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Bioinformatics. 2015 Dec 1;31(23):3862-4. doi: 10.1093/bioinformatics/btv448. Epub 2015 Aug 4.

NAM: association studies in multiple populations.

Author information

1
Department of Agronomy and.
2
Department of Plant Science, University of California, Riverside, CA 92521, USA.
3
Department of Animal Science, Purdue University, West Lafayette, IN 47907 and.

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:

krainey@purdue.edu.

SUPPLEMENTARY INFORMATION:

Supplementary date are available at Bioinformatics online.

PMID:
26243017
DOI:
10.1093/bioinformatics/btv448
[Indexed for MEDLINE]

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