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Methods for Analyzing Multivariate Phenotypes in Genetic Association Studies.

Qiong Yang1, Yuanjia Wang2

  • 1Department of Biostatistics, Boston University School of Public Health, 810 Mass Avenue, Boston, MA 02118, USA.

Journal of Probability and Statistics
|April 22, 2014
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Summary
This summary is machine-generated.

This review covers statistical methods for analyzing genetic associations with multiple traits (multivariate phenotypes). It explores methods for discovering pleiotropy and understanding genetic mechanisms influencing several traits.

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Area of Science:

  • Genetics
  • Biostatistics
  • Statistical Genetics

Background:

  • Multivariate phenotypes are common in genetic association studies.
  • Analyzing these phenotypes aids in discovering pleiotropic genetic variants and understanding underlying genetic mechanisms.

Purpose of the Study:

  • To review existing and novel statistical methods for analyzing associations between genetic markers and multivariate phenotypes.
  • To review causal inference methods for distinguishing true pleiotropy from mediated effects.

Main Methods:

  • Review of statistical methods for single marker association with multivariate phenotypes.
  • Review of causal inference techniques for pleiotropy assessment.

Main Results:

  • The paper categorizes methods based on phenotype component types (continuous, categorical, or mixed).
  • It discusses approaches to differentiate direct pleiotropic effects from indirect, mediated effects.

Conclusions:

  • A comprehensive overview of analytical approaches for multivariate phenotypes is provided.
  • The review aids researchers in selecting appropriate methods for genetic association studies involving complex traits.