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pParse: A method for accurate determination of monoisotopic peaks in high-resolution mass spectra

Authors

  • Zuo-F ei Yuan,

    1. Key Laboratory of Intelligent Information Processing – Institute of Computing Technology, Chinese Academy of Sciences, Beijing, P. R. China
    2. Graduate University of the Chinese Academy of Sciences, Beijing, P. R. China
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  • Chao Liu,

    1. Key Laboratory of Intelligent Information Processing – Institute of Computing Technology, Chinese Academy of Sciences, Beijing, P. R. China
    2. Graduate University of the Chinese Academy of Sciences, Beijing, P. R. China
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  • Hai-Peng Wang,

    1. Key Laboratory of Intelligent Information Processing – Institute of Computing Technology, Chinese Academy of Sciences, Beijing, P. R. China
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  • Rui-Xiang Sun,

    1. Key Laboratory of Intelligent Information Processing – Institute of Computing Technology, Chinese Academy of Sciences, Beijing, P. R. China
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  • Yan Fu,

    1. Key Laboratory of Intelligent Information Processing – Institute of Computing Technology, Chinese Academy of Sciences, Beijing, P. R. China
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  • Jing-Fen Zhang,

    1. Key Laboratory of Intelligent Information Processing – Institute of Computing Technology, Chinese Academy of Sciences, Beijing, P. R. China
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  • Le-Heng Wang,

    1. Key Laboratory of Intelligent Information Processing – Institute of Computing Technology, Chinese Academy of Sciences, Beijing, P. R. China
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  • Hao Chi,

    1. Key Laboratory of Intelligent Information Processing – Institute of Computing Technology, Chinese Academy of Sciences, Beijing, P. R. China
    2. Graduate University of the Chinese Academy of Sciences, Beijing, P. R. China
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  • You Li,

    1. Key Laboratory of Intelligent Information Processing – Institute of Computing Technology, Chinese Academy of Sciences, Beijing, P. R. China
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  • Li-Yun Xiu,

    1. Key Laboratory of Intelligent Information Processing – Institute of Computing Technology, Chinese Academy of Sciences, Beijing, P. R. China
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  • Wen-Ping Wang,

    1. Key Laboratory of Intelligent Information Processing – Institute of Computing Technology, Chinese Academy of Sciences, Beijing, P. R. China
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  • Si-Min He

    Corresponding author
    1. Key Laboratory of Intelligent Information Processing – Institute of Computing Technology, Chinese Academy of Sciences, Beijing, P. R. China
    • Institute of Computing Technology, Chinese Academy of Sciences, No. 6 Kexueyuan South Road, Haidian District, Beijing 100190, P. R. China Fax: +86-10-62601356
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Abstract

Determining the monoisotopic peak of a precursor is a first step in interpreting mass spectra, which is basic but non-trivial. The reason is that in the isolation window of a precursor, other peaks interfere with the determination of the monoisotopic peak, leading to wrong mass-to-charge ratio or charge state. Here we propose a method, named pParse, to export the most probable monoisotopic peaks for precursors, including co-eluted precursors. We use the relationship between the position of the highest peak and the mass of the first peak to detect candidate clusters. Then, we extract three features to sort the candidate clusters: (i) the sum of the intensity, (ii) the similarity of the experimental and the theoretical isotopic distribution, and (iii) the similarity of elution profiles. We showed that the recall of pParse, MaxQuant, and BioWorks was 98–98.8%, 0.5–17%, and 1.8–36.5% at the same precision, respectively. About 50% of tandem mass spectra are triggered by multiple precursors which are difficult to identify. Then we design a new scoring function to identify the co-eluted precursors. About 26% of all identified peptides were exclusively from co-eluted peptides. Therefore, accurately determining monoisotopic peaks, including co-eluted precursors, can greatly increase peptide identification rate.

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