Table 1. Examples of Proteins Identified in the 2-D/Replicate Data Set by ≥2 Peptides but Not in the 3-D Data Set.

			2-D methodb			3-D methodbc
IDa	Name	Sequence	Xcorr	ΔCn	z	Xcorr	ΔCn	z
Q53FT3	Uncharacterized protein C11orf73	R.LVQTAAQQVAEDK.F	4.74	0.35	2	4.62	0.35	2
		R.LAQNPLFWK.T	2.69	0.185	2	2.11	0.046	2
Q8IW35	Leucine-rich repeat and IQ domain-containing protein 2	K.AGLLPCPEPTIISAILK.D	3.39	0.129	3	2.94	0.314	2
		K.LPMILTQR.S	2.57	0.051	2	1.98	0.091	2
O95563	Brain protein 44	R.TVFFWAPIMK.W	2.87	0.254	2	3.08	0.263	2
		K.LRPLYNHPAGPR.T	3.54	0.283	3	3.12	0.328	3
		K.WGLVCAGLADMAR.P	2.87	0.254	2	-	-	-

^aThese proteins, which were identified by two or three peptides in the 2-D/replicate data set, were identified by a single peptide in the 3-D data set. In each case, a second peptide was detected in the 3-D data set but failed to pass the data filter cutoff due to slightly lower values for X_corr or ΔC_n (bolded values in table).

^bThe filtering cutoff values used were X_corr ≥ 1.8 (+1); 2.1 (+2); 3.25 (+3), ΔC_n ≥ 0.05.

^cThe bold values indicate they are below cutoff value. “-” indicates “not found.”