A likelihood method for estimating present-day human contamination in ancient male samples using low-depth...

Area of Science:

• Genetics
• Bioinformatics
• Paleogenomics

Background:

• Ancient DNA (aDNA) research faces challenges with modern human DNA contamination, complicating analysis of ancient human genomes.
• Existing computational methods for contamination assessment are often specific to empirical studies and may not perform well on low-depth nuclear data common in aDNA datasets.

Purpose of the Study:

• To develop and validate a novel X-chromosome-based maximum likelihood method for estimating present-day human contamination in low-depth sequencing data from male individuals.
• To ensure the method is suitable for general use and performs accurately under typical ancient human DNA research conditions.

Main Methods:

• Development of a new X-chromosome-based maximum likelihood method for contamination estimation.
• Implementation in C++ and R for broad accessibility.
• Extensive simulations to assess performance and compare with existing nuclear data-based methods.

Main Results:

• The new method provides accurate contamination estimates for male aDNA with X-chromosome coverage as low as 0.5× (contamination < 25%).
• Existing methods can yield unusable or underestimated contamination values for low-depth data.
• The method remains effective with closely related populations and increased error rates, running in under 5 minutes.

Conclusions:

• The developed X-chromosome method offers a robust and efficient solution for human contamination estimation in low-depth male aDNA.
• This tool is applicable to large-scale ancient genomics studies, improving data reliability.