Linked Life Data

20018095

Source:http://linkedlifedata.com/resource/pubmed/id/20018095

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PredicateObject
rdf:type
lifeskim:mentions
pubmed:dateCreated
2009-12-18
pubmed:abstractText
ABSTRACT : We examine a Bayesian Markov-chain Monte Carlo framework for simultaneous segregation and linkage analysis in the simulated single-nucleotide polymorphism data provided for Genetic Analysis Workshop 16. We conducted linkage only, linkage and association, and association only tests under this framework. We also compared these results with variance-component linkage analysis and regression analyses. The results indicate that the method shows some promise, but finding genes that have very small (<0.1%) contributions to trait variance may require additional sources of information. All methods examined fared poorly for the smallest in the simulated "polygene" range (h2 of 0.0015 to 0.0002).
pubmed:grant
pubmed:commentsCorrections
pubmed:language
eng
pubmed:journal
pubmed:status
PubMed-not-MEDLINE
pubmed:issn
1753-6561
pubmed:author
pubmed:issnType
Electronic
pubmed:volume
3 Suppl 7
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
S98
pubmed:year
2009
pubmed:articleTitle
A framework for analyzing both linkage and association: an analysis of Genetic Analysis Workshop 16 simulated data.
pubmed:affiliation
Division of Statistical Genomics, Washington University School of Medicine, 4444 Forest Park Boulevard, Campus Box 8506, St, Louis, Missouri 63108 USA. warwick@wustl.edu.
pubmed:publicationType
Journal Article