YHap: A population model for probabilistic assignment of Y haplogroups from re-sequencing data

Zhang, Fan, Chen, Ruoyan, Liu, Dongbing, Yao, Xiaotian, Li, Guoqing, Jin, Yabin, Yu, Chang, Li, Yingrui and Coin, Lachlan J. M. (2013) YHap: A population model for probabilistic assignment of Y haplogroups from re-sequencing data. BMC Bioinformatics, 14 1: 331.1-331.4. doi:10.1186/1471-2105-14-331


Author Zhang, Fan
Chen, Ruoyan
Liu, Dongbing
Yao, Xiaotian
Li, Guoqing
Jin, Yabin
Yu, Chang
Li, Yingrui
Coin, Lachlan J. M.
Title YHap: A population model for probabilistic assignment of Y haplogroups from re-sequencing data
Journal name BMC Bioinformatics   Check publisher's open access policy
ISSN 1471-2105
Publication date 2013-11-19
Sub-type Article (original research)
DOI 10.1186/1471-2105-14-331
Open Access Status DOI
Volume 14
Issue 1
Start page 331.1
End page 331.4
Total pages 5
Place of publication London, United Kingdom
Publisher BioMed Central Ltd
Language eng
Subject 1303 Specialist Studies in Education
1312 Molecular Biology
1706 Computer Science Applications
2604 Applied Mathematics
1315 Structural Biology
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.
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: Official 2014 Collection
Institute for Molecular Bioscience - Publications
 
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Created: Tue, 17 Dec 2013, 00:49:59 EST by Susan Allen on behalf of Institute for Molecular Bioscience