Enhancements to the ADMIXTURE algorithm for individual ancestry estimation

BMC Bioinformatics

Software

David H Alexander¹  Kenneth Lange² 

[1] Department of Biomathematics, UCLA, Los Angeles, California, USA;Department of Biomathematics, UCLA, Los Angeles, California, USA;Department of Human Genetics, UCLA, Los Angeles, California, USA;Department of Statistics, UCLA, Los Angeles, California, USA;

关键词: Ancestral Population;    Unsupervised Analysis;    Population Allele Frequency;    Supervise Analysis;    Individual Ancestry;   

DOI  :  10.1186/1471-2105-12-246

 received in 2011-02-02, accepted in 2011-06-18,  发布年份 2011

来源: Springer

【 摘 要 】

BackgroundThe 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.ResultsHere 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.ConclusionsThe enhancements we have described make ADMIXTURE a more accurate, efficient, and versatile tool for ancestry estimation.

【 授权许可】

CC BY   
© Alexander and Lange; licensee BioMed Central Ltd. 2011