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NAM: association studies in multiple populations

Alencar XavierShizhong Xu3 Department of Plant Science, University of California, Riverside, CA 92521, USAWilliam M. Muir2 Department of Animal Science, Purdue University, West Lafayette, IN 47907 andKaty Martin Rainey
2015en
ABI

Abstract

MOTIVATION: Mixed linear models provide important techniques for performing genome-wide association studies. However, current models have pitfalls associated with their strong assumptions. Here, we propose a new implementation designed to overcome some of these pitfalls using an empirical Bayes algorithm. RESULTS: Here we introduce NAM, an R package that allows user to take into account prior information regarding population stratification to relax the linkage phase assumption of current methods. It allows markers to be treated as a random effect to increase the resolution, and uses a sliding-window strategy to increase power and avoid double fitting markers into the model. AVAILABILITY AND IMPLEMENTATION: NAM is an R package available in the CRAN repository. It can be installed in R by typing install.packages ('NAM'). CONTACT: [email protected]. SUPPLEMENTARY INFORMATION: Supplementary date are available at Bioinformatics online.

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