WebMGA: a customizable web server for fast metagenomic sequence analysis

BMC Genomics

Table 1 Computational time and throughput for each tool of WebMGA

Category	Tool	Data^a	Wall time (h:m:s)	Total CPU time (h:m:s)	Daily throughput^b
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.

ISSN: 1471-2164