Statistical characterization of multiple-reaction monitoring mass spectrometry (MRM-MS) assays for quantitative proteomics

Table 4 Validation of AuDIT.

Dataset		Annotation	TN	TP	FN	FP	Overall Accuracy (%)	Sensitivity (%)	Specificity (%)
10 Peptide Standard Curve, 3 transitions MultiQuant	Site 1	Global	89 11	119	29	33	77	80	73
		Focused	7	144	1	8	97	99	94
	Site 2	Global	9	217	14	30	84	94	23
		Focused	23	247	0	0	100	100	100
	Site 3	Global	19	200	33	18	81	86	51
		Focused	50	218	2	0	99	99	100
	Site 4	Global	21	162	74	13	68	69	62
		Focused	81	174	14	1	94	93	99
10 Peptide Standard Curve, 3 transitions, Skyline	Site 1	Global	29	163	35	43	71	82	40
		Focused	56	206	8	0	97	96	100
	Site 2	Global	1	210	15	44	78	93	2
		Focused	15	254	1	0	100	100	100
	Site 5	Global	35	34	2	199	26	94	15
		Focused	37	232	0	1	100	100	97
10 Peptide Standard Curve, 5 transitions, MultiQuant	Site 6	Global	46 16	277	122	23	69	69	67
		Focused	8	294	0	6	99	100	97
Clinical Samples, 3 transitions, MultiQuant	Cardio-vascular Peptides	Global	4	33	5	9	73	87	31
		Focused	9	40	0	2	96	100	82

For each dataset, two contingency matrices are calculated. The 'pre-test' evaluation by the expert identifies overall data problems like poor chromatography, inaccurate peak integration, etc. Comparison of this global annotation with the algorithm calls results in one set of contingency matrices (shown under Annotation = Global). The second 'post-test' re-evaluation is based on the algorithm outcome, and accounts for the fact that the global annotation could be overly conservative (i.e., mark too many transitions as BAD). This focused annotation is compared with the algorithm-derived decisions to derive a second, algorithm-guided set of contingency matrices, shown under Annotation = Focused. TN: True Negative, TP: True Positive, FN: False Negative, and FP: False Positive. Overall Accuracy = (TP + TN)/(TP + TN + FN + FP). Sensitivity = TP/(TP + FN). Specificity = TN/(TN + FP). A transition is BAD if it has some form of interference, i.e., it is imprecise of inaccurate. If not, the transition is labeled as GOOD. Adapted from Abbatiello, Mani, et. al., Clinical Chemistry, 56, 291-305 [17].

ISSN: 1471-2105