Published long-read classification comparison; transcribed, not reproduced.
1 evaluation · 2 results. Different protocols are not a single leaderboard.
Protocol: Genus-level read classification of ONT bacterial isolates, main database (Peres da Silva et al. 2024) · Dataset: ONT reads from 81 bacterial isolates (Peres da Silva et al. 2024)
Sorted by F1 (genus level; mean across all 81 isolates (species in and out of the database)) (higher is better). The best value in each column is highlighted. Decimals are rounded for display; each value links to the printed value and its source.
| Tested configuration | F1 (genus level; mean across all 81 isolates (species in and out of the database)) | Recall (genus level; mean across all 81 isolates (species in and out of the database)) |
|---|---|---|
| MMseqs2 (main database, Peres da Silva et al. 2024)Evaluation | 0.85 | 0.81 |
Applied filters: All linked evaluations
| Tested configuration | Protocol and dataset | Finding | Evidence and details |
|---|---|---|---|
| Configuration: MMseqs2 (main database, Peres da Silva et al. 2024) | Protocol: Genus-level read classification of ONT bacterial isolates, main database (Peres da Silva et al. 2024) Dataset: ONT reads from 81 bacterial isolates (Peres da Silva et al. 2024) | 0.85 F1 (genus level; mean across all 81 isolates (species in and out of the database)) fraction · higher Uncertainty: Not reported by the source: Figure 3 shows standard-deviation error bars; no value is printed in the text Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourcedna-pathogen-20261012-metagenn-protocol-isolates Aggregation: Not reported MetageNN: a memory-efficient neural network taxonomic classifier robust to sequencing errors and missing genomes · Results 'Results for all genomes' paragraph 1, sentence 4 (values shown in Fig. 3a) |
| Configuration: MMseqs2 (main database, Peres da Silva et al. 2024) | Protocol: Genus-level read classification of ONT bacterial isolates, main database (Peres da Silva et al. 2024) Dataset: ONT reads from 81 bacterial isolates (Peres da Silva et al. 2024) | 0.81 Recall (genus level; mean across all 81 isolates (species in and out of the database)) fraction · higher Uncertainty: Not reported by the source: Figure 3 shows standard-deviation error bars; no value is printed in the text Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourcedna-pathogen-20261012-metagenn-protocol-isolates Aggregation: Not reported MetageNN: a memory-efficient neural network taxonomic classifier robust to sequencing errors and missing genomes · Results 'Results for all genomes' paragraph 1, sentence 4 (values shown in Fig. 3a) |
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19 evidence rows matching the loaded filters
| Property and statement | Original source and location | Review and provenance |
|---|---|---|
| Comparison: adaptation All tools use the 516-genome main database Context-only references | MetageNN: a memory-efficient neural network taxonomic classifier robust to sequencing errors and missing genomes Results 'Evaluation metrics'; 'Results for all genomes'; 'Results for “Species out of the database” settings' Version: BMC Bioinformatics 25:153, published 2024-04-16; PMC11022314 full-text XML | not individually reviewed No individual claim review recorded author reported Audit detailsField: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Comparison: aggregation Mean across isolates Context-only references | MetageNN: a memory-efficient neural network taxonomic classifier robust to sequencing errors and missing genomes Results 'Evaluation metrics'; 'Results for all genomes'; 'Results for “Species out of the database” settings' Version: BMC Bioinformatics 25:153, published 2024-04-16; PMC11022314 full-text XML | not individually reviewed No individual claim review recorded author reported Audit detailsField: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Comparison: budget Not reported Context-only references | MetageNN: a memory-efficient neural network taxonomic classifier robust to sequencing errors and missing genomes Results 'Evaluation metrics'; 'Results for all genomes'; 'Results for “Species out of the database” settings' Version: BMC Bioinformatics 25:153, published 2024-04-16; PMC11022314 full-text XML | missing or unspecified No individual claim review recorded author reported Audit detailsField: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Comparison: dataset version Genus-level read classification of ONT bacterial isolates, main database (Peres da Silva et al. 2024) Context-only references | MetageNN: a memory-efficient neural network taxonomic classifier robust to sequencing errors and missing genomes Results 'Evaluation metrics'; 'Results for all genomes'; 'Results for “Species out of the database” settings' Version: BMC Bioinformatics 25:153, published 2024-04-16; PMC11022314 full-text XML | not individually reviewed No individual claim review recorded author reported Audit detailsField: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Comparison: inputs ONT R9.4.1 reads Context-only references | MetageNN: a memory-efficient neural network taxonomic classifier robust to sequencing errors and missing genomes Results 'Evaluation metrics'; 'Results for all genomes'; 'Results for “Species out of the database” settings' Version: BMC Bioinformatics 25:153, published 2024-04-16; PMC11022314 full-text XML | not individually reviewed No individual claim review recorded author reported Audit detailsField: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Comparison: metric implementation For each taxon, sensitivity is the proportion of its reads classified as such and precision the proportion of correctly classified reads; F1 is their harmonic mean. Averages are across bacterial isolates; Wilcoxon rank-sum tests compare MetageNN with each tool. Context-only references | MetageNN: a memory-efficient neural network taxonomic classifier robust to sequencing errors and missing genomes Results 'Evaluation metrics'; 'Results for all genomes'; 'Results for “Species out of the database” settings' Version: BMC Bioinformatics 25:153, published 2024-04-16; PMC11022314 full-text XML | not individually reviewed No individual claim review recorded author reported Audit detailsField: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Comparison: population 81 ONT bacterial isolates, about 20,000 reads each Context-only references | MetageNN: a memory-efficient neural network taxonomic classifier robust to sequencing errors and missing genomes Results 'Evaluation metrics'; 'Results for all genomes'; 'Results for “Species out of the database” settings' Version: BMC Bioinformatics 25:153, published 2024-04-16; PMC11022314 full-text XML | not individually reviewed No individual claim review recorded author reported Audit detailsField: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Comparison: protocol id dna-pathogen-20261012-metagenn-protocol-isolates Context-only references | MetageNN: a memory-efficient neural network taxonomic classifier robust to sequencing errors and missing genomes Results 'Evaluation metrics'; 'Results for all genomes'; 'Results for “Species out of the database” settings' Version: BMC Bioinformatics 25:153, published 2024-04-16; PMC11022314 full-text XML | not individually reviewed No individual claim review recorded author reported Audit detailsField: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Comparison: split Test sets 'Species in the database' (47 isolates) and 'Species out of the database' (34 isolates) Context-only references | MetageNN: a memory-efficient neural network taxonomic classifier robust to sequencing errors and missing genomes Results 'Evaluation metrics'; 'Results for all genomes'; 'Results for “Species out of the database” settings' Version: BMC Bioinformatics 25:153, published 2024-04-16; PMC11022314 full-text XML | not individually reviewed No individual claim review recorded author reported Audit detailsField: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
Limitations1 values
| MetageNN: a memory-efficient neural network taxonomic classifier robust to sequencing errors and missing genomes Results 'Evaluation metrics'; 'Results for all genomes'; 'Results for “Species out of the database” settings' Version: BMC Bioinformatics 25:153, published 2024-04-16; PMC11022314 full-text XML | not individually reviewed No individual claim review recorded author reported Audit detailsField: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
Release 2026-10-22-1b7cf027e4f6 · Record review: source checked
Stable ID: dna-pathogen-20261012-metagenn-eval-mmseqs2-isolates