Source:http://linkedlifedata.com/resource/pubmed/id/20380755
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| Predicate | Object |
|---|---|
| rdf:type | |
| lifeskim:mentions | |
| pubmed:dateCreated |
2010-4-12
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| pubmed:abstractText |
Identification of QTL affecting a phenotype which is measured multiple times on the same experimental unit is not a trivial task because the repeated measures are not independent and in most cases show a trend in time. A complicating factor is that in most cases the mean increases non-linear with time as well as the variance. A two- step approach was used to analyze a simulated data set containing 1000 individuals with 5 measurements each. First the measurements were summarized in latent variables and subsequently a genome wide analysis was performed of these latent variables to identify segregating QTL using a Bayesian algorithm.
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| pubmed:commentsCorrections | |
| pubmed:language |
eng
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| pubmed:journal | |
| pubmed:status |
PubMed-not-MEDLINE
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| pubmed:issn |
1753-6561
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| pubmed:author | |
| pubmed:issnType |
Electronic
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| pubmed:volume |
4 Suppl 1
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| pubmed:owner |
NLM
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| pubmed:authorsComplete |
Y
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| pubmed:pagination |
S12
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| pubmed:dateRevised |
2011-10-24
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| pubmed:year |
2010
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| pubmed:articleTitle |
Bayesian multi-QTL mapping for growth curve parameters.
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| pubmed:affiliation |
Clinical Sciences of Companion Animals Faculty of Veterinary Medicine, Utrecht University P,O, box 80163, 3508 TD Utrecht, The Netherlands . h.c.m.heuven@uu.nl.
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| pubmed:publicationType |
Journal Article
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