Revisiting the Briggs Ancient DNA Damage Model: A Fast Maximum Likelihood Method to Estimate Post-Mortem Damage.

Area of Science:

• Ancient DNA analysis
• Bioinformatics
• Computational biology

Background:

• Authenticating ancient DNA (aDNA) is critical for reliable downstream analysis.
• Ancient DNA exhibits characteristic post-mortem damage (PMD), such as cytosine deamination and nicks.
• Existing methods for PMD quantification and aDNA authentication can be slow or less accurate.

Purpose of the Study:

• To present ngsBriggs, a novel, fast, and accurate method for quantifying PMD in aDNA.
• To improve the classification accuracy of ancient versus modern DNA reads for better data decontamination.
• To provide a practical tool for researchers analyzing ancient DNA samples.

Main Methods:

• Development of a fast, multithreaded program, ngsBriggs.
• Implementation of a multinomial model with maximum likelihood fit to estimate Briggs ancient damage model parameters (Briggs parameters).
• Extension of the Briggs model to accommodate contemporary sequencing platforms and various contamination levels.

Main Results:

• ngsBriggs accurately quantifies PMD by estimating Briggs parameters for both single and double-stranded DNA.
• The method demonstrates accurate parameter estimation across diverse contamination levels.
• Classification of reads into ancient or modern is significantly more accurate with ngsBriggs compared to existing methods.
• ngsBriggs offers substantial speed improvements over state-of-the-art methods.

Conclusions:

• ngsBriggs provides a practical and accurate solution for quantifying PMD in ancient DNA.
• The tool enhances the reliability of ancient DNA authentication and data quality.
• ngsBriggs represents a significant advancement in computational tools for ancient DNA research.