Jul
pubmed:issn
1462-2416
pubmed:author
pubmed:issnType
Print
pubmed:volume
4
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
431-41
pubmed:dateRevised
2010-11-18
pubmed:meshHeading
pubmed:year
2003
pubmed:articleTitle
Human population structure and genetic association studies.
pubmed:affiliation
Division of General Internal Medicine and Division of Pulmonary Medicine, Department of Medicine, University of California, San Francisco, CA 94115, USA. eziv@itsa.ucsf.edu
pubmed:publicationType
Journal Article, Research Support, U.S. Gov't, P.H.S., Review, Research Support, Non-U.S. Gov't