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 emerging sequencing projects. AVAILABILITY AND IMPLEMENTATION:FINEMAP v1.0 is freely available for Mac OS X and Linux at http://www.christianbenner.com CONTACT:: [e-mail] or [e-mail].

SUBMITTER: Benner C 

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

REPOSITORIES: biostudies-literature