Linked Life Data

16596940

Source:http://linkedlifedata.com/resource/pubmed/id/16596940

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
5
pubmed:dateCreated
2006-4-6
pubmed:abstractText
Although much attention has been given to statistical genetic methods for the initial localization and fine mapping of quantitative trait loci (QTLs), little methodological work has been done to date on the problem of statistically identifying the most likely functional polymorphisms using sequence data. In this paper we provide a general statistical genetic framework, called Bayesian quantitative trait nucleotide (BQTN) analysis, for assessing the likely functional status of genetic variants. The approach requires the initial enumeration of all genetic variants in a set of resequenced individuals. These polymorphisms are then typed in a large number of individuals (potentially in families), and marker variation is related to quantitative phenotypic variation using Bayesian model selection and averaging. For each sequence variant a posterior probability of effect is obtained and can be used to prioritize additional molecular functional experiments. An example of this quantitative nucleotide analysis is provided using the GAW12 simulated data. The results show that the BQTN method may be useful for choosing the most likely functional variants within a gene (or set of genes). We also include instructions on how to use our computer program, SOLAR, for association analysis and BQTN analysis.
pubmed:grant
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Oct
pubmed:issn
0018-7143
pubmed:author
pubmed:issnType
Print
pubmed:volume
77
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
541-59
pubmed:dateRevised
2011-4-18
pubmed:meshHeading
pubmed:year
2005
pubmed:articleTitle
Quantitative trait nucleotide analysis using Bayesian model selection.
pubmed:affiliation
Department of Genetics, Southwest Foundation for Biomedical Research, 620 NW Loop 410, San Antonio, TX 78245-0549, USA.
pubmed:publicationType
Journal Article, Research Support, N.I.H., Extramural