Gene-level association analysis of ordinal traits with functional ordinal logistic regressions.

ABSTRACT: In this paper, we develop functional ordinal logistic regression (FOLR) models to perform gene-based analysis of ordinal traits. In the proposed FOLR models, genetic variant data are viewed as stochastic functions of physical positions and the genetic effects are treated as a function of physical positions. The FOLR models are built upon functional data analysis which can be revised to analyze the ordinal traits and high dimension genetic data. The proposed methods are capable of dealing with dense genotype data which is usually encountered in analyzing the next-generation sequencing data. The methods are flexible and can analyze three types of genetic data: (1) rare variants only, (2) common variants only, and (3) a combination of rare and common variants. Simulation studies show that the

SUBMITTER: Chiu CY 

PROVIDER: S-EPMC11550389 | biostudies-literature | 2022 Jul

REPOSITORIES: biostudies-literature