Linked Life Data

16451660

Source:http://linkedlifedata.com/resource/pubmed/id/16451660

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PredicateObject
rdf:type
lifeskim:mentions
pubmed:dateCreated
2010-1-19
pubmed:abstractText
The purpose of these analyses was to determine if incorporating or adjusting for covariates in genetic analyses helped or hindered in genetic analyses, specifically heritability and linkage analyses. To study this question, two types of covariate models were used in the simulated Genetic Analysis Workshop 14 dataset in which the true gene locations are known. All four populations of one replicate were combined for the analyses. The first model included typical covariates of sex and cohort (population) and the second included the typical covariates and also those related endophenotypes that are thought to be associated with the trait (phenotypes A, B, C, D, E, F, G, H, I, J, K, and L). A final best fit model produced in the heritability analyses was used for linkage. Linkage for disease genes D1, D3, and D4 were localized using models with and without the covariates. The use of inclusion of covariates did not appear to have any consistent advantage or disadvantage for the different phenotypes in regards to gene localization or false positive rate.
pubmed:commentsCorrections
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:issn
1471-2156
pubmed:author
pubmed:issnType
Electronic
pubmed:volume
6 Suppl 1
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
S49
pubmed:dateRevised
2010-11-18
pubmed:meshHeading
pubmed:year
2005
pubmed:articleTitle
Including endophenotypes as covariates in variance component heritability and linkage analysis.
pubmed:affiliation
Neuropsychiatric Institute and Epilepsy Genetics/Genomics Laboratories, University of California at Los Angeles School of Medicine, Los Angeles, CA, USA. jbailey@mednet.ucla.edu
pubmed:publicationType
Journal Article