Journal of Computer Science & Systems Biology

SpADS: An R Script for Mass Spectrometry Data Preprocessing before Data Mining

Abstract

Luca Belmonte, Rosanna Spera and Claudio Nicolini

The recent application of Mass Spectrometry (MS) to Nucleic Acid Programmable Protein Array (NAPPA) technique for proteins identification by non-classical methods leads to the needs of more sophisticated algorithm for peak recognition. NAPPA technique allows for functional proteins to be synthesized in situ directly from printed cDNAs but faces the difficulty generated by the presence of master mix and lysate molecules peaks appearing as background in the overall spectra. A wide range of tools are available to analyze proteins conventional mass spectra corresponding to few molecular species. None of them is optimized for background subtraction. Moreover, peak identification is performed by statistical analysis on characteristics peaks and thus background subtraction can alter outcome by erasing characteristic peaks. A first attempt to overcome the so far discussed problem is here discussed. The result of this effort is the development of SpADS: Spectrum Analyzer and Data Set manager-an R script for MS data preprocessing-therein discussed. SpADS provides useful preprocessing functions such binning and peak extractions, as available tools, and provides functions of spectra background subtraction and dataset managing. It is entirely developed in R, thus free of charge. A cluster k means implementation is here used to improve results of SpADS preprocessing on test datasets and on NAPPA expressed proteins.