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AdDeam: a fast and scalable tool for estimating and clustering reference-level damage profiles.

Louis Kraft1, Thorfinn Sand Korneliussen2, Peter Wad Sackett1

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Summary

AdDeam is a new tool for analyzing ancient DNA (aDNA) damage patterns, streamlining authenticity assessment and contaminant detection. It rapidly estimates and clusters DNA damage profiles, simplifying the identification of ancient fragments and potential outliers in large datasets.

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Area of Science:

  • Ancient DNA research
  • Bioinformatics
  • Genomics

Background:

  • DNA damage patterns are crucial for authenticating ancient DNA (aDNA) and detecting contamination.
  • Current methods for analyzing damage profiles in metagenomic studies are often time-consuming and lack efficient clustering capabilities.

Purpose of the Study:

  • To develop a computational tool, AdDeam, for rapid estimation and clustering of DNA damage patterns in aDNA.
  • To streamline the identification of authentic ancient fragments, contaminants, and outliers in large-scale metagenomic datasets.

Main Methods:

  • AdDeam processes aligned aDNA fragments, computes damage patterns, and clusters them using a combination of Python and C++.
  • The tool outputs representative damage profiles per cluster, sample-to-cluster probabilities, and Principal Component Analysis for visualization.

Main Results:

  • AdDeam effectively distinguishes varying levels of DNA damage, including those from uracil-DNA glycosylase treatment and sample-specific historical damage.
  • The tool accurately differentiates between ancient and modern DNA fragments within contigs, aiding in aDNA authentication.

Conclusions:

  • AdDeam provides a robust framework for efficient aDNA authentication and contaminant screening.
  • The tool facilitates large-scale ancient DNA analyses by simplifying the interpretation of damage profiles.