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ProbPS: A new model for peak selection based on quantifying the dependence of the existence of derivative peaks on primary ion intensity by Shenghui Zhang; Yaojun Wang; Dongbo Bu; Hong Zhang; Shiwei Sun is a Biochemistry, Genetics and Molecular Biology article available to read on EtoBox.

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## Background The analysis of mass spectra suggests that the existence of derivative peaks is strongly dependent on the intensity of the primary peaks. Peak selection from tandem mass spectrum is used to filter out noise and contaminant peaks. It is widely accepted that a valid primary peak tends to have high intensity and is accompanied by derivative peaks, including isotopic peaks, neutral loss peaks, and complementary peaks. Existing models for peak selection ignore the dependence between the existence of the derivative peaks and the intensity of the primary peaks. Simple models for peak selection assume that these two attributes are independent; however, this assumption is contrary to real data and prone to error. ## Results In this paper, we present a statistical model to quantitatively measure the dependence of the derivative peak's existence on the primary peak's intensity. Here, we propose a statistical model, named ProbPS, to capture the dependence in a quantitative manner and describe a statistical model for peak selection. Our results show that the quantitative understanding can successfully guide the peak selection process. By comparing ProbPS with AuDeNS we demonstrate

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Author

Shenghui Zhang; Yaojun Wang; Dongbo Bu; Hong Zhang; Shiwei Sun

Publisher

BioMed Central; Springer (Biomed Central Ltd.); [London]: BioMed Central, [2000]-; Springer Science and Business Media LLC; Society for Mining, Metallurgy and Exploration Inc. (ISSN 1471-2105)

Published

2011

Language

EN

Field

Biochemistry, Genetics and Molecular Biology (Life Sciences)