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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 SNPs prior...

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Detalles Bibliográficos
Autores principales: Cheng, Lu, Zhu, Mu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6436689/
https://www.ncbi.nlm.nih.gov/pubmed/30917131
http://dx.doi.org/10.1371/journal.pone.0213236
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author Cheng, Lu
Zhu, Mu
author_facet Cheng, Lu
Zhu, Mu
author_sort Cheng, Lu
collection PubMed
description 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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spelling pubmed-64366892019-04-12 Compositional epistasis detection using a few prototype disease models Cheng, Lu Zhu, Mu PLoS One Research Article 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. Public Library of Science 2019-03-27 /pmc/articles/PMC6436689/ /pubmed/30917131 http://dx.doi.org/10.1371/journal.pone.0213236 Text en © 2019 Cheng, Zhu http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Cheng, Lu
Zhu, Mu
Compositional epistasis detection using a few prototype disease models
title Compositional epistasis detection using a few prototype disease models
title_full Compositional epistasis detection using a few prototype disease models
title_fullStr Compositional epistasis detection using a few prototype disease models
title_full_unstemmed Compositional epistasis detection using a few prototype disease models
title_short Compositional epistasis detection using a few prototype disease models
title_sort compositional epistasis detection using a few prototype disease models
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6436689/
https://www.ncbi.nlm.nih.gov/pubmed/30917131
http://dx.doi.org/10.1371/journal.pone.0213236
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