Wavelet-based peak detection and a new charge inference procedure for MS/MS implemented in ProteoWizard's msConvert

Area of Science:

• Proteomics
• Computational Biology
• Mass Spectrometry

Background:

• Proteomics tandem mass spectrometry (MS/MS) data analysis relies on robust signal processing.
• Existing software may be vendor-specific, limiting cross-platform applicability.
• High-quality, universal algorithms are needed for reproducible inter- and intralaboratory studies.

Purpose of the Study:

• To implement and evaluate novel signal processing algorithms within the ProteoWizard software.
• To provide vendor-neutral tools for enhanced proteomics data analysis.
• To assess the performance of new algorithms against existing commercial and vendor software.

Main Methods:

• Integration of a wavelet-based peak-picker (CantWaiT) into ProteoWizard.
• Implementation of a precursor charge determination algorithm (Turbocharger) into ProteoWizard.
• Comparative analysis of identified peptides and precursor mass accuracy across multiple mass spectrometer platforms (Waters, Agilent, AB SCIEX, Thermo).

Main Results:

• The implemented algorithms (CantWaiT and Turbocharger) provided comparable peptide identification rates to vendor and commercial software.
• Mass accuracy of matched precursor ions was favorable compared to existing tools.
• Analysis runtimes were efficient (1-100 ms per spectrum), suitable for large datasets.

Conclusions:

• The enhanced ProteoWizard software offers high-quality, universal signal processing tools for proteomics MS/MS data.
• These additions facilitate cross-platform analysis and support large-scale clinical and research applications.
• The developed algorithms are effective and efficient for diverse proteomics workflows.