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...
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Main Authors: | , |
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Format: | Article |
Language: | English |
Published: |
Public Library of Science (PLoS)
2019-01-01
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Series: | PLoS ONE |
Online Access: | https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0213236&type=printable |
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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. |
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ISSN: | 1932-6203 |