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FALCON2: compression-based metagenomic classification of ancient viruses.

Luis L Marques1,2,3, Armando J Pinho1,2,3, Diogo Pratas1,2,3,4

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|March 30, 2026
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FALCON2, a novel metagenomic classifier, accurately analyzes degraded ancient DNA (aDNA) by using compression and position-aware models. It significantly outperforms existing tools on short, damaged reads, enabling new paleogenomic insights.

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Area of Science:

  • Paleogenomics
  • Bioinformatics
  • Computational Biology

Background:

  • Ancient DNA (aDNA) presents significant challenges for taxonomic classification due to fragmentation, deamination, and contamination.
  • Conventional metagenomic classifiers struggle with short, damaged aDNA reads, limiting paleogenomic analyses.

Purpose of the Study:

  • To develop and present FALCON2, a compression-based metagenomic classifier designed for high accuracy on degraded aDNA.
  • To improve upon existing methods for taxonomic classification of ancient viral sequences.

Main Methods:

  • Leverages position-aware finite-context models for classification.
  • Consolidates FALCON-meta capabilities into a unified executable with enhanced features.
  • Includes model persistence, direct compressed input processing, and optional pre-filtering.

Main Results:

  • FALCON2 achieved superior performance on simulated viral datasets, with an AUC-ROC of 0.999, AUPRC of 0.968, and F1-score of 0.918.
  • Outperformed Centrifuge, Kraken2, and CLARK-S, particularly on ultra-short reads (20-40 bp).
  • Pre-filtering improved precision by 10 percentage points with minimal recall loss.

Conclusions:

  • FALCON2 offers a robust solution for taxonomic classification of challenging ancient DNA samples.
  • The tool enhances paleogenomic research by enabling accurate analysis of degraded and contaminated sequences.
  • FALCON2 is efficient, requiring 4-8 GB RAM for typical analyses and is freely available.