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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: : christian.benner@helsinki.fi or matti.pirinen@helsinki.fi.

Original publication

DOI

10.1093/bioinformatics/btw018

Type

Journal article

Journal

Bioinformatics

Publication Date

15/05/2016

Volume

32

Pages

1493 - 1501

Keywords

Algorithms, Genome, Genome-Wide Association Study, Genomics, Polymorphism, Single Nucleotide, Software