Table 3

Comparison of the number of features detected (total and known) using apLCMS, xMSanalyzer, and XCMS
Datasets apLCMS xMSanalyzer-apLCMS XCMS v1.20.1
{default} {3,0.3} υ {3,0.8} {step = 0.001, snthresh = 3, max = 5, mzdiff = 0.1}
Sample Set 1 (Column A) 1454 2384 1027
MMCD: 314 (21.6%) MMCD: 534 (22.3%) MMCD: 222 (21.6%)
Metlin: 292 (20.1%) Metlin: 433 (18.1%) Metlin: 230 (22.4%)
Sample Set 1 (Column B) 1238 2201 998
MMCD: 309 (25%) MMCD: 557 (25.3%) MMCD: 261 (26.1%)
Metlin: 279 (22.5%) Metlin: 468 (21.2%) Metlin: 252 (25.2%)
Sample Set 2 (Column A) 1324 2677 1262
MMCD: 408 (30.8%) MMCD: 732 (27.3%) MMCD: 324 (25.7%)
Metlin: 497 (37.5%) Metlin: 705 (26.3%) Metlin: 431 (34.2%)
Sample Set 2 (Column B) 1573 2969 1395
MMCD: 508 (32.3%) MMCD: 794 (26.7%) MMCD: 359 (25.7%)
Metlin: 693 (44.1%) Metlin: 848 (28.5%) Metlin: 514 (36.8%)
Average over all datasets Total: 1397 Total: 2558 Total: 1171
Known metabolites: 413 (29.6%) Known metabolites: 634 (24.8%) Known metabolites: 324 (27.7%)

Uppal et al.

Uppal et al. BMC Bioinformatics 2013 14:15   doi:10.1186/1471-2105-14-15

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