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. 2011 Sep 7;12:444. doi: 10.1186/1471-2164-12-444

Table 1.

Computational time and throughput for each tool of WebMGA

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

a See text for descriptions of the 3 datasets tested.

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.