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A reproducibility‐based evaluation procedure for quantifying the differences between MS/MS peak intensity normalization methods
Author(s) -
Degroeve Sven,
Colaert Niklaas,
Vandekerckhove Joël,
Gevaert Kris,
Martens Lennart
Publication year - 2011
Publication title -
proteomics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.26
H-Index - 167
eISSN - 1615-9861
pISSN - 1615-9853
DOI - 10.1002/pmic.201000605
Subject(s) - normalization (sociology) , reproducibility , quartile , computer science , data mining , biological system , pattern recognition (psychology) , statistics , mathematics , artificial intelligence , confidence interval , sociology , anthropology , biology
The identification of peptides and proteins from fragmentation mass spectra is a very common approach in the field of proteomics. Contemporary high‐throughput peptide identification pipelines can quickly produce large quantities of MS/MS data that contain valuable knowledge about the actual physicochemical processes involved in the peptide fragmentation process, which can be extracted through extensive data mining studies. As these studies attempt to exploit the intensity information contained in the MS/MS spectra, a critical step required for a meaningful comparison of this information between MS/MS spectra is peak intensity normalization. We here describe a procedure for quantifying the efficiency of different published normalization methods in terms of the quartile coefficient of dispersion (qcod) statistic. The quartile coefficient of dispersion is applied to measure the dispersion of the peak intensities between redundant MS/MS spectra, allowing the quantification of the differences in computed peak intensity reproducibility between the different normalization methods. We demonstrate that our results are independent of the data set used in the evaluation procedure, allowing us to provide generic guidance on the choice of normalization method to apply in a certain MS/MS pipeline application.