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GMDR: Versatile Software for Detecting Gene-Gene and Gene-Environ- ment Interactions Underlying Complex Traits

Identification of multifactor gene-gene (G×G) and gene-environment (G×E) interactions underlying complex traits poses one of the great challenges to today’s genetic study. Development of the generalized multifactor dimensionality reduction (GMDR) method provides a practicable solution to problems in...

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Autores principales: Xu, Hai-Ming, Xu, Li-Feng, Hou, Ting-Ting, Luo, Lin-Feng, Chen, Guo-Bo, Sun, Xi-Wei, Lou, Xiang-Yang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Bentham Science Publishers 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5320543/
https://www.ncbi.nlm.nih.gov/pubmed/28479868
http://dx.doi.org/10.2174/1389202917666160513102612
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author Xu, Hai-Ming
Xu, Li-Feng
Hou, Ting-Ting
Luo, Lin-Feng
Chen, Guo-Bo
Sun, Xi-Wei
Lou, Xiang-Yang
author_facet Xu, Hai-Ming
Xu, Li-Feng
Hou, Ting-Ting
Luo, Lin-Feng
Chen, Guo-Bo
Sun, Xi-Wei
Lou, Xiang-Yang
author_sort Xu, Hai-Ming
collection PubMed
description Identification of multifactor gene-gene (G×G) and gene-environment (G×E) interactions underlying complex traits poses one of the great challenges to today’s genetic study. Development of the generalized multifactor dimensionality reduction (GMDR) method provides a practicable solution to problems in detection of interactions. To exploit the opportunities brought by the availability of diverse data, it is in high demand to develop the corresponding GMDR software that can handle a breadth of phenotypes, such as continuous, count, dichotomous, polytomous nominal, ordinal, survival and multivariate, and various kinds of study designs, such as unrelated case-control, family-based and pooled unrelated and family samples, and also allows adjustment for covariates. We developed a versatile GMDR package to implement this serial of GMDR analyses for various scenarios (e.g., unified analysis of unrelated and family samples) and large-scale (e.g., genome-wide) data. This package includes other desirable features such as data management and preprocessing. Permutation testing strategies are also built in to evaluate the threshold or empirical p values. In addition, its performance is scalable to the computational resources. The software is available at http://www.soph.uab.edu/ssg/software or http://ibi.zju.edu.cn/software.
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spelling pubmed-53205432017-05-05 GMDR: Versatile Software for Detecting Gene-Gene and Gene-Environ- ment Interactions Underlying Complex Traits Xu, Hai-Ming Xu, Li-Feng Hou, Ting-Ting Luo, Lin-Feng Chen, Guo-Bo Sun, Xi-Wei Lou, Xiang-Yang Curr Genomics Article Identification of multifactor gene-gene (G×G) and gene-environment (G×E) interactions underlying complex traits poses one of the great challenges to today’s genetic study. Development of the generalized multifactor dimensionality reduction (GMDR) method provides a practicable solution to problems in detection of interactions. To exploit the opportunities brought by the availability of diverse data, it is in high demand to develop the corresponding GMDR software that can handle a breadth of phenotypes, such as continuous, count, dichotomous, polytomous nominal, ordinal, survival and multivariate, and various kinds of study designs, such as unrelated case-control, family-based and pooled unrelated and family samples, and also allows adjustment for covariates. We developed a versatile GMDR package to implement this serial of GMDR analyses for various scenarios (e.g., unified analysis of unrelated and family samples) and large-scale (e.g., genome-wide) data. This package includes other desirable features such as data management and preprocessing. Permutation testing strategies are also built in to evaluate the threshold or empirical p values. In addition, its performance is scalable to the computational resources. The software is available at http://www.soph.uab.edu/ssg/software or http://ibi.zju.edu.cn/software. Bentham Science Publishers 2016-10 2016-10 /pmc/articles/PMC5320543/ /pubmed/28479868 http://dx.doi.org/10.2174/1389202917666160513102612 Text en © 2016 Bentham Science Publishers https://creativecommons.org/licenses/by-nc/4.0/legalcode This is an open access article licensed under the terms of the Creative Commons Attribution-Non-Commercial 4.0 International Public License (CC BY-NC 4.0) (https://creativecommons.org/licenses/by-nc/4.0/legalcode), which permits unrestricted, non-commercial use, distribution and reproduction in any medium, provided the work is properly cited.
spellingShingle Article
Xu, Hai-Ming
Xu, Li-Feng
Hou, Ting-Ting
Luo, Lin-Feng
Chen, Guo-Bo
Sun, Xi-Wei
Lou, Xiang-Yang
GMDR: Versatile Software for Detecting Gene-Gene and Gene-Environ- ment Interactions Underlying Complex Traits
title GMDR: Versatile Software for Detecting Gene-Gene and Gene-Environ- ment Interactions Underlying Complex Traits
title_full GMDR: Versatile Software for Detecting Gene-Gene and Gene-Environ- ment Interactions Underlying Complex Traits
title_fullStr GMDR: Versatile Software for Detecting Gene-Gene and Gene-Environ- ment Interactions Underlying Complex Traits
title_full_unstemmed GMDR: Versatile Software for Detecting Gene-Gene and Gene-Environ- ment Interactions Underlying Complex Traits
title_short GMDR: Versatile Software for Detecting Gene-Gene and Gene-Environ- ment Interactions Underlying Complex Traits
title_sort gmdr: versatile software for detecting gene-gene and gene-environ- ment interactions underlying complex traits
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5320543/
https://www.ncbi.nlm.nih.gov/pubmed/28479868
http://dx.doi.org/10.2174/1389202917666160513102612
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