title: A SUPER powerful method for genome wide association study.
abstract: 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, solved the computational problem, but requires that the number of SNPs be less than the number of individuals to derive a rank-reduced relationship. This restriction potentially leads to less statistical power when compared to using all SNPs. We developed a method to extract a small subset of SNPs and use them in FaST-LMM. This method not only retains the computational advantage of FaST-LMM, but also remarkably increases statistical power even when compared to using the entire set of SNPs. We named the method SUPER (Settlement of MLM Under Progressively Exclusive Relationship) and made it available within an implementation of the GAPIT software package.
authors.affiliation: School of Agriculture and Biology, Shanghai Jiaotong University, Shanghai, China.
authors.forename: Qishan
authors.initials: Q
authors.lastname: Wang
authors.affiliation: National Maize Improvement Center of China, China Agricultural University, Beijing, China.
authors.forename: Feng
authors.initials: F
authors.lastname: Tian
authors.affiliation: School of Agriculture and Biology, Shanghai Jiaotong University, Shanghai, China.
authors.forename: Yuchun
authors.initials: Y
authors.lastname: Pan
authors.affiliation: United States Department of Agriculture (USDA) - Agricultural Research Service (ARS), Ithaca, New York, United States of America; Institute for Genomic Diversity, Cornell University, Ithaca, New York, United States of America.
authors.forename: Edward S
authors.initials: ES
authors.lastname: Buckler
authors.affiliation: Institute for Genomic Diversity, Cornell University, Ithaca, New York, United States of America; Department of Animal Science, Northeast Agricultural University, Harbin, China; Department of Crop and Soil Science, Washington State University, Pullman, Washington, United States of America.
authors.forename: Zhiwu
authors.initials: Z
authors.lastname: Zhang
mesh_terms: D000465:Algorithms; D000818:Animals; D005819:Genetic Markers; D016678:Genome; D055106:Genome-Wide Association Study / Q000379:methods*; D006801:Humans; D016014:Linear Models; D019684:Magnoliopsida / Q000235:genetics; D020641:Polymorphism, Single Nucleotide; D012984:Software
chemical_list: D005819:Genetic Markers