Detecting and aligning peaks in mass spectrometry data with applications to MALDI

Weichuan Yu, Baolin Wu, Ning Lin, Kathy Stone, Kenneth Williams, Hongyu Zhao

Research output: Contribution to journalArticlepeer-review

40 Scopus citations

Abstract

In this paper, we address the peak detection and alignment problem in the analysis of mass spectrometry data. To deal with the peak redundancy problem existing in the MALDI data acquired in the reflectron mode, we propose to use the amplitude modulation technique in peak detection. The alignment of two peak sets is formulated as a non-rigid registration problem and is solved using a robust point matching (RPM) approach. To align multiple peak sets, we first use a super set method to find a common peak set among all peak sets as a standard and then align all peak sets to the standard using the robust point matching approach in a sequential manner (i.e. We align only one peak set to the standard each time, thus reducing the multiple peak set alignment problem to a simpler two peak set alignment problem). Experimental results from a study of ovarian cancer data set show that the quantitative cross-correlation coefficients among technical replicates are increased after peak alignment. Additional comparisons also demonstrate that our method has a similar performance as the hierarchical clustering method, although the implementations of these methods are different.

Original languageEnglish (US)
Pages (from-to)27-38
Number of pages12
JournalComputational Biology and Chemistry
Volume30
Issue number1
DOIs
StatePublished - Feb 2006

Bibliographical note

Funding Information:
This work was supported with Federal funds from NHLBI/NIH contract N01-HV-28186, NIDA/NIH grant 1 P30 DA018343-01, NIGMS R01-59507, and NSF grant DMS-0241160.

Keywords

  • Biomarker discovery
  • Envelope detection
  • Mass spectrometry peak detection
  • Non-rigid point matching
  • Peak alignment
  • Super set

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