Bayesian peptide peak detection for high resolution TOF mass spectrometry

Jianqiu Zhang; Xiaobo Zhou; Honghui Wang; Anthony Suffredini; Lin Zhang; Yufei Huang; Stephen Wong

doi:10.1109/TSP.2010.2065226

Bayesian peptide peak detection for high resolution TOF mass spectrometry

Jianqiu Zhang, Xiaobo Zhou, Honghui Wang, Anthony Suffredini, Lin Zhang, Yufei Huang, Stephen Wong

Research output: Contribution to journal › Article › peer-review

6 Scopus citations

Abstract

In this paper, we address the issue of peptide ion peak detection for high resolution time-of-flight (TOF) mass spectrometry (MS) data. A novel Bayesian peptide ion peak detection method is proposed for TOF data with resolution of 10\thinspace 00015\thinspace 000 full width at half-maximum (FWHW). MS spectra exhibit distinct characteristics at this resolution, which are captured in a novel parametric model. Based on the proposed parametric model, a Bayesian peak detection algorithm based on Markov chain Monte Carlo (MCMC) sampling is developed. The proposed algorithm is tested on both simulated and real datasets. The results show a significant improvement in detection performance over a commonly employed method. The results also agree with expert's visual inspection. Moreover, better detection consistency is achieved across MS datasets from patients with identical pathological condition.

Original language	English (US)
Article number	5549940
Pages (from-to)	5883-5894
Number of pages	12
Journal	IEEE Transactions on Signal Processing
Volume	58
Issue number	11
DOIs	https://doi.org/10.1109/TSP.2010.2065226
State	Published - Nov 2010

Keywords

Bayesian methods
Markov chain Monte Carlo
mass spectrometry
peptide peak detection
time-of-flight

ASJC Scopus subject areas

Electrical and Electronic Engineering
Signal Processing

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10.1109/TSP.2010.2065226

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title = "Bayesian peptide peak detection for high resolution TOF mass spectrometry",

abstract = "In this paper, we address the issue of peptide ion peak detection for high resolution time-of-flight (TOF) mass spectrometry (MS) data. A novel Bayesian peptide ion peak detection method is proposed for TOF data with resolution of 10\thinspace 00015\thinspace 000 full width at half-maximum (FWHW). MS spectra exhibit distinct characteristics at this resolution, which are captured in a novel parametric model. Based on the proposed parametric model, a Bayesian peak detection algorithm based on Markov chain Monte Carlo (MCMC) sampling is developed. The proposed algorithm is tested on both simulated and real datasets. The results show a significant improvement in detection performance over a commonly employed method. The results also agree with expert's visual inspection. Moreover, better detection consistency is achieved across MS datasets from patients with identical pathological condition.",

keywords = "Bayesian methods, Markov chain Monte Carlo, mass spectrometry, peptide peak detection, time-of-flight",

author = "Jianqiu Zhang and Xiaobo Zhou and Honghui Wang and Anthony Suffredini and Lin Zhang and Yufei Huang and Stephen Wong",

note = "Funding Information: Manuscript received January 11, 2010; accepted July 14, 2010. Date of publication August 16, 2010; date of current version October 13, 2010. The associate editor coordinating the review of this manuscript and approving it for publication was Dr. Z. Jane Wang. The work of J. Zhang is funded by a San Antonio Life Sciences Institute-Research Enhancement grant and supported by a SALSI research enhancement grant and an award G12RR013646 from the National Center For Research Resources. The work of X. Zhou is funded in part by The Methodist Hospital Scholarship Award. The work of X. Zhou and S. Wong are also funded in part by NIH Grants R01LM08696, R01LM009161, and R01AG028928. The work of Y. Huang is supported by NSF Grant CCF-0546345. The work of L. Zhang is supported by the Chinese Scholarship Council.",

year = "2010",

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doi = "10.1109/TSP.2010.2065226",

language = "English (US)",

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journal = "IEEE Transactions on Signal Processing",

issn = "1053-587X",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

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AU - Zhang, Jianqiu

AU - Zhou, Xiaobo

AU - Wang, Honghui

AU - Suffredini, Anthony

AU - Zhang, Lin

AU - Huang, Yufei

AU - Wong, Stephen

N1 - Funding Information: Manuscript received January 11, 2010; accepted July 14, 2010. Date of publication August 16, 2010; date of current version October 13, 2010. The associate editor coordinating the review of this manuscript and approving it for publication was Dr. Z. Jane Wang. The work of J. Zhang is funded by a San Antonio Life Sciences Institute-Research Enhancement grant and supported by a SALSI research enhancement grant and an award G12RR013646 from the National Center For Research Resources. The work of X. Zhou is funded in part by The Methodist Hospital Scholarship Award. The work of X. Zhou and S. Wong are also funded in part by NIH Grants R01LM08696, R01LM009161, and R01AG028928. The work of Y. Huang is supported by NSF Grant CCF-0546345. The work of L. Zhang is supported by the Chinese Scholarship Council.

PY - 2010/11

Y1 - 2010/11

N2 - In this paper, we address the issue of peptide ion peak detection for high resolution time-of-flight (TOF) mass spectrometry (MS) data. A novel Bayesian peptide ion peak detection method is proposed for TOF data with resolution of 10\thinspace 00015\thinspace 000 full width at half-maximum (FWHW). MS spectra exhibit distinct characteristics at this resolution, which are captured in a novel parametric model. Based on the proposed parametric model, a Bayesian peak detection algorithm based on Markov chain Monte Carlo (MCMC) sampling is developed. The proposed algorithm is tested on both simulated and real datasets. The results show a significant improvement in detection performance over a commonly employed method. The results also agree with expert's visual inspection. Moreover, better detection consistency is achieved across MS datasets from patients with identical pathological condition.

AB - In this paper, we address the issue of peptide ion peak detection for high resolution time-of-flight (TOF) mass spectrometry (MS) data. A novel Bayesian peptide ion peak detection method is proposed for TOF data with resolution of 10\thinspace 00015\thinspace 000 full width at half-maximum (FWHW). MS spectra exhibit distinct characteristics at this resolution, which are captured in a novel parametric model. Based on the proposed parametric model, a Bayesian peak detection algorithm based on Markov chain Monte Carlo (MCMC) sampling is developed. The proposed algorithm is tested on both simulated and real datasets. The results show a significant improvement in detection performance over a commonly employed method. The results also agree with expert's visual inspection. Moreover, better detection consistency is achieved across MS datasets from patients with identical pathological condition.

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KW - time-of-flight

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Bayesian peptide peak detection for high resolution TOF mass spectrometry

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