Comparison between the stochastic search variable selection and the least absolute shrinkage and selection operator for genome-wide association studies of rheumatoid arthritis.

ABSTRACT:

Background

Because multiple loci control complex diseases, there is great interest in testing markers simultaneously instead of one by one. In this paper, we applied two model selection algorithms: the stochastic search variable selection (SSVS) and the least absolute shrinkage and selection operator (LASSO) to two quantitative phenotypes related to rheumatoid arthritis (RA).

Results

The Genetic Analysis Workshop 16 data includes 2,062 unrelated individuals and 545,080 single-nucleotide polymorphism markers from the Illumina 550 k chip. We performed our analyses on the cases as the quantitative phenotype data was not provided for the controls. The performance of the two algorithms was compared. Using sure independence screening as the prescreening procedure, both SSVS and LA

SUBMITTER: Srivastava S 

PROVIDER: S-EPMC2795918 | biostudies-literature | 2009 Dec

REPOSITORIES: biostudies-literature