SHEIB-AGM: A Novel Stochastic Approach for Detecting High-Order Epistatic Interactions Using Bioinformation With Automatic Gene Matrix in Genome-Wide Association Studies
Abstract:Detecting epistatic interactions in GWAS (genome-wide association studies) data is of great significance in studying common and complex diseases; however, the ability to detect high-order epistatic interactions in GWAS data is still insufficient. Existing methods are usually used to identify two-order interactions, and they cannot detect a large number of interactions. In this article, we propose a novel stochastic approach named SHEIB-AGM (stochastic approach for detecting high-order epistatic interactions us… Show more
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