Table 1 Binning performance on various datasets (simulated reads, mock libraries and real samples).
No. of bins | No. of binned contigs | Precision (%) | Recall (%) | F1 (%) | ||
|---|---|---|---|---|---|---|
Simulated dataset | 10 Genomes (2,185 contigsa ) | |||||
CONCOCT | 19 | 2,185 | 98.78 | 97.67 | 98.2 | |
MaxBin | 10 | 2,125 | 93.16 | 97.17 | 95.1 | |
MetaBAT | 9 | 1,653 | 90.26 | 95.13 | 92.6 | |
MyCC (default) | 10 | 2,185 | 97.79 | 97.79 | 97.8 | |
MyCC (one stage) | 11 | 2,185 | 99.17 | 98.45 | 98.8 | |
100 Genomes (8,978 contigsa ) | ||||||
CONCOCT | 79 | 8,977 | 59.67 | 97.40 | 74.0 | |
MaxBin | 84 | 7,308 | 89.64 | 84.52 | 87.0 | |
MetaBAT | 105 | 5,430 | 92.72 | 89.59 | 91.1 | |
MyCC (default) | 93 | 8,978 | 87.45 | 90.54 | 89.0 | |
MyCC (5p6 mer, cov) | 88 | 8,978 | 89.68 | 94.09 | 91.8 | |
Mock datasets | 25 Genomes, 2 libraries (1,893 contigsa ) | |||||
CONCOCT | 29 | 1,892 | 72.67 | 97.15 | 83.1 | |
MaxBin2 | 26 | 1,892 | 90.00 | 90.38 | 90.2 | |
MetaBAT | 31 | 1,742 | 93.78 | 93.57 | 93.7 | |
MyCC (default) | 23 | 1,893 | 88.97 | 97.35 | 93.0 | |
MyCC (4 mer, cov) | 24 | 1,893 | 95.87 | 97.28 | 96.6 | |
64 Genomes (23,602 contigsa ) | ||||||
CONCOCT | 84 | 23,585 | 70.63 | 93.90 | 80.6 | |
MaxBin | 56 | 20,639 | 84.96 | 81.83 | 83.4 | |
MetaBAT | 70 | 8,722 | 86.78 | 77.40 | 81.8 | |
MyCC (default) | 61 | 23,602 | 83.19 | 88.76 | 85.9 | |
MyCC (5p6 mer, cov) | 57 | 23,602 | 84.36 | 92.85 | 88.4 | |
Real dataset | Sharon’s dataset, 18 runs (2,294 contigsa ) | |||||
CONCOCT | 32 | 2,291 | 79.92 | 97.58 | 87.9 | |
GroopM | 13 | 1,687 | 88.39 | 86.29 | 87.3 | |
MaxBin2 | 10 | 2,294 | 82.94 | 93.75 | 88.0 | |
MetaBAT | 10 | 1,573 | 85.46 | 93.66 | 89.4 | |
MyCC (4 mer, cov) | 14 | 2,294 | 86.72 | 98.68 | 92.3 | |
