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Table 4 Results for filtering of non-peptide masses.

From: Analytical model of peptide mass cluster centres with applications

   Arabidopsis t. Rhodopirelulla b. Mus musculus
1 Identification no PR filtering 423 1009 872
2 Identification with PR filtering 432 1017 894
3 Change in identification (Percent) 2.13 0.79 2.52
4 Total nr. of samples* 818 1169 1709
5 Nr. samples with PBMS increase 240 622 724
6 Nr. samples with no change of PBMS 571 542 982
7 Nr. samples with PBMS decrease 7 5 3
8 Percent increase of PBMS score 29.34 53.21 42.36
9 Percent decrease of PBMS score 0.86 0.43 0.18
  1. Columns: Arabidopsis t., Rhodopirelulla b., Mus musculus – peptide mass fingerprint datasets (cf. Methods). Row 1 – number of samples with a significant PBMS score prior to filtering of non-peptide peak masses. Row 2 – number of samples with a significant PBMS score for peak-lists with non-peptide removed. Row 3 – relative change of the identification rate (Row 2 – Row 1)/Row1 100. Row 4 – Total number of samples which produced a PBMS score. Row 5 -number of samples for which an increase of the PBMS score due to non peptide peak filtering was observed. Row 6 – number of samples for which no change of the PBMS score due to non-peptide peak filtering was observed. Row 7 – number of samples for which a decrease of the PBMS score due to non-peptide peak filtering was observed. Row 8–9 – relative increase and decrease of the PBMS score, respectively.