Epi2Loc: An R Package to Investigate Two-Locus Epistatic Models

Abstract

Epistasis is a growing area of research in genome-wide studies, but the differences between alternative definitions of epistasis remain a source of confusion for many researchers. One problem is that models for epistasis are presented in a number of formats, some of which have difficult-to-interpret parameters. In addition, the relation between the different models is rarely explained. Existing software for testing epistatic interactions between single-nucleotide polymorphisms (SNPs) does not provide the flexibility to compare the available model parameterizations. For that reason we have developed an R package for investigating epistatic and penetrance models, Epi2Loc, to aid users who wish to easily compare, interpret, and utilize models for two-locus epistatic interactions. Epi2Loc facilitates research on SNP-SNP interactions by allowing the R user to easily convert between common parametric forms for two-locus interactions, generate data for simulation studies, and perform power analyses for the selected model with a continuous or dichotomous phenotype. The usefulness of the package for model interpretation and power analysis is illustrated using data on rheumatoid arthritis.

A heuristic method for simulating open-data of arbitrary complexity that can be used to compare and evaluate machine learning methods

“…Genetic data simulated is this way can then be used to simulate phenotypes using a statistical or computational model. Simple additive effects can be simulated using a linear regression model or more complex genetic effects such as gene-gene interactions can be simulated using methods and software such as Epi2Loc [7] or GAMETES [8]. Although useful, these tools don’t explicitly build their models using a framework that approximates the hierarchical complexity of biological systems.…”