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Table 2 Performance measures of KMA, SRST2, MGmapper, BWA-MEM, Bowtie2, Minimap2 and Salmon, for predicting genes directly from raw reads. Thresholds for predicting a gene has been set to: 90% coverage, 90% identity and a minimum depth of 5. A minimum mapping quality of 10 was used for methods relying on post processing with SAMtools and BEDTools, as this gave the best performance across the tested thresholds

From: Rapid and precise alignment of raw reads against redundant databases with KMA

Mapping method Post- processing method Avg. mapping CPU time Avg. post- processing CPU time Peak memory MCC
Predicting antimicrobial resistance
 KMA NA 00:00:24.6 NA 42.3 MB 1.000
 SRST2 NA 00:10:21.3 NA 165.0 MB 1.000
 MGmappera NA 00:13:14.2 NA 101.4 MB 0.288
 BWA-MEM SAMtools / BEDTools 00:07:35.5 00:00:06.1 113.0 MB 0.000
 BWA-MEMb Salmon 00:07:34.5 00:00:12.2 694.9 MB 0.828
 Bowtie2 SAMtools / BEDTools 00:02:35.5 00:00:06.7 33.7 MB 0.000
 Bowtie2b Salmon 00:03:16.4 00:02:24.5 935.8 MB 0.623
 Minimap2 SAMtools / BEDTools 00:02:18.6 00:00:06.0 517.3 MB 0.000
Mapping towards cgMLST alleles
 KMA NA 00:07:02.1 NA 8.3 GB 0.998
 SRST2 NA > 99:99:99.9 NA NA NA
 MGmappera NA 01:23:21.5 NA 8.7 GB 0.062
 BWA-MEM SAMtools / BEDTools 02:14:50.8 00:14:06.7 8.9 GB 0.021
 BWA-MEMb Salmon 03:22:45.4 04:41:09.6 104.2 GBP 0.530
 Bowtie2 SAMtools / BEDTools 01:50:56.8 00:15:23.5 4.1 GB 0.035
 Bowtie2b Salmon > 99:99:99.9 NA NA NA
 Minimap2 SAMtools / BEDTools 01:20:56.2 00:13:11.7 33.6 GB 0.035
  1. a MGmapper was executed on the forward reads only, as paired end mode crashed
  2. b Report all alignments
  3. P The post processing method was responsible for the peak memory consumption