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Analysis of case-control association studies with known risk variants

Zaitlen, Noah
Pasaniuc, Bogdan
Patterson, Nick
Pollack, Samuela
Voight, Benjamin
Groop, Leif
Altshuler, David
Henderson, Brian E
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Published in Bioinformatics. 2012, vol. 28, no. 13, p. 1729-37
Abstract The question of how to best use information from known associated variants when conducting disease association studies has yet to be answered. Some studies compute a marginal P-value for each Several Nucleotide Polymorphisms independently, ignoring previously discovered variants. Other studies include known variants as covariates in logistic regression, but a weakness of this standard conditioning strategy is that it does not account for disease prevalence and non-random ascertainment, which can induce a correlation structure between candidate variants and known associated variants even if the variants lie on different chromosomes. Here, we propose a new conditioning approach, which is based in part on the classical technique of liability threshold modeling. Roughly, this method estimates model parameters for each known variant while accounting for the published disease prevalence from the epidemiological literature.
Keywords Case-Control StudiesGenetic Association StudiesGenome-Wide Association StudyHumansLogistic ModelsModels, StatisticalPolymorphism, Single NucleotidePrevalenceRiskSoftware
PMID: 22556366
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Article (Published version) (322 Kb) - public document Free access
Research group Population Genomics and Genetics of Complex Traits (892)
Autre: Jeantet
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ZAITLEN, Noah et al. Analysis of case-control association studies with known risk variants. In: Bioinformatics, 2012, vol. 28, n° 13, p. 1729-37. doi: 10.1093/bioinformatics/bts259 https://archive-ouverte.unige.ch/unige:32170

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Deposited on : 2013-12-16

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