Ordered multinomial regression for genetic association analysis of ordinal phenotypes at Biobank scale.

ABSTRACT: Logistic regression is the primary analysis tool for binary traits in genome-wide association studies (GWAS). Multinomial regression extends logistic regression to multiple categories. However, many phenotypes more naturally take ordered, discrete values. Examples include (a) subtypes defined from multiple sources of clinical information and (b) derived phenotypes generated by specific phenotyping algorithms for electronic health records (EHR). GWAS of ordinal traits have been problematic. Dichotomizing can lead to a range of arbitrary cutoff values, generating inconsistent, hard to interpret results. Using multinomial regression ignores trait value hierarchy and potentially loses power. Treating ordinal data as quantitative can lead to misleading inference. To address these issues, we ana

SUBMITTER: German CA 

PROVIDER: S-EPMC8256450 | biostudies-literature | 2020 Apr

REPOSITORIES: biostudies-literature