The sequence kernel association test for the proportional odds model

TY - JOUR

T1 - The sequence kernel association test for the proportional odds model

AU - Yan, Jingxin

AU - Zhang, Xiaoyu

AU - Wang, Shuying

AU - Wang, Jinjuan

AU - Li, Qizhai

N1 - Publisher Copyright: © 2025 The Author(s).

PY - 2025/6/1

Y1 - 2025/6/1

N2 - Motivation The Sequence Kernel Association Test (SKAT) and its extensions are the most popular methods for studying the association between phenotypes and a set of single nucleotide polymorphisms. Their practical application is very wide, but most of these methods are designed for continuous and binary phenotypes. Ordered categorical phenotypes are also very common in practice, so there is an urgent need to develop SKAT-type tests for proportional odds model. Results To accommodate ordered categorical phenotypes, we propose a test named the Sequence Kernel Association Test for the Proportional Odds Model (POM-SKAT). It constructs a score test for the variance of the coefficients of interest using a quasi-likelihood and the P-value is evaluated by approximating the asymptotic distribution of the test statistic with the Pearson Type III distribution. Simulation studies demonstrate that our method performs well and achieves high power in detecting gene-phenotype associations. We apply POM-SKAT to rheumatoid arthritis data provided by Genetic Analysis Workshop 16, identifying multiple relevant gene variants. Availability and implementation Code is available at GitHub (https://github.com/amss-stat/POM-SKAT).

AB - Motivation The Sequence Kernel Association Test (SKAT) and its extensions are the most popular methods for studying the association between phenotypes and a set of single nucleotide polymorphisms. Their practical application is very wide, but most of these methods are designed for continuous and binary phenotypes. Ordered categorical phenotypes are also very common in practice, so there is an urgent need to develop SKAT-type tests for proportional odds model. Results To accommodate ordered categorical phenotypes, we propose a test named the Sequence Kernel Association Test for the Proportional Odds Model (POM-SKAT). It constructs a score test for the variance of the coefficients of interest using a quasi-likelihood and the P-value is evaluated by approximating the asymptotic distribution of the test statistic with the Pearson Type III distribution. Simulation studies demonstrate that our method performs well and achieves high power in detecting gene-phenotype associations. We apply POM-SKAT to rheumatoid arthritis data provided by Genetic Analysis Workshop 16, identifying multiple relevant gene variants. Availability and implementation Code is available at GitHub (https://github.com/amss-stat/POM-SKAT).

UR - https://www.scopus.com/pages/publications/105009541275

U2 - 10.1093/bioinformatics/btaf304

DO - 10.1093/bioinformatics/btaf304

M3 - Article

AN - SCOPUS:105009541275

SN - 1367-4803

VL - 41

JO - Bioinformatics

JF - Bioinformatics

IS - 6

M1 - btaf304

ER -