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

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...

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Detalles Bibliográficos
Autores principales: Zhang, Fan, Chen, Ruoyan, Liu, Dongbing, Yao, Xiaotian, Li, Guoqing, Jin, Yabin, Yu, Chang, Li, Yingrui, Coin, Lachlan JM
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4225519/
https://www.ncbi.nlm.nih.gov/pubmed/24252171
http://dx.doi.org/10.1186/1471-2105-14-331
Descripción
Sumario: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.