Linked Life Data

20018069

Source:http://linkedlifedata.com/resource/pubmed/id/20018069

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PredicateObject
rdf:type
lifeskim:mentions
pubmed:dateCreated
2009-12-18
pubmed:abstractText
ABSTRACT : Many phenotypes of public health importance (e.g., diabetes, coronary artery disease, major depression, obesity, and addictions to alcohol and nicotine) involve complex pathways of action. Interactions between genetic variants or between genetic variants and environmental factors likely play important roles in the functioning of these pathways. Unfortunately, complex interacting systems are likely to have important interacting factors that may not readily reveal themselves to univariate analyses. Instead, detecting the role of some of these factors may require analyses that are sensitive to interaction effects.In this study, we evaluate the sensitivity and specificity of the restricted partition method (RPM) to detect signals related to coronary artery disease in the Genetic Analysis Workshop 16 Problem 3 data using the 50,000 k candidate gene single-nucleotide polymorphism set. Power and false-positive rates were evaluated using the first 100 replicate datasets. This included an exploration of the utility of using of all genotyped family members compared with selecting one member per family.
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
S74
pubmed:year
2009
pubmed:articleTitle
Power and false-positive rates for the restricted partition method (RPM) in a large candidate gene data set.
pubmed:affiliation
Department of Medicine, Washington University School of Medicine, 660 South Euclid Avenue, St, Louis, Missouri 63110, USA. rculverh@wustl.edu.
pubmed:publicationType
Journal Article