A statistical method for chromatographic alignment of LC-MS data

Pei Wang, Hua Tang, Matthew P. Fitzgibbon, Martin McIntosh, Marc Coram, Hui Zhang, Eugene Yi, Ruedi Aebersold

Research output: Contribution to journalArticlepeer-review

Abstract

Integrated liquid-chromatography mass-spectrometry (LC-MS) is becoming a widely used approach for quantifying the protein composition of complex samples. The output of the LC-MS system measures the intensity of a peptide with a specific mass-charge ratio and retention time. In the last few years, this technology has been used to compare complex biological samples across multiple conditions. One challenge for comparative proteomic profiling with LC-MS is to match corresponding peptide features from different experiments. In this paper, we propose a new method - Peptide Element Alignment (PETAL) that uses raw spectrum data and detected peak to simultaneously align features from multiple LC-MS experiments. PETAL creates spectrum elements, each of which represents the mass spectrum of a single peptide in a single scan. Peptides detected in different LC-MS data are aligned if they can be represented by the same elements. By considering each peptide separately, PETAL enjoys greater flexibility than time warping methods. While most existing methods process multiple data sets by sequentially aligning each data set to an arbitrarily chosen template data set, PETAL treats all experiments symmetrically and can analyze all experiments simultaneously. We illustrate the performance of PETAL on example data sets.

Original languageEnglish (US)
Pages (from-to)357-367
Number of pages11
JournalBiostatistics
Volume8
Issue number2
DOIs
StatePublished - Apr 2007
Externally publishedYes

Keywords

  • Alignment
  • LC-MS
  • Regression
  • Retention time

ASJC Scopus subject areas

  • Statistics and Probability
  • Statistics, Probability and Uncertainty

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