Linked Life Data

10721613

Source:http://linkedlifedata.com/resource/pubmed/id/10721613

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
1
pubmed:dateCreated
2000-3-31
pubmed:abstractText
In the past decade phenomenal progress has been made in molecular and statistical genetic methods for localizing quantitative trait loci. Because of these advances, we can anticipate a long period of active genetic research in which the genes influencing human quantitative variability will be mapped and their effects accurately evaluated. Here, we review the current state of the science in statistical genetic methods for quantitative trait linkage analysis. In particular, we detail a variance component-based framework for localizing quantitative trait loci and for accurately estimating their relative effect sizes. Attention is paid to the optimal design of human family studies for localizing genes of small to moderate effect. In addition, methods and strategies are described for dealing with the most important complications of quantitative variation, including the assessment of genotype x environment interaction and epistasis.
pubmed:grant
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Feb
pubmed:issn
0018-7143
pubmed:author
pubmed:issnType
Print
pubmed:volume
72
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
35-62
pubmed:dateRevised
2011-4-18
pubmed:meshHeading
pubmed:year
2000
pubmed:articleTitle
Quantitative trait locus mapping using human pedigrees.
pubmed:affiliation
Department of Genetics, Southwest Foundation for Biomedical Research, San Antonio, TX 78245-0549, USA.
pubmed:publicationType
Journal Article, Research Support, U.S. Gov't, P.H.S.