Bayesian survival analysis in genetic association studies.

ABSTRACT:

Motivation

Large-scale genetic association studies are carried out with the hope of discovering single nucleotide polymorphisms involved in the etiology of complex diseases. There are several existing methods in the literature for performing this kind of analysis for case-control studies, but less work has been done for prospective cohort studies. We present a Bayesian method for linking markers to censored survival outcome by clustering haplotypes using gene trees. Coalescent-based approaches are promising for LD mapping, as the coalescent offers a good approximation to the evolutionary history of mutations.

Results

We compare the performance of the proposed method in simulation studies to the univariate Cox regression and to dimension reduction methods, and we observe that

SUBMITTER: Tachmazidou I 

PROVIDER: S-EPMC2530885 | biostudies-literature | 2008 Sep

REPOSITORIES: biostudies-literature