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Taxonomic classification of DNA sequences beyond sequence similarity using deep neural networks (PNAS PDF)

PNAS · 2022 · PNAS 119(35):e2122636119 version-of-record PDF (10 pages) · Peer-reviewed

DOI: 10.1073/pnas.2122636119

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Results

Values as the source printed them. Compare results only under compatible protocols, datasets and metrics.

ValueMetricModel or configurationDatasetEvaluation
85.55 percentAccuracy (phylum rank; among the samples the tool classified; SI Table S2 'acc.')BERTax (Closely related dataset, Mock et al. 2022)BERTax Closely related dataset (Mock et al. 2022)BERTax on the BERTax closely related dataset
94.78 percentAccuracy (superkingdom rank; among the samples the tool classified; SI Table S2 'acc.')BERTax (Closely related dataset, Mock et al. 2022)BERTax Closely related dataset (Mock et al. 2022)BERTax on the BERTax closely related dataset
83.88 percentMacro average precision (phylum rank; macro average over classes; unclassified samples treated as random guesses)BERTax (Closely related dataset, Mock et al. 2022)BERTax Closely related dataset (Mock et al. 2022)BERTax on the BERTax closely related dataset
95.65 percentMacro average precision (superkingdom rank; macro average over classes; unclassified samples treated as random guesses)BERTax (Closely related dataset, Mock et al. 2022)BERTax Closely related dataset (Mock et al. 2022)BERTax on the BERTax closely related dataset
100 percentProportion (phylum rank; share of test samples the tool returned a prediction for)BERTax (Closely related dataset, Mock et al. 2022)BERTax Closely related dataset (Mock et al. 2022)BERTax on the BERTax closely related dataset
100 percentProportion (superkingdom rank; share of test samples the tool returned a prediction for)BERTax (Closely related dataset, Mock et al. 2022)BERTax Closely related dataset (Mock et al. 2022)BERTax on the BERTax closely related dataset
60.10 percentAccuracy (phylum rank; among the samples the tool classified; SI Table S2 'acc.')BERTax (Distantly related dataset, Mock et al. 2022)BERTax Distantly related dataset (Mock et al. 2022)BERTax on the BERTax distantly related dataset
60.10 percentAccuracy (phylum rank; among the samples the tool classified; SI Table S5; all distantly related test sequences)BERTax (Distantly related dataset, Mock et al. 2022)BERTax Distantly related dataset (Mock et al. 2022)BERTax on the BERTax distantly related dataset
63.52 percentAccuracy (phylum rank; among the samples the tool classified; SI Table S5; test sequences with at least one megablast hit to the training partition (removed by the filter))BERTax (Distantly related dataset, Mock et al. 2022)BERTax Distantly related dataset (Mock et al. 2022)BERTax on the BERTax distantly related dataset
59.15 percentAccuracy (phylum rank; among the samples the tool classified; SI Table S5; test sequences without a megablast hit to the training partition)BERTax (Distantly related dataset, Mock et al. 2022)BERTax Distantly related dataset (Mock et al. 2022)BERTax on the BERTax distantly related dataset
88.95 percentAccuracy (superkingdom rank; among the samples the tool classified; SI Table S2 'acc.')BERTax (Distantly related dataset, Mock et al. 2022)BERTax Distantly related dataset (Mock et al. 2022)BERTax on the BERTax distantly related dataset
88.95 percentAccuracy (superkingdom rank; among the samples the tool classified; SI Table S5; all distantly related test sequences)BERTax (Distantly related dataset, Mock et al. 2022)BERTax Distantly related dataset (Mock et al. 2022)BERTax on the BERTax distantly related dataset
93.48 percentAccuracy (superkingdom rank; among the samples the tool classified; SI Table S5; test sequences with at least one megablast hit to the training partition (removed by the filter))BERTax (Distantly related dataset, Mock et al. 2022)BERTax Distantly related dataset (Mock et al. 2022)BERTax on the BERTax distantly related dataset
88.30 percentAccuracy (superkingdom rank; among the samples the tool classified; SI Table S5; test sequences without a megablast hit to the training partition)BERTax (Distantly related dataset, Mock et al. 2022)BERTax Distantly related dataset (Mock et al. 2022)BERTax on the BERTax distantly related dataset
54.10 percentMacro average precision (phylum rank; macro average over classes; unclassified samples treated as random guesses)BERTax (Distantly related dataset, Mock et al. 2022)BERTax Distantly related dataset (Mock et al. 2022)BERTax on the BERTax distantly related dataset
90.06 percentMacro average precision (superkingdom rank; macro average over classes; unclassified samples treated as random guesses)BERTax (Distantly related dataset, Mock et al. 2022)BERTax Distantly related dataset (Mock et al. 2022)BERTax on the BERTax distantly related dataset
100 percentProportion (phylum rank; share of test samples the tool returned a prediction for)BERTax (Distantly related dataset, Mock et al. 2022)BERTax Distantly related dataset (Mock et al. 2022)BERTax on the BERTax distantly related dataset
100 percentProportion (superkingdom rank; share of test samples the tool returned a prediction for)BERTax (Distantly related dataset, Mock et al. 2022)BERTax Distantly related dataset (Mock et al. 2022)BERTax on the BERTax distantly related dataset
66.92 percentMacro average precision (genus rank; macro average over classes; unclassified samples treated as random guesses)BERTax (Final model dataset, Mock et al. 2022)BERTax Final model dataset (Mock et al. 2022)BERTax on the BERTax final model dataset
95.10 percentMacro average precision (phylum rank; macro average over classes; unclassified samples treated as random guesses)BERTax (Final model dataset, Mock et al. 2022)BERTax Final model dataset (Mock et al. 2022)BERTax on the BERTax final model dataset
98.62 percentMacro average precision (superkingdom rank; macro average over classes; unclassified samples treated as random guesses)BERTax (Final model dataset, Mock et al. 2022)BERTax Final model dataset (Mock et al. 2022)BERTax on the BERTax final model dataset
87.72 percentAccuracy (phylum rank; among the samples the tool classified; SI Table S2 'acc.')DeepMicrobes (Closely related dataset, Mock et al. 2022)BERTax Closely related dataset (Mock et al. 2022)DeepMicrobes on the BERTax closely related dataset
96.68 percentAccuracy (superkingdom rank; among the samples the tool classified; SI Table S2 'acc.')DeepMicrobes (Closely related dataset, Mock et al. 2022)BERTax Closely related dataset (Mock et al. 2022)DeepMicrobes on the BERTax closely related dataset
86.62 percentMacro average precision (phylum rank; macro average over classes; unclassified samples treated as random guesses)DeepMicrobes (Closely related dataset, Mock et al. 2022)BERTax Closely related dataset (Mock et al. 2022)DeepMicrobes on the BERTax closely related dataset
97.18 percentMacro average precision (superkingdom rank; macro average over classes; unclassified samples treated as random guesses)DeepMicrobes (Closely related dataset, Mock et al. 2022)BERTax Closely related dataset (Mock et al. 2022)DeepMicrobes on the BERTax closely related dataset
100 percentProportion (phylum rank; share of test samples the tool returned a prediction for)DeepMicrobes (Closely related dataset, Mock et al. 2022)BERTax Closely related dataset (Mock et al. 2022)DeepMicrobes on the BERTax closely related dataset
100 percentProportion (superkingdom rank; share of test samples the tool returned a prediction for)DeepMicrobes (Closely related dataset, Mock et al. 2022)BERTax Closely related dataset (Mock et al. 2022)DeepMicrobes on the BERTax closely related dataset
41.95 percentAccuracy (phylum rank; among the samples the tool classified; SI Table S2 'acc.')DeepMicrobes (Distantly related dataset, Mock et al. 2022)BERTax Distantly related dataset (Mock et al. 2022)DeepMicrobes on the BERTax distantly related dataset
41.95 percentAccuracy (phylum rank; among the samples the tool classified; SI Table S5; all distantly related test sequences)DeepMicrobes (Distantly related dataset, Mock et al. 2022)BERTax Distantly related dataset (Mock et al. 2022)DeepMicrobes on the BERTax distantly related dataset
47.80 percentAccuracy (phylum rank; among the samples the tool classified; SI Table S5; test sequences with at least one megablast hit to the training partition (removed by the filter))DeepMicrobes (Distantly related dataset, Mock et al. 2022)BERTax Distantly related dataset (Mock et al. 2022)DeepMicrobes on the BERTax distantly related dataset
39.89 percentAccuracy (phylum rank; among the samples the tool classified; SI Table S5; test sequences without a megablast hit to the training partition)DeepMicrobes (Distantly related dataset, Mock et al. 2022)BERTax Distantly related dataset (Mock et al. 2022)DeepMicrobes on the BERTax distantly related dataset
68.39 percentAccuracy (superkingdom rank; among the samples the tool classified; SI Table S2 'acc.')DeepMicrobes (Distantly related dataset, Mock et al. 2022)BERTax Distantly related dataset (Mock et al. 2022)DeepMicrobes on the BERTax distantly related dataset
68.39 percentAccuracy (superkingdom rank; among the samples the tool classified; SI Table S5; all distantly related test sequences)DeepMicrobes (Distantly related dataset, Mock et al. 2022)BERTax Distantly related dataset (Mock et al. 2022)DeepMicrobes on the BERTax distantly related dataset
81.13 percentAccuracy (superkingdom rank; among the samples the tool classified; SI Table S5; test sequences with at least one megablast hit to the training partition (removed by the filter))DeepMicrobes (Distantly related dataset, Mock et al. 2022)BERTax Distantly related dataset (Mock et al. 2022)DeepMicrobes on the BERTax distantly related dataset
63.24 percentAccuracy (superkingdom rank; among the samples the tool classified; SI Table S5; test sequences without a megablast hit to the training partition)DeepMicrobes (Distantly related dataset, Mock et al. 2022)BERTax Distantly related dataset (Mock et al. 2022)DeepMicrobes on the BERTax distantly related dataset
36.61 percentMacro average precision (phylum rank; macro average over classes; unclassified samples treated as random guesses)DeepMicrobes (Distantly related dataset, Mock et al. 2022)BERTax Distantly related dataset (Mock et al. 2022)DeepMicrobes on the BERTax distantly related dataset
67.25 percentMacro average precision (superkingdom rank; macro average over classes; unclassified samples treated as random guesses)DeepMicrobes (Distantly related dataset, Mock et al. 2022)BERTax Distantly related dataset (Mock et al. 2022)DeepMicrobes on the BERTax distantly related dataset
100 percentProportion (phylum rank; share of test samples the tool returned a prediction for)DeepMicrobes (Distantly related dataset, Mock et al. 2022)BERTax Distantly related dataset (Mock et al. 2022)DeepMicrobes on the BERTax distantly related dataset
100 percentProportion (superkingdom rank; share of test samples the tool returned a prediction for)DeepMicrobes (Distantly related dataset, Mock et al. 2022)BERTax Distantly related dataset (Mock et al. 2022)DeepMicrobes on the BERTax distantly related dataset
66.43 percentMacro average precision (genus rank; macro average over classes; unclassified samples treated as random guesses)DeepMicrobes (Final model dataset, Mock et al. 2022)BERTax Final model dataset (Mock et al. 2022)DeepMicrobes on the BERTax final model dataset
92.11 percentMacro average precision (phylum rank; macro average over classes; unclassified samples treated as random guesses)DeepMicrobes (Final model dataset, Mock et al. 2022)BERTax Final model dataset (Mock et al. 2022)DeepMicrobes on the BERTax final model dataset
98.13 percentMacro average precision (superkingdom rank; macro average over classes; unclassified samples treated as random guesses)DeepMicrobes (Final model dataset, Mock et al. 2022)BERTax Final model dataset (Mock et al. 2022)DeepMicrobes on the BERTax final model dataset
98.82 percentAccuracy (phylum rank; among the samples the tool classified; SI Table S2 'acc.')Kraken2 (Closely related dataset, Mock et al. 2022)BERTax Closely related dataset (Mock et al. 2022)Kraken2 on the BERTax closely related dataset
99.82 percentAccuracy (superkingdom rank; among the samples the tool classified; SI Table S2 'acc.')Kraken2 (Closely related dataset, Mock et al. 2022)BERTax Closely related dataset (Mock et al. 2022)Kraken2 on the BERTax closely related dataset
75.99 percentMacro average precision (phylum rank; macro average over classes; unclassified samples treated as random guesses)Kraken2 (Closely related dataset, Mock et al. 2022)BERTax Closely related dataset (Mock et al. 2022)Kraken2 on the BERTax closely related dataset
86.26 percentMacro average precision (superkingdom rank; macro average over classes; unclassified samples treated as random guesses)Kraken2 (Closely related dataset, Mock et al. 2022)BERTax Closely related dataset (Mock et al. 2022)Kraken2 on the BERTax closely related dataset
75.95 percentProportion (phylum rank; share of test samples the tool returned a prediction for)Kraken2 (Closely related dataset, Mock et al. 2022)BERTax Closely related dataset (Mock et al. 2022)Kraken2 on the BERTax closely related dataset
76.11 percentProportion (superkingdom rank; share of test samples the tool returned a prediction for)Kraken2 (Closely related dataset, Mock et al. 2022)BERTax Closely related dataset (Mock et al. 2022)Kraken2 on the BERTax closely related dataset
68.26 percentAccuracy (phylum rank; among the samples the tool classified; SI Table S2 'acc.')Kraken2 (Distantly related dataset, Mock et al. 2022)BERTax Distantly related dataset (Mock et al. 2022)Kraken2 on the BERTax distantly related dataset
90.71 percentAccuracy (superkingdom rank; among the samples the tool classified; SI Table S2 'acc.')Kraken2 (Distantly related dataset, Mock et al. 2022)BERTax Distantly related dataset (Mock et al. 2022)Kraken2 on the BERTax distantly related dataset

Claims

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Protocols (3)

Evaluations (27)

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32 evidence rows matching the loaded filters

Claims, original sources and review scope · Release 2026-10-22-1b7cf027e4f6
Property and statementOriginal source and locationReview and provenance
attributes.artifact_sha256
7977424613ab5e5f4986745b527a270fd2c0427dbab40471813903eda85dcaec
Source metadata
Taxonomic classification of DNA sequences beyond sequence similarity using deep neural networks (PNAS PDF)

Original source ↗

No field-specific location recorded

Version: PNAS 119(35):e2122636119 version-of-record PDF (10 pages)
Retrieved: 2026-10-12T20:56:37Z

catalogued

No individual claim review recorded

Audit details

Field: attributes.artifact_sha256

Source artifact SHA-256: 7977424613ab5e5f4986745b527a270fd2c0427dbab40471813903eda85dcaec

Hash scope: Hash scope not separately documented; inspect source record

Inspected artifact

Artifact url
https://www.pnas.org/doi/pdf/10.1073/pnas.2122636119
Source metadata
Taxonomic classification of DNA sequences beyond sequence similarity using deep neural networks (PNAS PDF)

Original source ↗

No field-specific location recorded

Version: PNAS 119(35):e2122636119 version-of-record PDF (10 pages)
Retrieved: 2026-10-12T20:56:37Z

catalogued

No individual claim review recorded

Audit details

Field: attributes.artifact_url

Source artifact SHA-256: 7977424613ab5e5f4986745b527a270fd2c0427dbab40471813903eda85dcaec

Hash scope: Hash scope not separately documented; inspect source record

Inspected artifact

Doi
10.1073/pnas.2122636119
Source metadata
Taxonomic classification of DNA sequences beyond sequence similarity using deep neural networks (PNAS PDF)

Original source ↗

No field-specific location recorded

Version: PNAS 119(35):e2122636119 version-of-record PDF (10 pages)
Retrieved: 2026-10-12T20:56:37Z

catalogued

No individual claim review recorded

Audit details

Field: attributes.doi

Source artifact SHA-256: 7977424613ab5e5f4986745b527a270fd2c0427dbab40471813903eda85dcaec

Hash scope: Hash scope not separately documented; inspect source record

Inspected artifact

Licence
CC-BY-NC-ND-4.0
Source metadata
Taxonomic classification of DNA sequences beyond sequence similarity using deep neural networks (PNAS PDF)

Original source ↗

No field-specific location recorded

Version: PNAS 119(35):e2122636119 version-of-record PDF (10 pages)
Retrieved: 2026-10-12T20:56:37Z

catalogued

No individual claim review recorded

Audit details

Field: attributes.licence

Source artifact SHA-256: 7977424613ab5e5f4986745b527a270fd2c0427dbab40471813903eda85dcaec

Hash scope: Hash scope not separately documented; inspect source record

Inspected artifact

Limitations
1 values
  • The reviewer could not re-fetch the pinned PNAS bytes (HTTP 403 to command-line clients) and did not use a browser, so the pinned SHA-256 is the extractor's in-browser hash, not independently re-verified. Table 1 values were checked against the PMC copy instead.
Source metadata
Taxonomic classification of DNA sequences beyond sequence similarity using deep neural networks (PNAS PDF)

Original source ↗

No field-specific location recorded

Version: PNAS 119(35):e2122636119 version-of-record PDF (10 pages)
Retrieved: 2026-10-12T20:56:37Z

catalogued

No individual claim review recorded

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Field: attributes.limitations

Source artifact SHA-256: 7977424613ab5e5f4986745b527a270fd2c0427dbab40471813903eda85dcaec

Hash scope: Hash scope not separately documented; inspect source record

Inspected artifact

Media type
application/pdf
Source metadata
Taxonomic classification of DNA sequences beyond sequence similarity using deep neural networks (PNAS PDF)

Original source ↗

No field-specific location recorded

Version: PNAS 119(35):e2122636119 version-of-record PDF (10 pages)
Retrieved: 2026-10-12T20:56:37Z

catalogued

No individual claim review recorded

Audit details

Field: attributes.media_type

Source artifact SHA-256: 7977424613ab5e5f4986745b527a270fd2c0427dbab40471813903eda85dcaec

Hash scope: Hash scope not separately documented; inspect source record

Inspected artifact

Publication status
peer_reviewed
Source metadata
Taxonomic classification of DNA sequences beyond sequence similarity using deep neural networks (PNAS PDF)

Original source ↗

No field-specific location recorded

Version: PNAS 119(35):e2122636119 version-of-record PDF (10 pages)
Retrieved: 2026-10-12T20:56:37Z

catalogued

No individual claim review recorded

Audit details

Field: attributes.publication_status

Source artifact SHA-256: 7977424613ab5e5f4986745b527a270fd2c0427dbab40471813903eda85dcaec

Hash scope: Hash scope not separately documented; inspect source record

Inspected artifact

Retrieval method
Fetched in a Chrome session (Claude in Chrome) from the article page, because PNAS returns HTTP 403 to command-line clients; SHA-256 computed in the page with crypto.subtle; text layer read with pdf.js 4.0.379.
Source metadata
Taxonomic classification of DNA sequences beyond sequence similarity using deep neural networks (PNAS PDF)

Original source ↗

No field-specific location recorded

Version: PNAS 119(35):e2122636119 version-of-record PDF (10 pages)
Retrieved: 2026-10-12T20:56:37Z

catalogued

No individual claim review recorded

Audit details

Field: attributes.retrieval_method

Source artifact SHA-256: 7977424613ab5e5f4986745b527a270fd2c0427dbab40471813903eda85dcaec

Hash scope: Hash scope not separately documented; inspect source record

Inspected artifact

Retrieval note
The bytes were not saved to disk. A reviewer must re-fetch the PDF through a browser and compare its SHA-256.
Source metadata
Taxonomic classification of DNA sequences beyond sequence similarity using deep neural networks (PNAS PDF)

Original source ↗

No field-specific location recorded

Version: PNAS 119(35):e2122636119 version-of-record PDF (10 pages)
Retrieved: 2026-10-12T20:56:37Z

catalogued

No individual claim review recorded

Audit details

Field: attributes.retrieval_note

Source artifact SHA-256: 7977424613ab5e5f4986745b527a270fd2c0427dbab40471813903eda85dcaec

Hash scope: Hash scope not separately documented; inspect source record

Inspected artifact

Retrieved at
2026-10-12T20:56:37Z
Source metadata
Taxonomic classification of DNA sequences beyond sequence similarity using deep neural networks (PNAS PDF)

Original source ↗

No field-specific location recorded

Version: PNAS 119(35):e2122636119 version-of-record PDF (10 pages)
Retrieved: 2026-10-12T20:56:37Z

catalogued

No individual claim review recorded

Audit details

Field: attributes.retrieved_at

Source artifact SHA-256: 7977424613ab5e5f4986745b527a270fd2c0427dbab40471813903eda85dcaec

Hash scope: Hash scope not separately documented; inspect source record

Inspected artifact

How to read the evidence

Sources and history

Release 2026-10-22-1b7cf027e4f6 · Record review: source checked

Version-of-record PDF, used for Table 1, whose PMC copy is an image.

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Technical metadata and extraction receipts

Stable ID: dna-pathogen-20261012-bertax-source-pdf

areas
microbes-communities
contexts
research
url
https://doi.org/10.1073/pnas.2122636119
artifact url
https://www.pnas.org/doi/pdf/10.1073/pnas.2122636119
version
PNAS 119(35):e2122636119 version-of-record PDF (10 pages)
retrieved at
2026-10-12T20:56:37Z
artifact sha256
7977424613ab5e5f4986745b527a270fd2c0427dbab40471813903eda85dcaec
doi
10.1073/pnas.2122636119
publication status
peer_reviewed
licence
CC-BY-NC-ND-4.0
media type
application/pdf
venue
PNAS
year
2022
retrieval method
Fetched in a Chrome session (Claude in Chrome) from the article page, because PNAS returns HTTP 403 to command-line clients; SHA-256 computed in the page with crypto.subtle; text layer read with pdf.js 4.0.379.
retrieval note
The bytes were not saved to disk. A reviewer must re-fetch the PDF through a browser and compare its SHA-256.
source locator
Page 4, Table 1 'Comparison of the macro AveP on all three datasets'
review artifact
PMC open-access copy of the version-of-record PDF, https://pmc-oa-opendata.s3.amazonaws.com/PMC9436379.1/PMC9436379.1.pdf, SHA-256 725c99ba8bb95d9e5e73997cbbe45d3a889185163749f494673a084de534c835, retrieved 2026-10-12; Table 1 text identical to the pinned PDF's text layer as archived by the extractor
review artifact matches original artifact sha256
false
limitations
The reviewer could not re-fetch the pinned PNAS bytes (HTTP 403 to command-line clients) and did not use a browser, so the pinned SHA-256 is the extractor's in-browser hash, not independently re-verified. Table 1 values were checked against the PMC copy instead.
review
method: pdf-text-parse; independent-cell-check; reviewer: claude; reviewer note: Separate Claude review agent (rev-mlvb), independent of the extracting agent; no human review claimed; date: 2026-10-12; artifact sha256: 725c99ba8bb95d9e5e73997cbbe45d3a889185163749f494673a084de534c835; retrieval url: https://pmc-oa-opendata.s3.amazonaws.com/PMC9436379.1/PMC9436379.1.pdf; note: Pinned hash not re-verified (PNAS HTTP 403). Values checked against the PMC copy named in review_artifact.
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