Dataset Information
FINEMAP: efficient variable selection using summary data from genome-wide association studies.
Ontology highlight
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.comContact
: christian.benner@helsinki.fi or matti.pirinen@helsinki.fi.
SUBMITTER: Benner C
PROVIDER: S-EPMC4866522 | biostudies-literature | 2016 May
REPOSITORIES: biostudies-literature
Publications
FINEMAP: efficient variable selection using summary data from genome-wide association studies.
Bioinformatics (Oxford, England) 20160114 10
<h4>Motivation</h4>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.<h4>Results</h4>We introduce FINEMAP, a software package to efficiently explore a set of the most important causa ...[more]