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FaST linear mixed models for genome-wide association studies
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/).
@article{LippertLLKDH2011, title = {FaST linear mixed models for genome-wide association studies}, journal = {Nature Methods}, 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/).}, volume = {8}, number = {10}, pages = {833–835}, month = oct, year = {2011}, slug = {lippertllkdh2011}, author = {Lippert, C. and Listgarten, J. and Liu, Y. and Kadie, CM. and Davidson, RI. and Heckerman, D.}, month_numeric = {10} }