GWASinlps: non-local prior based iterative SNP selection tool for genome-wide association studies.

ABSTRACT:

Motivation

Multiple marker analysis of the genome-wide association study (GWAS) data has gained ample attention in recent years. However, because of the ultra high-dimensionality of GWAS data, such analysis is challenging. Frequently used penalized regression methods often lead to large number of false positives, whereas Bayesian methods are computationally very expensive. Motivated to ameliorate these issues simultaneously, we consider the novel approach of using non-local priors in an iterative variable selection framework.

Results

We develop a variable selection method, named, iterative non-local prior based selection for GWAS, or GWASinlps, that combines, in an iterative variable selection framework, the computational efficiency of the screen-and-select approach based on

SUBMITTER: Sanyal N 

PROVIDER: S-EPMC6298063 | biostudies-literature | 2019 Jan

REPOSITORIES: biostudies-literature