title: Towards automated discrimination of lipids versus peptides from full scan mass spectra.
abstract: Although physicochemical fractionation techniques play a crucial role in the analysis of complex mixtures, they are not necessarily the best solution to separate specific molecular classes, such as lipids and peptides. Any physical fractionation step such as, for example, those based on liquid chromatography, will introduce its own variation and noise. In this paper we investigate to what extent the high sensitivity and resolution of contemporary mass spectrometers offers viable opportunities for computational separation of signals in full scan spectra. We introduce an automatic method that can discriminate peptide from lipid peaks in full scan mass spectra, based on their isotopic properties. We systematically evaluate which features maximally contribute to a peptide versus lipid classification. The selected features are subsequently used to build a random forest classifier that enables almost perfect separation between lipid and peptide signals without requiring ion fragmentation and classical tandem MS-based identification approaches. The classifier is trained onin silicodata, but is also capable of discriminating signals in real world experiments. We evaluate the influence of typical data inaccuracies of common classes of mass spectrometry instruments on the optimal set of discriminant features. Finally, the method is successfully extended towards the classification of individual lipid classes from full scan mass spectral features, based on input data defined by the Lipid Maps Consortium.
authors.affiliation: College of Inter-faculty Individual Studies in Mathematics and Natural Sciences, University of Warsaw, Warsaw, Poland ; Institute of Informatics, University of Warsaw, Warsaw, Poland.
authors.forename: Piotr
authors.initials: P
authors.lastname: Dittwald
authors.affiliation: Department of Mathematics and Computer Science, University of Antwerp, Antwerp, Belgium ; Biomedical Informatics Research Center Antwerp (biomina), University of Antwerp/Antwerp University Hospital, Edegem, Belgium.
authors.forename: Vu Trung
authors.initials: VT
authors.lastname: Nghia
authors.affiliation: Mass Spectrometry Research Center and Departments of Biochemistry, Chemistry, Pharmacology, and Medicine, Vanderbilt University, Nashville, USA.
authors.forename: Glenn A
authors.initials: GA
authors.lastname: Harris
authors.affiliation: Mass Spectrometry Research Center and Departments of Biochemistry, Chemistry, Pharmacology, and Medicine, Vanderbilt University, Nashville, USA.
authors.forename: Richard M
authors.initials: RM
authors.lastname: Caprioli
authors.affiliation: Mass Spectrometry Research Center and Departments of Biochemistry, Chemistry, Pharmacology, and Medicine, Vanderbilt University, Nashville, USA.
authors.forename: Raf
authors.initials: R
authors.lastname: Van de Plas
authors.affiliation: Department of Mathematics and Computer Science, University of Antwerp, Antwerp, Belgium ; Biomedical Informatics Research Center Antwerp (biomina), University of Antwerp/Antwerp University Hospital, Edegem, Belgium.
authors.forename: Kris
authors.initials: K
authors.lastname: Laukens
authors.affiliation: Institute of Informatics, University of Warsaw, Warsaw, Poland ; Mossakowski Medical Research Centre, Polish Academy of Sciences, Warsaw, Poland.
authors.forename: Anna
authors.initials: A
authors.lastname: Gambin
authors.affiliation: Applied Bio & molecular Systems, VITO, Mol, Belgium ; Center for Proteomics, Antwerp, Belgium ; Interuniversity Institute for Biostatistics and Statistical Bioinformatics, Hasselt University, Diepenbeek, Belgium.
authors.forename: Dirk
authors.initials: D
authors.lastname: Valkenborg