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.