A logistic regression mixture model for interval mapping of genetic trait loci affecting binary phenotypes.

ABSTRACT: Often in genetic research, presence or absence of a disease is affected by not only the trait locus genotypes but also some covariates. The finite logistic regression mixture models and the methods under the models are developed for detection of a binary trait locus (BTL) through an interval-mapping procedure. The maximum-likelihood estimates (MLEs) of the logistic regression parameters are asymptotically unbiased. The null asymptotic distributions of the likelihood-ratio test (LRT) statistics for detection of a BTL are found to be given by the supremum of a chi2-process. The limiting null distributions are free of the null model parameters and are determined explicitly through only four (backcross case) or nine (intercross case) independent standard normal random variables. Therefore a th

SUBMITTER: Deng W 

PROVIDER: S-EPMC1456231 | biostudies-literature | 2006 Feb

REPOSITORIES: biostudies-literature