NAM: association studies in multiple populations

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


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').


Supplementary information: Supplementary date are available at Bioinformatics online.

MeSH terms

  • Algorithms
  • Bayes Theorem
  • Genetic Linkage
  • Genome-Wide Association Study / methods*
  • Linear Models
  • Software*