A new method for alignment of LC-MALDI-TOF data

Table 3 The CV and correlation of the Benkali’s LC-MALDI-TOF dataset before and after alignment. The result of the best performing method is in boldface.

			After alignment
	Original		Our method using three dimensions (RT, m/z, intensity)		Our method using two dimensions (RT, m/z)		Podwojski’s method (hierarchical clustering and linear regression)		Podwojski’s method (hierarchical clustering and loess)
Group	CV	Corr	CV	Corr	CV	Corr	CV	Corr	CV	Corr
1	32	0.31	20	0.89	31	0.71	26	0.68	29	0.79
2	30	0.39	15	0.90	26	0.82	19	0.86	29	0.89
3	28	0.45	17	0.89	31	0.7	22	0.67	30	0.71
4	27	0.5	21	0.93	26	0.83	25	0.94	24	0.97
5	33	0.36	25	0.83	31	0.75	26	0.77	28	0.83

CV=coefficients of variation (%); Corr=Pearson correlation coefficient; Group 1=samples without spike-in peptides; Group 2=samples with 0.25X spike-in peptides; group 3: samples with 0.5X spike-in peptides; group 4: samples with 1X spike-in peptides; Group 5: Group 1-4 combined.

ISSN: 1477-5956