Document Detail


Mixed linear model approach adapted for genome-wide association studies.
MedLine Citation:
PMID:  20208535     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
Mixed linear model (MLM) methods have proven useful in controlling for population structure and relatedness within genome-wide association studies. However, MLM-based methods can be computationally challenging for large datasets. We report a compression approach, called 'compressed MLM', that decreases the effective sample size of such datasets by clustering individuals into groups. We also present a complementary approach, 'population parameters previously determined' (P3D), that eliminates the need to re-compute variance components. We applied these two methods both independently and combined in selected genetic association datasets from human, dog and maize. The joint implementation of these two methods markedly reduced computing time and either maintained or improved statistical power. We used simulations to demonstrate the usefulness in controlling for substructure in genetic association datasets for a range of species and genetic architectures. We have made these methods available within an implementation of the software program TASSEL.
Authors:
Zhiwu Zhang; Elhan Ersoz; Chao-Qiang Lai; Rory J Todhunter; Hemant K Tiwari; Michael A Gore; Peter J Bradbury; Jianming Yu; Donna K Arnett; Jose M Ordovas; Edward S Buckler
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Publication Detail:
Type:  Journal Article; Research Support, N.I.H., Extramural; Research Support, U.S. Gov't, Non-P.H.S.     Date:  2010-03-07
Journal Detail:
Title:  Nature genetics     Volume:  42     ISSN:  1546-1718     ISO Abbreviation:  Nat. Genet.     Publication Date:  2010 Apr 
Date Detail:
Created Date:  2010-03-29     Completed Date:  2010-04-16     Revised Date:  2014-09-18    
Medline Journal Info:
Nlm Unique ID:  9216904     Medline TA:  Nat Genet     Country:  United States    
Other Details:
Languages:  eng     Pagination:  355-60     Citation Subset:  IM    
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MeSH Terms
Descriptor/Qualifier:
Family
Genome-Wide Association Study / methods*
Humans
Linear Models*
Population Groups
Software
Grant Support
ID/Acronym/Agency:
1R21AR055228-01A1/AR/NIAMS NIH HHS; 5U01HL072524-06/HL/NHLBI NIH HHS; HL54776/HL/NHLBI NIH HHS; R01 HL054776/HL/NHLBI NIH HHS; R01 HL054776-04/HL/NHLBI NIH HHS; R01 HL054776-05/HL/NHLBI NIH HHS; R01 HL054776-06/HL/NHLBI NIH HHS; R01 HL054776-07/HL/NHLBI NIH HHS; R01 HL054776-08/HL/NHLBI NIH HHS; R01 HL054776-09A1/HL/NHLBI NIH HHS; R01 HL054776-10/HL/NHLBI NIH HHS; R01 HL054776-11/HL/NHLBI NIH HHS; R01 HL054776-12/HL/NHLBI NIH HHS; R01 HL054776-13/HL/NHLBI NIH HHS; U 01 HL72524/HL/NHLBI NIH HHS
Comments/Corrections

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