Bayesian epistasis association mapping via SNP imputation

Yu Zhang

Research output: Contribution to journalArticle

3 Citations (Scopus)

Abstract

Genetic mutations may interact to increase the risk of human complex diseases. Mapping of multiple interacting disease loci in the human genome has recently shown promise in detecting genes with little main effects. The power of interaction association mapping, however, can be greatly influenced by the set of single nucleotide polymorphism (SNP) genotyped in a case-control study. Previous imputation methods only focus on imputation of individual SNPs without considering their joint distribution of possible interactions. We present a new method that simultaneously detects multilocus interaction associations and imputes missing SNPs from a full Bayesian model. Our method treats both the case-control sample and the reference data as random observations. The output of our method is the posterior probabilities of SNPs for their marginal and interacting associations with the disease. Using simulations, we show that the method produces accurate and robust imputation with little overfitting problems. We further show that, with the type I error rate maintained at a common level, SNP imputation can consistently and sometimes substantially improve the power of detecting disease interaction associations. We use a data set of inflammatory bowel disease to demonstrate the application of our method.

Original languageEnglish (US)
Pages (from-to)211-222
Number of pages12
JournalBiostatistics
Volume12
Issue number2
DOIs
StatePublished - Apr 1 2011

Fingerprint

Epistasis
Single nucleotide Polymorphism
Imputation
Interaction
Case-control
Type I Error Rate
Case-control Study
Overfitting
Main Effect
Posterior Probability
Bayesian Model
Joint Distribution
Locus
Polymorphism
Mutation
Genome
Gene
Output
Demonstrate
Simulation

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Statistics, Probability and Uncertainty

Cite this

Zhang, Yu. / Bayesian epistasis association mapping via SNP imputation. In: Biostatistics. 2011 ; Vol. 12, No. 2. pp. 211-222.
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Bayesian epistasis association mapping via SNP imputation. / Zhang, Yu.

In: Biostatistics, Vol. 12, No. 2, 01.04.2011, p. 211-222.

Research output: Contribution to journalArticle

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