Learning probabilistic models of hydrogen bond stability from molecular dynamics simulation trajectories |
| |
Authors: | Chikalov Igor Yao Peggy Moshkov Mikhail Latombe Jean-Claude |
| |
Affiliation: | 1. Department of Biomathematics, UCLA, Los Angeles, California, USA 2. Department of Human Genetics, UCLA, Los Angeles, California, USA 3. Department of Statistics, UCLA, Los Angeles, California, USA
|
| |
Abstract: | Background The estimation of individual ancestry from genetic data has become essential to applied population genetics and genetic epidemiology. Software programs for calculating ancestry estimates have become essential tools in the geneticist's analytic arsenal. Results Here we describe four enhancements to ADMIXTURE, a high-performance tool for estimating individual ancestries and population allele frequencies from SNP (single nucleotide polymorphism) data. First, ADMIXTURE can be used to estimate the number of underlying populations through cross-validation. Second, individuals of known ancestry can be exploited in supervised learning to yield more precise ancestry estimates. Third, by penalizing small admixture coefficients for each individual, one can encourage model parsimony, often yielding more interpretable results for small datasets or datasets with large numbers of ancestral populations. Finally, by exploiting multiple processors, large datasets can be analyzed even more rapidly. Conclusions The enhancements we have described make ADMIXTURE a more accurate, efficient, and versatile tool for ancestry estimation. |
| |
Keywords: | |
本文献已被 SpringerLink 等数据库收录! |
|