Title: An approach to assessing peptide mass spectral quality without prior information

Authors: Fang-Xiang Wu, Jiarui Ding, Guy G. Poirier

Addresses: Department of Mechanical Engineering, Division of Biomedical Engineering, University of Saskatchewan, Saskatoon, SK, S7N 5A9, Canada. ' Department of Mechanical Engineering, University of Saskatchewan, Saskatoon, SK, S7N 5A9, Canada. ' Health and Environment Unit, Eastern Quebec Proteomics Center, Laval University Medical Research Center (CHUL), Ste-Foy, Quebec, G1V 4G2, Canada

Abstract: This paper proposes an approach to assessing the quality of tandem mass spectra without any prior information. The proposed approach includes: filtering noises from the experimental mass spectra and extracting the peaks; mapping each spectrum into a feature vector which describes the quality of spectra; classifying spectra into clusters by using the mean-shift clustering; learning a classifier using the two clusters with the extreme means; assessing all spectra by using the trained classifier. Computational experiments illustrate that the proposed approach can eliminate majority of poor quality spectra while losing very minority of high quality spectra.

Keywords: tandem mass spectrum; quality assessment; fisher linear discriminant analysis; mass spectrometers; peptide mass spectral quality; noise filtering; feature vectors; clustering; classifier training.

DOI: 10.1504/IJFIPM.2008.020184

International Journal of Functional Informatics and Personalised Medicine, 2008 Vol.1 No.2, pp.140- 155

Published online: 08 Sep 2008 *

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