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A Powerful Method To Test Associations Between Ordinal Traits and Genotypes.

Jinjuan Wang1,2, Juan Ding3, Shouyou Huang4

  • 1LSC, NCMIS, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, 100190, China.

G3 (Bethesda, Md.)
|June 7, 2019
PubMed
Summary

This study introduces a novel statistical model for analyzing ordinal phenotypes and genotypes, offering improved power for genetic association studies with ordered outcomes.

Keywords:
M-estimationassociation studygeneralized estimating equationlatent normal variateordinal phenotype

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Area of Science:

  • Statistics
  • Genetics
  • Biostatistics

Background:

  • Current methods for genotype-phenotype association often oversimplify ordinal data.
  • Treating ordinal phenotypes or genotypes as continuous variables can lead to loss of information and statistical power.

Purpose of the Study:

  • To propose a new statistical model that jointly analyzes ordinal phenotypes and genotypes.
  • To address the limitations of existing methods by modeling both variables as manifestations of an underlying multivariate normal distribution.

Main Methods:

  • The proposed method models ordinal phenotypes, genotypes, and covariates simultaneously.
  • It utilizes generalized estimating equation (GEE) technique and M-estimation theory for parameter estimation.
  • Asymptotic distribution of the parameters is derived.

Main Results:

  • The new method was compared to logit and probit models via simulations and real data.
  • While Type I error control may have limitations, the proposed method demonstrates increased statistical power for ordinal phenotypes.

Conclusions:

  • The novel multivariate normal model offers practical advantages for genetic association studies with ordinal phenotypes.
  • It provides a more nuanced approach than treating variables as continuous, enhancing power in specific scenarios.