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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...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2019
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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. |
format | Online Article Text |
id | pubmed-6436689 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
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 |
work_keys_str_mv | AT chenglu compositionalepistasisdetectionusingafewprototypediseasemodels AT zhumu compositionalepistasisdetectionusingafewprototypediseasemodels |