Detecting rare and common haplotype-environment interaction under uncertainty of gene-environment independence assumption

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Detecting rare haplotype-environment interaction with logistic Bayesian LASSO.

Two important contributors to missing heritability are believed to be rare variants and gene-environment interaction (GXE). Thus, detecting GXE where G is a rare haplotype variant (rHTV) is a pressing problem. Haplotype analysis is usually the natural second step to follow up on a genomic region that is implicated to be associated through single nucleotide variants (SNV) analysis. Further, rHTV...

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It is important to investigate whether genetic susceptibility variants exercise the same effects in populations that are differentially exposed to environmental risk factors. Here, we assess the power of four two-stage case-control design strategies for assessing multiplicative gene-environment (G-E) interactions or for assessing genetic or environmental effects in the presence of G-E interacti...

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SBERIA: set-based gene-environment interaction test for rare and common variants in complex diseases.

Identification of gene-environment interaction (G × E) is important in understanding the etiology of complex diseases. However, partially due to the lack of power, there have been very few replicated G × E findings compared to the success in marginal association studies. The existing G × E testing methods mainly focus on improving the power for individual markers. In this paper, we took a diffe...

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A Bayesian hierarchical model for detecting haplotype-haplotype and haplotype-environment interactions in genetic association studies.

OBJECTIVE Genetic association studies based on haplotypes are powerful in the discovery and characterization of the genetic basis of complex human diseases. However, statistical methods for detecting haplotype-haplotype and haplotype-environment interactions have not yet been fully developed owing to the difficulties encountered: large numbers of potential haplotypes and unknown haplotype pairs...

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ژورنال

عنوان ژورنال: Biometrics

سال: 2016

ISSN: 0006-341X

DOI: 10.1111/biom.12567