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bioRxiv · 10.1101/027342

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

Christian Benner·Chris C.A. Spencer·Samuli Ripatti·Matti Pirinen
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Abstract

MotivationThe 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.\n\nResultsWe 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.\n\nAvailabilityFINEMAP v1.0 is freely available for Mac OS X and Linux at http://www.christianbenner.com.\n\nContact: christian.benner@helsinki.fi, matti.pirinen@helsinki.fi

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Christian Benner, Chris C.A. Spencer, Samuli Ripatti, Matti Pirinen. 2015-09-22. FINEMAP: Efficient variable selection using summary data from genome-wide association studies. https://doi.org/10.1101/027342

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