Methods for Analyzing Multivariate Phenotypes in Genetic Association Studies

Multivariate phenotypes are frequently encountered in genetic association studies. The purpose of analyzing multivariate phenotypes usually includes discovery of novel genetic variants of pleiotropy effects, that is, affecting multiple phenotypes, and the ultimate goal of uncovering the underlying g...

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Main Authors: Qiong Yang, Yuanjia Wang
Format: Article
Language:English
Published: Wiley 2012-01-01
Series:Journal of Probability and Statistics
Online Access:http://dx.doi.org/10.1155/2012/652569
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author Qiong Yang
Yuanjia Wang
author_facet Qiong Yang
Yuanjia Wang
author_sort Qiong Yang
collection DOAJ
description Multivariate phenotypes are frequently encountered in genetic association studies. The purpose of analyzing multivariate phenotypes usually includes discovery of novel genetic variants of pleiotropy effects, that is, affecting multiple phenotypes, and the ultimate goal of uncovering the underlying genetic mechanism. In recent years, there have been new method development and application of existing statistical methods to such phenotypes. In this paper, we provide a review of the available methods for analyzing association between a single marker and a multivariate phenotype consisting of the same type of components (e.g., all continuous or all categorical) or different types of components (e.g., some are continuous and others are categorical). We also reviewed causal inference methods designed to test whether the detected association with the multivariate phenotype is truly pleiotropy or the genetic marker exerts its effects on some phenotypes through affecting the others.
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institution Kabale University
issn 1687-952X
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language English
publishDate 2012-01-01
publisher Wiley
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series Journal of Probability and Statistics
spelling doaj-art-005d70e8dff343fb8a42ff8c32d308882025-02-03T07:25:31ZengWileyJournal of Probability and Statistics1687-952X1687-95382012-01-01201210.1155/2012/652569652569Methods for Analyzing Multivariate Phenotypes in Genetic Association StudiesQiong Yang0Yuanjia Wang1Department of Biostatistics, Boston University School of Public Health, 810 Mass Avenue, Boston, MA 02118, USADepartment of Biostatistics, Mailman School of Public Health, Columbia University, New York, NY 10027, USAMultivariate phenotypes are frequently encountered in genetic association studies. The purpose of analyzing multivariate phenotypes usually includes discovery of novel genetic variants of pleiotropy effects, that is, affecting multiple phenotypes, and the ultimate goal of uncovering the underlying genetic mechanism. In recent years, there have been new method development and application of existing statistical methods to such phenotypes. In this paper, we provide a review of the available methods for analyzing association between a single marker and a multivariate phenotype consisting of the same type of components (e.g., all continuous or all categorical) or different types of components (e.g., some are continuous and others are categorical). We also reviewed causal inference methods designed to test whether the detected association with the multivariate phenotype is truly pleiotropy or the genetic marker exerts its effects on some phenotypes through affecting the others.http://dx.doi.org/10.1155/2012/652569
spellingShingle Qiong Yang
Yuanjia Wang
Methods for Analyzing Multivariate Phenotypes in Genetic Association Studies
Journal of Probability and Statistics
title Methods for Analyzing Multivariate Phenotypes in Genetic Association Studies
title_full Methods for Analyzing Multivariate Phenotypes in Genetic Association Studies
title_fullStr Methods for Analyzing Multivariate Phenotypes in Genetic Association Studies
title_full_unstemmed Methods for Analyzing Multivariate Phenotypes in Genetic Association Studies
title_short Methods for Analyzing Multivariate Phenotypes in Genetic Association Studies
title_sort methods for analyzing multivariate phenotypes in genetic association studies
url http://dx.doi.org/10.1155/2012/652569
work_keys_str_mv AT qiongyang methodsforanalyzingmultivariatephenotypesingeneticassociationstudies
AT yuanjiawang methodsforanalyzingmultivariatephenotypesingeneticassociationstudies