Efficient Simulation of Epistatic Interactions in Case-Parent Trios

Abstract

Statistical approaches to evaluate interactions between single nucleotide polymorphisms (SNPs) and SNP-environment interactions are of great importance in genetic association studies, as susceptibility to complex disease might be related to the interaction of multiple SNPs and/or environmental factors. With these methods under active development, algorithms to simulate genomic data sets are needed to ensure proper type I error control of newly proposed methods and to compare power with existing methods. In this paper we propose an efficient method for a haplotype-based simulation of case-parent trios when the disease risk is thought to depend on possibly higher-order epistatic interactions or gene-environment interactions with binary exposures.

Simulating autosomal genotypes with realistic linkage disequilibrium and a spiked-in genetic effect

“…An important extension would be to accommodate a richer genetic structure for each pathway. Currently, our code is restricted to a dominant (at least one variant present) mode of inheritance for each SNP in a pathway; our framework would allow more flexibility in that specification, ideally the Boolean specifications used in logic regression [ 10 , 11 ].…”

Detecting Disease Variants in Case-Parent Trio Studies Using the Bioconductor Software Packagetrio

“…One example for additional functionality is a method for efficient retrospective simulation of case‐parent trios in which disease risk can also depend on complex gene–gene and gene–environment interactions (as described in Li et al., ). We also offer an implementation of the EM algorithm proposed by Weinberg [] in the function colEMlrt(), based on a likelihood‐based method including genetic information from incomplete trios, thereby not suffering from a loss of power and induced bias, compared to a complete case analysis [see Curtis and Sham, ].…”