A powerful test for ordinal trait genetic association analysis

Yuan Xue, Jinjuan Wang, Juan Ding, Sanguo Zhang, Qizhai Li*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

Abstract

Response selective sampling design is commonly adopted in genetic epidemiologic study because it can substantially reduce time cost and increase power of identifying deleterious genetic variants predispose to human complex disease comparing with prospective design. The proportional odds model (POM) can be used to fit data obtained by this design. Unlike the logistic regression model, the estimated genetic effect based on POM by taking data as being enrolled prospectively is inconsistent. So the power of resulted Wald test is not satisfactory. The modified POM is suitable to fit this type of data, however, the corresponding Wald test is not optimal when the genetic effect is small. Here, we propose a new association test to handle this issue. Simulation studies show that the proposed test can control the type I error rate correctly and is more powerful than two existing methods. Finally, we applied three tests to Anticyclic Citrullinated Protein Antibody data from Genetic Workshop 16.

Original languageEnglish
Article number20170066
JournalStatistical Applications in Genetics and Molecular Biology
Volume18
Issue number2
DOIs
Publication statusPublished - 2019
Externally publishedYes

Keywords

  • ordinal response
  • power
  • proportional odds model
  • response selective sampling

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