title: MetAssign: probabilistic annotation of metabolites from LC-MS data using a Bayesian clustering approach.
abstract: BACKGROUND
  The use of liquid chromatography coupled to mass spectrometry has enabled the high-throughput profiling of the metabolite composition of biological samples. However, the large amount of data obtained can be difficult to analyse and often requires computational processing to understand which metabolites are present in a sample. This article looks at the dual problem of annotating peaks in a sample with a metabolite, together with putatively annotating whether a metabolite is present in the sample. The starting point of the approach is a Bayesian clustering of peaks into groups, each corresponding to putative adducts and isotopes of a single metabolite.
  
  
  RESULTS
  The Bayesian modelling introduced here combines information from the mass-to-charge ratio, retention time and intensity of each peak, together with a model of the inter-peak dependency structure, to increase the accuracy of peak annotation. The results inherently contain a quantitative estimate of confidence in the peak annotations and allow an accurate trade-off between precision and recall. Extensive validation experiments using authentic chemical standards show that this system is able to produce more accurate putative identifications than other state-of-the-art systems, while at the same time giving a probabilistic measure of confidence in the annotations.
  
  
  METHODS
  The software has been implemented as part of the mzMatch metabolomics analysis pipeline, which is available for download at http://mzmatch.sourceforge.net/.
authors.affiliation: School of Computing Science, University of Glasgow, Glasgow, Manchester Institute of Biotechnology, Faculty of Life Sciences, University of Manchester, Manchester and Institute of Infection, Immunity and Inflammation, University of Glasgow, Glasgow, UK.
authors.forename: Rónán
authors.initials: R
authors.lastname: Daly
authors.affiliation: School of Computing Science, University of Glasgow, Glasgow, Manchester Institute of Biotechnology, Faculty of Life Sciences, University of Manchester, Manchester and Institute of Infection, Immunity and Inflammation, University of Glasgow, Glasgow, UK.
authors.forename: Simon
authors.initials: S
authors.lastname: Rogers
authors.affiliation: School of Computing Science, University of Glasgow, Glasgow, Manchester Institute of Biotechnology, Faculty of Life Sciences, University of Manchester, Manchester and Institute of Infection, Immunity and Inflammation, University of Glasgow, Glasgow, UK.
authors.forename: Joe
authors.initials: J
authors.lastname: Wandy
authors.affiliation: School of Computing Science, University of Glasgow, Glasgow, Manchester Institute of Biotechnology, Faculty of Life Sciences, University of Manchester, Manchester and Institute of Infection, Immunity and Inflammation, University of Glasgow, Glasgow, UK.
authors.forename: Andris
authors.initials: A
authors.lastname: Jankevics
authors.affiliation: School of Computing Science, University of Glasgow, Glasgow, Manchester Institute of Biotechnology, Faculty of Life Sciences, University of Manchester, Manchester and Institute of Infection, Immunity and Inflammation, University of Glasgow, Glasgow, UK.
authors.forename: Karl E V
authors.initials: KE
authors.lastname: Burgess
authors.affiliation: School of Computing Science, University of Glasgow, Glasgow, Manchester Institute of Biotechnology, Faculty of Life Sciences, University of Manchester, Manchester and Institute of Infection, Immunity and Inflammation, University of Glasgow, Glasgow, UK.
authors.forename: Rainer
authors.initials: R
authors.lastname: Breitling
mesh_terms: D000465:Algorithms; D001499:Bayes Theorem; D002853:Chromatography, Liquid / Q000379:methods*; D016000:Cluster Analysis; D003544:Cysteic Acid / Q000032:analysis; D003627:Data Interpretation, Statistical; D013058:Mass Spectrometry / Q000379:methods*; D055432:Metabolomics; D016011:Normal Distribution; D011336:Probability; D015203:Reproducibility of Results; D012984:Software; D014230:Triazoles / Q000032:analysis
chemical_list: D014230:Triazoles; D003544:Cysteic Acid