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CC0 V1.0, Open Access
Journal article
Iterative Usage of Fixed and Random Effect Models for Powerful and Efficient Genome-Wide Association Studies
PLoS genetics, Vol.12(2), pp.e1005767-e1005767
02/2016
Handle:
https://hdl.handle.net/2376/105814
PMCID: PMC4734661
PMID: 26828793
Abstract
False positives in a Genome-Wide Association Study (GWAS) can be effectively controlled by a fixed effect and random effect Mixed Linear Model (MLM) that incorporates population structure and kinship among individuals to adjust association tests on markers; however, the adjustment also compromises true positives. The modified MLM method, Multiple Loci Linear Mixed Model (MLMM), incorporates multiple markers simultaneously as covariates in a stepwise MLM to partially remove the confounding between testing markers and kinship. To completely eliminate the confounding, we divided MLMM into two parts: Fixed Effect Model (FEM) and a Random Effect Model (REM) and use them iteratively. FEM contains testing markers, one at a time, and multiple associated markers as covariates to control false positives. To avoid model over-fitting problem in FEM, the associated markers are estimated in REM by using them to define kinship. The P values of testing markers and the associated markers are unified at each iteration. We named the new method as Fixed and random model Circulating Probability Unification (FarmCPU). Both real and simulated data analyses demonstrated that FarmCPU improves statistical power compared to current methods. Additional benefits include an efficient computing time that is linear to both number of individuals and number of markers. Now, a dataset with half million individuals and half million markers can be analyzed within three days.
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Details
- Title
- Iterative Usage of Fixed and Random Effect Models for Powerful and Efficient Genome-Wide Association Studies
- Creators
- Xiaolei Liu - Huazhong Agricultural UniversityMeng Huang - Department of Crop and Soil Sciences, Washington State University, Pullman, Washington, United States of AmericaBin Fan - Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction, Ministry of Education, College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, Hubei, ChinaEdward S Buckler - United States Department of Agriculture (USDA)-Agricultural Research Service (ARS), Ithaca, New York, United States of AmericaZhiwu Zhang - Department of Animal Sciences, Northeast Agricultural University, Harbin, Heilongjiang, China
- Publication Details
- PLoS genetics, Vol.12(2), pp.e1005767-e1005767
- Academic Unit
- Department of Crop and Soil Sciences
- Publisher
- United States
- Identifiers
- 99900546808901842
- Language
- English
- Resource Type
- Journal article