PLMET: A Novel Pseudolikelihood-Based EM Test for Homogeneity in Generalilzed Exponential Tilt Mixture Models.

ABSTRACT: Motivated by analyses of DNA methylation data, we propose a semiparametric mixture model, namely the generalized exponential tilt mixture model, to account for heterogeneity between differentially methylated and non-differentially methylated subjects in the cancer group, and capture the differences in higher order moments (e.g. mean and variance) between subjects in cancer and normal groups. A pairwise pseudolikelihood is constructed to eliminate the unknown nuisance function. To circumvent boundary and non-identifiability problems as in parametric mixture models, we modify the pseudolikelihood by adding a penalty function. In addition, the test with simple asymptotic distribution has computational advantages compared with permutation-based test for high-dimensional genetic or epigenetic d

SUBMITTER: Hong C 

PROVIDER: S-EPMC5798902 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature