TitleBayesian Polynomial Regression Models to Fit Multiple Genetic Models for Quantitative Traits.
Publication TypeJournal Article
Year of Publication2015
AuthorsBae, H, Perls, T, Steinberg, M, Sebastiani, P
JournalBayesian Anal
Date Published03/2015

We present a coherent Bayesian framework for selection of the most likely model from the five genetic models (genotypic, additive, dominant, co-dominant, and recessive) commonly used in genetic association studies. The approach uses a polynomial parameterization of genetic data to simultaneously fit the five models and save computations. We provide a closed-form expression of the marginal likelihood for normally distributed data, and evaluate the performance of the proposed method and existing method through simulated and real genome-wide data sets.

Alternate JournalBayesian Anal
PubMed ID26029316
PubMed Central IDPMC4446790
Grant ListU19 AG023122 / AG / NIA NIH HHS / United States
T32 GM074905 / GM / NIGMS NIH HHS / United States
R21 HL114237 / HL / NHLBI NIH HHS / United States
U01 AG023755 / AG / NIA NIH HHS / United States
R01 HL087681 / HL / NHLBI NIH HHS / United States