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Table 1 The ARG/non-ARG classification results between different methods

From: HMD-ARG: hierarchical multi-task deep learning for annotating antibiotic resistance genes

 

Accuracy

Precisiona

Recall

F1-score

HMD-ARG

0.948

0.939

0.971

0.948

CARD

0.71

0.999

0.421

0.592

DeepARG

0.965

0.998

0.93

0.963

AMRPlusPlusb

0.691

0.867

0.449

0.592

Meta-MARCc

0.848

0.847

0.85

0.848

  1. aThe precision, recall, and F1-score are only for ARG
  2. bAMR++ requires the input in a paired fastq format. So, we simulated the fastq data from our test protein dataset. Details can be seen in the supplementary
  3. cMeta-MARC can work with both assembly and raw data; we tested it with the assembled sequences (our test dataset)