Testing the Significance of Interactions in Genetic Studies Using Interaction Information and Resampling Technique

ABSTRACT: Interaction information is a model-free, non-parametric measure used for detection of interaction among variables. It frequently finds interactions which remain undetected by standard model-based methods. However in the previous studies application of interaction information was limited by lack of appropriate statistical tests. We study a challenging problem of testing the positiveness of interaction information which allows to confirm the statistical significance of the investigated interactions. It turns out that commonly used chi-squared test detects too many spurious interactions when the dependence between the variables (e.g. between two genetic markers) is strong. To overcome this problem we consider permutation test and also propose a novel HYBRID method that combines permutation an

SUBMITTER: Teisseyre P 

PROVIDER: S-EPMC7304020 | biostudies-literature | 2020 May

REPOSITORIES: biostudies-literature