A powerful method to test associations between ordinal traits and genotypes

Jinjuan Wang, Juan Ding, Shouyou Huang, Qizhai Li*, Dongdong Pan

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)

Abstract

The methods commonly used to test the associations between ordinal phenotypes and genotypes often treat either the ordinal phenotype or the genotype as continuous variables. To address limitations of these approaches, we propose a model where both the ordinal phenotype and the genotype are viewed as manifestations of an underlying multivariate normal random variable. The proposed method allows modeling the ordinal phenotype, the genotype and covariates jointly. We employ the generalized estimating equation technique and M-estimation theory to estimate the model parameters and deduce the corresponding asymptotic distribution. Numerical simulations and real data applications are also conducted to compare the performance of the proposed method with those of methods based on the logit and probit models. Even though there may be potential limitations in Type I error rate control for our method, the gains in power can prove its practical value in case of exactly ordinal phenotypes.

Original languageEnglish
Pages (from-to)2573-2579
Number of pages7
JournalG3: Genes, Genomes, Genetics
Volume9
Issue number8
DOIs
Publication statusPublished - 1 Aug 2019
Externally publishedYes

Keywords

  • Association study
  • Equation
  • Estimating
  • Generalized
  • Latent normal
  • M-estimation
  • Ordinal
  • Phenotype
  • Variate

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