Journal
GENETICS
Volume 196, Issue 4, Pages 973-+Publisher
GENETICS SOCIETY AMERICA
DOI: 10.1534/genetics.113.160572
Keywords
inference of population structure; ancestry coefficients; nonnegative matrix factorization algorithms
Categories
Funding
- la Region Rhone-Alpes
- Grenoble Institute of Technology
Ask authors/readers for more resources
Inference of individual ancestry coefficients, which is important for population genetic and association studies, is commonly performed using computer-intensive likelihood algorithms. With the availability of large population genomic data sets, fast versions of likelihood algorithms have attracted considerable attention. Reducing the computational burden of estimation algorithms remains, however, a major challenge. Here, we present a fast and efficient method for estimating individual ancestry coefficients based on sparse nonnegative matrix factorization algorithms. We implemented our method in the computer program sNMF and applied it to human and plant data sets. The performances of sNMF were then compared to the likelihood algorithm implemented in the computer program ADMIXTURE. Without loss of accuracy, sNMF computed estimates of ancestry coefficients with runtimes similar to 10-30 times shorter than those of ADMIXTURE.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available