Abstract
Background: Y haplogroup analyses are an important component of genealogical reconstruction, population genetic analyses, medical genetics and forensics. These fields are increasingly moving towards use of low-coverage, high throughput sequencing. While there have been methods recently proposed for assignment of Y haplogroups on the basis of high-coverage sequence data, assignment on the basis of low-coverage data remains challenging. Results: We developed a new algorithm, YHap, which uses an imputation framework to jointly predict Y chromosome genotypes and assign Y haplogroups using low coverage population sequence data. We use data from the 1000 genomes project to demonstrate that YHap provides accurate Y haplogroup assignment with less than 2x coverage.Conclusions: Borrowing information across multiple samples within a population using an imputation framework enables accurate Y haplogroup assignment. © 2013 Zhang et al.; licensee BioMed Central Ltd.
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CITATION STYLE
Zhang, F., Chen, R., Liu, D., Yao, X., Li, G., Jin, Y., … Coin, L. J. M. (2013). YHap: A population model for probabilistic assignment of Y haplogroups from re-sequencing data. BMC Bioinformatics, 14(1). https://doi.org/10.1186/1471-2105-14-331
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