Linked Life Data

15682273

Source:http://linkedlifedata.com/resource/pubmed/id/15682273

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
2
pubmed:dateCreated
2005-3-7
pubmed:abstractText
Quantitative trait phenotypes and linked marker genotypes were simulated for a range of models with different sets of assumptions based on displacement, prevalence, and heritability of the trait in 30 Utah Centre d'Etude du Polymorphisme Humain (CEPH) families. The gain in power by the addition of 15 families was also estimated by extrapolation. Power was evaluated using both parametric single locus (PSL) models and variance components (VC) methods for two situations: (1) a single marker with 75% heterozygosity and a recombination fraction of 0.05, and (2) a fully informative marker as an approximation to multipoint analysis. When the simulation and analysis models were both dominant with the same prevalence, power > or =80% for lod >3 was estimated when quantitative trait locus variance was > or =40% with a displacement of 2.5 or 3. Power was 5-15% lower for recessive models compared to dominant models. With the addition of 15 families, an average increase in power of 17% and 22% was estimated for the dominant and recessive models, respectively. In PSL analyses, power was estimated at < or =20% when the dominance was misspecified. This investigation delineates parameter conditions under which this unique sample affords adequate power to detect linkage using both PSL and VC methods.
pubmed:grant
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:issn
1434-5161
pubmed:author
pubmed:issnType
Print
pubmed:volume
50
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
69-75
pubmed:dateRevised
2010-11-18
pubmed:meshHeading
pubmed:year
2005
pubmed:articleTitle
The power to detect genetic linkage for quantitative traits in the Utah CEPH pedigrees.
pubmed:affiliation
Department of Human Genetics, Eccles Institute of Human Genetics, University of Utah Health Sciences Center, Salt Lake City, UT, USA. amalhotra@tgen.org
pubmed:publicationType
Journal Article, Research Support, U.S. Gov't, P.H.S., Research Support, Non-U.S. Gov't