title: FaST linear mixed models for genome-wide association studies.
abstract: We describe factored spectrally transformed linear mixed models (FaST-LMM), an algorithm for genome-wide association studies (GWAS) that scales linearly with cohort size in both run time and memory use. On Wellcome Trust data for 15,000 individuals, FaST-LMM ran an order of magnitude faster than current efficient algorithms. Our algorithm can analyze data for 120,000 individuals in just a few hours, whereas current algorithms fail on data for even 20,000 individuals (http://mscompbio.codeplex.com/).
authors: Microsoft Research, Los Angeles, California, USA. christoph.lippert@tuebingen.mpg.de
authors: Christoph
authors: C
authors: Lippert
authors: Jennifer
authors: J
authors: Listgarten
authors: Ying
authors: Y
authors: Liu
authors: Carl M
authors: CM
authors: Kadie
authors: Robert I
authors: RI
authors: Davidson
authors: David
authors: D
authors: Heckerman
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D055106:Genome-Wide Association Study; D008957:Models, Genetic; D012984:Software