期刊
HUMAN BIOLOGY
卷 84, 期 4, 页码 343-364出版社
WAYNE STATE UNIV PRESS
DOI: 10.3378/027.084.0401
关键词
ADMIXTURE; PRINCIPAL COMPONENTS ANALYSIS (PCA); LOCAL ANCESTRY DECONVOLUTION; HAPLOTYPE-BASED; FORWARD-BACKWARD ALGORITHM
资金
- NSF [0516310]
- Division Of Environmental Biology
- Direct For Biological Sciences [0516310] Funding Source: National Science Foundation
Identifying ancestry along each chromosome in admixed individuals provides a wealth of information for understanding the population genetic history of admixture events and is valuable for admixture mapping and identifying recent targets of selection. We present PCAdmix (available at https://sites.google.com/site/pcadmix/home), a Principal Components-based algorithm for determining ancestry along each chromosome from a high-density, genome-wide set of phased single-nucleotide polymorphism (SNP) genotypes of admixed individuals. We compare our method to HAPMIX on simulated data from two ancestral populations, and we find high concordance between the methods. Our method also has better accuracy than LAMP when applied to three-population admixture, a situation as yet unaddressed by HAPMIX. Finally, we apply our method to a data set of four Latino populations with European, African, and Native American ancestry. We find evidence of assortative mating in each of the four populations, and we identify regions of shared ancestry that may be recent targets of selection and could serve as candidate regions for admixture-based association mapping.
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