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Table 1 Benchmarking of taxonomic assignment tasks using simulated reads (ICTV and HIV-1)

From: A multi-task CNN learning model for taxonomic assignment of human viruses

Datasets Simulated reads (50 bp, n = 1million) from ICTV standard genomes Simulated reads (150 bp, n = 100 k) from ICTV standard genomes Simulated divergent HIV-1 reads (150 bp, n = 100 k) (100 generations) Simulated divergent HIV-1 reads (150 bp, n = 100 k) (1 K generations) Simulated divergent HIV-1 reads (150 bp, n = 100 k) (10 K generations)
Metrics Kappa F1 Kappa F1 Prediction accuracy Prediction accuracy Prediction accuracy
Kraken 2 0.3139 0.3184 0.7274 0.7318 0.9664 0.7755 4.890 × 10–3
Centrifuge 0.5953 0.6011 0.7219 0.7266 0.8865 0.8679 3.056 × 10–2
Bowtie 2 0.9597 0.9605 0.9991 0.9991 0.9976 0.9828 8.501 × 10–4
MT-CNN 0.9464 0.9475 0.9976 0.9976 1.000 0.9963 0.1531