Adaptive binning: an improved binning method for metabolomics data using the undecimated wavelet transform

Richard Davis, Adrian Charlton, John Godward, Stephen Jones, Mark Harrison, J.C. Wilson

Research output: Contribution to journalArticlepeer-review


Statistical analysis of metabolomic datasets can lead to erroneous interpretation of results due to misalignment of the data. Therefore pre-processing methods for peak alignment and data averaging (binning or bucketing) to improve data quality have been used. Here we introduce adaptive binning. The undecimated wavelet transform is used in an improved method for correcting variation in chemical shifts in nuclear magnetic resonance spectroscopy data. Adaptive binning using theoretical and metabolomics NMR spectra significantly increases the ratio of inter-class to intra-class variation and increases data interpretability when compared to conventional binning.
Original languageEnglish
Pages (from-to)144-154
Number of pages10
JournalChemometrics and Intelligent Laboratory Systems
Issue number1
Publication statusPublished - Jan 2007


  • Binning;
  • Wavelets;
  • Metabolomics;
  • Metabonomics;
  • NMR

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