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Refining filtering criteria of Kraken family of tools for accurate taxonomic profiling of ancient metagenomic data

Oskolkov, Nikolay LU (2026) In Frontiers in Microbiology 17.
Abstract

Taxonomic profiling is a key component of ancient metagenomic analysis, however it is also susceptible to false-positive identifications. In particular, taxonomic classification tools from the Kraken family, such as Kraken2 and KrakenUniq, are highly sensitive to the choice of filtering options. To address this issue, various filtering approaches have been proposed. In this study, I conduct a comprehensive benchmarking of different filtering strategies for Kraken family of tools using simulated microbial and environmental ancient metagenomic data. I evaluate these approaches based on the balance between sensitivity and specificity of ground truth reconstruction (F1-score), and propose an optimal thresholding strategy tailored to... (More)

Taxonomic profiling is a key component of ancient metagenomic analysis, however it is also susceptible to false-positive identifications. In particular, taxonomic classification tools from the Kraken family, such as Kraken2 and KrakenUniq, are highly sensitive to the choice of filtering options. To address this issue, various filtering approaches have been proposed. In this study, I conduct a comprehensive benchmarking of different filtering strategies for Kraken family of tools using simulated microbial and environmental ancient metagenomic data. I evaluate these approaches based on the balance between sensitivity and specificity of ground truth reconstruction (F1-score), and propose an optimal thresholding strategy tailored to specific sequencing depths in ancient metagenomic datasets.

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Please use this url to cite or link to this publication:
author
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
ancient DNA, ancient metagenomics, ancient pathogens, metagenomics, microbiome profiling
in
Frontiers in Microbiology
volume
17
article number
1603339
publisher
Frontiers Media S. A.
external identifiers
  • pmid:42232910
  • scopus:105041194030
ISSN
1664-302X
DOI
10.3389/fmicb.2026.1603339
language
English
LU publication?
yes
id
5d8121ed-741e-4b17-88bb-d5ca0c56d56b
date added to LUP
2026-07-03 13:21:20
date last changed
2026-08-28 18:24:16
@article{5d8121ed-741e-4b17-88bb-d5ca0c56d56b,
  abstract     = {{<p>Taxonomic profiling is a key component of ancient metagenomic analysis, however it is also susceptible to false-positive identifications. In particular, taxonomic classification tools from the Kraken family, such as Kraken2 and KrakenUniq, are highly sensitive to the choice of filtering options. To address this issue, various filtering approaches have been proposed. In this study, I conduct a comprehensive benchmarking of different filtering strategies for Kraken family of tools using simulated microbial and environmental ancient metagenomic data. I evaluate these approaches based on the balance between sensitivity and specificity of ground truth reconstruction (F1-score), and propose an optimal thresholding strategy tailored to specific sequencing depths in ancient metagenomic datasets.</p>}},
  author       = {{Oskolkov, Nikolay}},
  issn         = {{1664-302X}},
  keywords     = {{ancient DNA; ancient metagenomics; ancient pathogens; metagenomics; microbiome profiling}},
  language     = {{eng}},
  publisher    = {{Frontiers Media S. A.}},
  series       = {{Frontiers in Microbiology}},
  title        = {{Refining filtering criteria of Kraken family of tools for accurate taxonomic profiling of ancient metagenomic data}},
  url          = {{http://dx.doi.org/10.3389/fmicb.2026.1603339}},
  doi          = {{10.3389/fmicb.2026.1603339}},
  volume       = {{17}},
  year         = {{2026}},
}