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. 2013 Apr 8;11:13. doi: 10.1186/1477-5956-11-13

Table 1.

Summary of proteins identified by Mascot and Spectrum Mill

A Proteins identified by Spectrum Mill
 
Number of identified proteins
Protein pre-fractionation High confidencea Low confidenceb Total identified proteinsc
1-D pre-fractionationd
2354
1066
3420
2-D pre-fractionatione
 
 
 
 Fr. 1 (pH 3–4.6)
1189
708
1897
 Fr. 2 (pH 4.6-5.4)
1753
827
2580
 Fr. 3 (pH 5.4-6.2)
1423
886
2309
 Fr. 4 (pH6.2-7.0)
2228
909
3137
 Fr. 5 (pH 7.0-10.0)
1699
841
2540
Total numberf
8292
4171
12463
Total distinct proteinsg
4322
1875
6197
Total distinct genesh
 
 
2085
B Proteins identified by Mascot
1-D pre-fractionationd
543
261
804
2-D pre-fractionatione
 
 
 
 Fr. 1 (pH 3–4.6)
268
123
391
 Fr. 2 (pH 4.6-5.4)
393
178
571
 Fr. 3 (pH 5.4-6.2)
370
139
509
 Fr. 4 (pH6.2-7.0)
562
171
733
 Fr. 5 (pH 7.0-10.0)
416
147
563
Total numberf
2009
758
2767
Total distinct proteinsg
1340
477
1817
Total distinct genesh     1478

aThe number of identified proteins with two or more peptide matches counted by using the non-redundant dataset of identified proteins. bThe number of identified proteins with one peptide match counted by using non-redundant dataset of identified proteins. cThe sum of the number of identified proteins with high confidence and low confidence as defined above. dGlomerular proteins were directly separated into 15 fractions by one-dimensional (1-D) SDS-PAGE. eGlomerular proteins were separated into 5 fractions with different pI ranges by solution-phase IEF in the first dimension and each fraction was further separated into 15 fractions by 1-D SDS-PAGE in the second dimension. fThe sum of the numbers of proteins identified in each fraction of 2-D pre-fractionation with high confidence or low-confidence as defined above. gThe sum of identified proteins counted by using the non-redundant dataset created by merging all the identified proteins in fractions of 1-D and 2-D pre-fractionation. hTotal distinct proteins included proteins derived from the same genes. In order to identify total distinct genes, the same gene symbols dispersed in the dataset were processed in an Excel work sheet to merge into one gene symbol by using the “Remove Duplicate” command.