A unified mixed-model method for association mapping that accounts for multiple levels of relatedness

@article{Yu2006AUM,
  title={A unified mixed-model method for association mapping that accounts for multiple levels of relatedness},
  author={Jianming Yu and Gael Pressoir and William H. Briggs and Irie Vroh Bi and Masanori Yamasaki and John Doebley and Michael D. McMullen and Brandon S. Gaut and Dahlia M. Nielsen and James B Holland and Stephen Kresovich and Edward S. Buckler},
  journal={Nature Genetics},
  year={2006},
  volume={38},
  pages={203-208}
}
As population structure can result in spurious associations, it has constrained the use of association studies in human and plant genetics. Association mapping, however, holds great promise if true signals of functional association can be separated from the vast number of false signals generated by population structure. We have developed a unified mixed-model approach to account for multiple levels of relatedness simultaneously as detected by random genetic markers. We applied this new approach… CONTINUE READING
Highly Influential
This paper has highly influenced 234 other papers. REVIEW HIGHLY INFLUENTIAL CITATIONS