Compositional epistasis detection using a few prototype disease models.

We study computational approaches for detecting SNP-SNP interactions that are characterized by a set of "two-locus, two-allele, two-phenotype and complete-penetrance" disease models. We argue that existing methods, which use data to determine a best-fitting disease model for each pair of S...

Full description

Saved in:
Bibliographic Details
Main Authors: Lu Cheng, Mu Zhu
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2019-01-01
Series:PLoS ONE
Online Access:https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0213236&type=printable
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:We study computational approaches for detecting SNP-SNP interactions that are characterized by a set of "two-locus, two-allele, two-phenotype and complete-penetrance" disease models. We argue that existing methods, which use data to determine a best-fitting disease model for each pair of SNPs prior to screening, may be too greedy. We present a less greedy strategy which, for each given pair of SNPs, limits the number of candidate disease models to a set of prototypes determined a priori.
ISSN:1932-6203