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Genome-Wide Association Studies shed light on the identification of genes underlying human diseases and agriculturally important traits. This potential has been shadowed by false positive findings. The Mixed Linear Model (MLM) method is flexible enough to simultaneously incorporate population structure and cryptic relationships to reduce false positives. However, its intensive computational burden is prohibitive in practice, especially for large samples. The newly developed algorithm, FaST-LMM,doi:10.1371/journal.pone.0107684 pmid:25247812 pmcid:PMC4172578 fatcat:eddmwp3f6raw5kqhhzm6m3zkde