Methods for Analyzing Multivariate Phenotypes in Genetic Association Studies

Journal of Probability and Statistics. 2012;2012 DOI 10.1155/2012/652569

 

Journal Homepage

Journal Title: Journal of Probability and Statistics

ISSN: 1687-952X (Print); 1687-9538 (Online)

Publisher: Hindawi Publishing Corporation

LCC Subject Category: Science: Mathematics: Probabilities. Mathematical statistics

Country of publisher: Egypt

Language of fulltext: English

Full-text formats available: PDF, HTML, ePUB

 

AUTHORS

Qiong Yang (Department of Biostatistics, Boston University School of Public Health, 810 Mass Avenue, Boston, MA 02118, USA)
Yuanjia Wang (Department of Biostatistics, Mailman School of Public Health, Columbia University, New York, NY 10027, USA)

EDITORIAL INFORMATION

Blind peer review

Editorial Board

Instructions for authors

Time From Submission to Publication: 18 weeks

 

Abstract | Full Text

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.