Precursor Mass Dependent Filtering of Mass Spectra for Proteomics Analysis

Identification and elimination of noise peaks in mass spectra from large proteomics data streams simultaneously improves the accuracy of peptide identification and significantly decreases the size of the data. There are a number of peak filtering strategies that can achieve this goal. Here we present a simple algorithm wherein the number of highest intensity peaks retained for further analysis is proportional to the mass of the precursor ion. We show that this technique provides an improvement over other intensity based strategies, especially for low mass precursors.