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A continuous wavelet transform algorithm for peak detection

  • Andrew Wee
  • , David B. Grayden
  • , Yonggang Zhu*
  • , Karolina Petkovic-Duran
  • , David Smith
  • *Corresponding author for this work
  • University of Melbourne
  • CSIRO

Research output: Contribution to journalArticlepeer-review

Abstract

Contactless conductivity detector technology has unique advantages for microfluidic applications. However, the low S/N and varying baseline makes the signal analysis difficult. In this paper, a continuous wavelet transform-based peak detection algorithm was developed for CE signals from microfluidic chips. The Ridger peak detection algorithm is based on the MassSpecWavelet algorithm by Du et al. Bioinformatics 2006, 22, 2059-2065, and performs a continuous wavelet transform on data, using a wavelet proportional to the first derivative of a Gaussian function. It forms sequences of local maxima and minima in the continuous wavelet transform, before pairing sequences of maxima to minima to define peaks. The peak detection algorithm was tested against the Cromwell, MassSpecWavelet, and Linear Matrix-assisted laser desorption/ ionizationtime-of-flight-mass spectrometer Peak Indication and Classification algorithms using experimental data. Its sensitivity to false discovery rate curve is superior to other techniques tested.

Original languageEnglish
Pages (from-to)4215-4225
Number of pages11
JournalElectrophoresis
Volume29
Issue number20
DOIs
StatePublished - 2008
Externally publishedYes

Keywords

  • Microfluidics
  • Peak detection
  • Separation
  • Wavelets

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