Linked Life Data

11793767

Source:http://linkedlifedata.com/resource/pubmed/id/11793767

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:dateCreated
2002-1-16
pubmed:abstractText
We utilized pedigree discriminant and factor analytic approaches to combine multivariate phenotypic information into a single liability phenotype in the isolate and general populations. We applied two-stage relative-pair quantitative trait linkage analysis to detect genetic contributions to variation in the resulting liability phenotypes. Linkage analysis revealed several regions of suggestive linkage in both the general and isolate populations, the majority of which appear in retrospect to be false positives. A likely explanation is an overall lack of power given that we tested hypotheses in data from only one replicate. However, it may be possible that a construct that ignores affection status when using liability-associated characteristics as indicators of this construct is not the most effective approach in modeling the liability underlying a complex phenotype.
pubmed:grant
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:issn
0741-0395
pubmed:author
pubmed:issnType
Print
pubmed:volume
21 Suppl 1
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
S720-5
pubmed:dateRevised
2008-11-21
pubmed:meshHeading
pubmed:year
2001
pubmed:articleTitle
Quantitative trait linkage analysis of the liability underlying a common oligogenic disease.
pubmed:affiliation
University of Pittsburgh, Pittsburgh, PA 15261, USA.
pubmed:publicationType
Journal Article, Research Support, U.S. Gov't, P.H.S.