From Statistical Genetics to Predictive Models in Personalized Medicine

FaST linear mixed models for genome-wide association studies

author: Christoph Lippert, Max Planck Institute for Biological Cybernetics, Max Planck Institute
published: Jan. 23, 2012, recorded: December 2011, views: 4921

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Description

We describe FaST-LMM, a linear mixed model for genome-wide association studies that scales linearly in the number of individuals in both runtime and memory use. Our algorithm is an order of magnitude faster than current efficient algorithms (EMMAX/P3D) on Wellcome Trust data with 15,000 individuals. On synthetic data, FaST-LMM can analyze 120,000 individuals in just a few hours, whereas the current algorithms are unable to analyze even 20,000 individuals (http://fastlmm.codeplex.com).

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