Source:http://linkedlifedata.com/resource/pubmed/id/19635737
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Predicate | Object |
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rdf:type | |
lifeskim:mentions | |
pubmed:issue |
5
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pubmed:dateCreated |
2009-8-20
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pubmed:abstractText |
In genetic association studies, investigators compare allele or genotype frequencies in unrelated case and control subjects or examine preferential allele transmissions from parents to affected offspring. In many genetic case-control studies, the collection of DNA material extends to relatives such as parents of cases. Thus, case-control and case-parent trio association analyses are possible. Whereas the goal of collecting genetic information from family members in a study initially designed as a case-control study is to enrich the genetic analysis, increase power, or address concern about population structure bias, methods of combining genetic data from unrelated case and control subjects with genetic trio data from the same study population are not well known. A number of hybrid approaches have been developed that utilize such data together. In this paper, the authors describe key features of genetic case-control and case-parent trio studies and review commonly used methods of genetic analysis for case-parent trio designs. In addition, they provide a pragmatic review of statistical methods and available software for existing hybrid approaches that combine various components of case-control and genetic trio data. The application of all methods is illustrated using a candidate gene study of childhood leukemia that included case-control subjects and their parents.
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pubmed:language |
eng
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pubmed:journal | |
pubmed:citationSubset |
IM
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pubmed:status |
MEDLINE
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pubmed:month |
Sep
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pubmed:issn |
1476-6256
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pubmed:author | |
pubmed:issnType |
Electronic
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pubmed:day |
1
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pubmed:volume |
170
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pubmed:owner |
NLM
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pubmed:authorsComplete |
Y
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pubmed:pagination |
657-64
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pubmed:meshHeading | |
pubmed:year |
2009
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pubmed:articleTitle |
Combining case-control and case-trio data from the same population in genetic association analyses: overview of approaches and illustration with a candidate gene study.
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pubmed:affiliation |
Department of Epidemiology, Biostatistics and Occupational Health, Faculty of Medicine, McGill University, 1110 Pine Avenue West, Montreal, Quebec H3A1A3, Canada. claire.infante-rivard@mcgill.ca
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pubmed:publicationType |
Journal Article,
Review,
Research Support, Non-U.S. Gov't
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