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 journalArticle

5 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 languageEnglish (US)
Article number5549940
Pages (from-to)5883-5894
Number of pages12
JournalIEEE Transactions on Signal Processing
Volume58
Issue number11
DOIs
StatePublished - 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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