Evidence map›Paper›PMID 40574466›Full record

ArticleBioinformatics (Oxford, England)2025

The sequence kernel association test for the proportional odds model.

Jingxin Yan, Xiaoyu Zhang, Shuying Wang, Jinjuan Wang, Qizhai Li

Abstract read
In one paragraph

Article in Bioinformatics (Oxford, England), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Jingxin YanState Key Laboratory of Mathematical Sciences, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100190, China.
Xiaoyu ZhangState Key Laboratory of Mathematical Sciences, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100190, China.
Shuying WangSchool of Mathematics and Statistics, Changchun University of Technology, Changchun 130012, China.
Jinjuan WangSchool of Mathematics and Statistics, Beijing Institute of Technology, Beijing 100081, China.ORCID 0000-0002-4320-8528
Qizhai LiState Key Laboratory of Mathematical Sciences, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100190, China.ORCID 0000-0002-3325-8265

Funding

National Natural Science Foundation of China 12288201National Natural Science Foundation of China 12325110
6 · The paper itself

Abstract

motivationThe 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.

resultsTo 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).

Indexed as

Computational BiologyModels, GeneticPolymorphism, Single NucleotideAlgorithmsArthritis, RheumatoidComputer SimulationGenetic Association StudiesHumansPhenotypeSoftware

Identifiers

PMID40574466
PMCPMC12202753

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