Peak detection in mass spectrometry by gabor filters and envelope analysis

Nha H. Nguyen, Heng Huang, Soontorn Oraintara, An Vo

Research output: Contribution to journalArticle

13 Citations (Scopus)

Abstract

Mass Spectrometry (MS) is increasingly being used to discover diseases-related proteomic patterns. The peak detection step is one of the most important steps in the typical analysis of MS data. Recently, many new algorithms have been proposed to increase true position rate with low false discovery rate in peak detection. Most of them follow two approaches: one is the denoising approach and the other is the decomposing approach. In the previous studies, the decomposition of MS data method shows more potential than the first one. In this paper, we propose two novel methods, named GaborLocal and GaborEnvelop, both of which can detect more true peaks with a lower false discovery rate than previous methods. We employ the method of Gaussian local maxima to detect peaks, because it is robust to noise in signals. A new approach, peak rank, is defined for the first time to identify peaks instead of using the signal-to-noise ratio. Meanwhile, the Gabor filter is used to amplify important information and compress noise in the raw MS signal. Moreover, we also propose the envelope analysis to improve the quantification of peaks and remove more false peaks. The proposed methods have been performed on the real SELDI-TOF spectrum with known polypeptide positions. The experimental results demonstrate that our methods outperform other commonly used methods in the Receiver Operating Characteristic (ROC) curve.

Original languageEnglish (US)
Pages (from-to)547-569
Number of pages23
JournalJournal of Bioinformatics and Computational Biology
Volume7
Issue number3
DOIs
StatePublished - Jun 19 2009
Externally publishedYes

Fingerprint

Gabor filters
Mass spectrometry
Mass Spectrometry
Polypeptides
Noise
Signal to noise ratio
Decomposition
Signal-To-Noise Ratio
Peptides
ROC Curve
Proteomics

Keywords

  • Envelope analysis
  • Gabor filter
  • Gaussian local maxima
  • Mass spectrometry
  • Peak detection
  • Peak rank

ASJC Scopus subject areas

  • Biochemistry
  • Molecular Biology
  • Computer Science Applications

Cite this

Peak detection in mass spectrometry by gabor filters and envelope analysis. / Nguyen, Nha H.; Huang, Heng; Oraintara, Soontorn; Vo, An.

In: Journal of Bioinformatics and Computational Biology, Vol. 7, No. 3, 19.06.2009, p. 547-569.

Research output: Contribution to journalArticle

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