FINEMAP: efficient variable selection using summary data from genome-wide association studies.

ABSTRACT:

Motivation

The goal of fine-mapping in genomic regions associated with complex diseases and traits is to identify causal variants that point to molecular mechanisms behind the associations. Recent fine-mapping methods using summary data from genome-wide association studies rely on exhaustive search through all possible causal configurations, which is computationally expensive.

Results

We introduce FINEMAP, a software package to efficiently explore a set of the most important causal configurations of the region via a shotgun stochastic search algorithm. We show that FINEMAP produces accurate results in a fraction of processing time of existing approaches and is therefore a promising tool for analyzing growing amounts of data produced in genome-wide association studies and eme

SUBMITTER: Benner C 

PROVIDER: S-EPMC4866522 | biostudies-literature | 2016 May

REPOSITORIES: biostudies-literature