A Graphical Tool for Exploring SNP-by-Environment Interaction in Case-Parent Trios
This project proposes a data-smoothing method for exploring statistical interaction between a single nucleotide polymorphism (SNP) and a non-genetic risk factor, such as age, in case-parent trios. The smoother can be used as a diagnostic tool for checking for the presence of interaction after conducting a genetic association test, such as the transmission/disequilibrium test, that does not account for interaction. Alternately, if an interaction model is fit to the data, the smoother can be used to check the adequacy of the chosen model.
The smoother arises from a case-only analysis conditional on parental genotypes. Such conditioning is used to protect against the false impression of statistical interaction, in the event that the genotypes and non-genetic risk factors violate the critical assumption of independence necessary for a traditional case-only analysis.
In this project, we discuss the theoretical motivation for the smoother, and illustrate its use with a simulated dataset. We also show that if the smoother had not been used to detect statistical interaction, the genetic effect due to the SNP genotype in the simulated dataset would have been missed.
This type of interdisciplinary work is a hallmark of our program in Applied Statistics at Simon Fraser University. For more information, please contact Linnea Duke (firstname.lastname@example.org) or her supervisor Jinko Graham (email@example.com), Department of Statistics and Actuarial Science.