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Table 1 Computational time and throughput for each tool of WebMGA

From: WebMGA: a customizable web server for fast metagenomic sequence analysis

Category Tool Dataa Wall time (h:m:s) Total CPU time (h:m:s) Daily throughputb
Clustering CD-HIT-EST 1 00:08:53 00:34:08 3,113
  CD-HIT 2 00:00:58 00:02:52 23,040
  H-CD-HIT 2 00:20:06 01:10:26 1,600
  CD-HIT-454 1 00:05:40 00:21:54 4,800
rRNA BLASTN-rRNA 1 00:12:43 13:44:53 139
  hmm-rRNA 1 00:01:56 00:20:35 5,008
tRNA tRNA-scan 1 00:02:29 02:01:50 936
ORF calling ORF-finder 1 00:02:06 00:02:06 23,040
  Metagene 1 00:16:21 00:15:21 6,400
  FragGeneScan 1 01:27:50 01:27:50 1,294
Function COG 2 00:14:55 15:12:50 126
  KOG 2 00:15:16 16:25:31 116
  PRK 2 00:28:38 32:03:16 59
  PFAM 2 01:33:44 115:30:23 16
  TIGRFAM 2 00:53:23 62:31:51 30
Pathway KEGG 2 20:24:33 553:32:48 3
Statistics FNA-stat 1 00:00:38 00:00:38 43,746
  FAA-stat 2 00:00:12 00:00:12 52,363
Quality control QC-filter-FASTQ 1 00:03:13 00:03:13 19,200
  QC-filter-FASTA-qual 1 00:02:47 00:02:47 23,040
  Trim 1 00:04:00 00:04:00 16,457
Filtering Filter-human 1 00:40:28 02:29:57 762
Binning RDP-binning 1 01:16:30 01:20:00 1,404
  FR-HIT-binning 1 00:36:59 02:13:53 853
OTU clustering CD-HIT-OTU 3 00:05:10 00:10:23 8,861
File conversion FASTQ2FASTA 1 00:02:24 00:02:24 23,040
  1. a See text for descriptions of the 3 datasets tested.
  2. b Daily throughput is calculated as the daily CPU time of WebMGA cluster with 80 cores divided by the total CPU time of a job, assuming 2 minutes of administrative CPU cost such as job queuing, file coping etc. for each job.