title: Pinpointing biomarkers in proteomic LC/MS data by moving-window discriminant analysis.
abstract: The identification of differential patterns in data originating from combined measurement techniques such as LC/MS is pivotal to proteomics. Although "shotgun proteomics" has been employed successfully to this end, this method also has severe drawbacks, because of its dependence on largely untargeted MS/MS sequencing and databases for statistical analyses. Alternatively, several MS-signal-based (MS/MS-independent) methods have been published that are mainly based on (univariate) Student's t-tests. Here, we present a more robust multivariate alternative employing linear discriminant analysis. Like the t-test-based methods, it is applied directly to LC/MS data, instead of using MS/MS measurements. We demonstrate the method on a number of simulated data sets, as well as on a spike-in LC/MS data set, and show its superior performance over t-tests.
authors.affiliation: Radboud University Nijmegen, Institute for Molecules and Materials, Heyendaalseweg 135, 6525 AJ, Nijmegen, The Netherlands.
authors.forename: Tom G
authors.initials: TG
authors.lastname: Bloemberg
authors.forename: Hans J C T
authors.initials: HJ
authors.lastname: Wessels
authors.forename: Maurice
authors.initials: M
authors.lastname: van Dael
authors.forename: Jolein
authors.initials: J
authors.lastname: Gloerich
authors.forename: Lambert P
authors.initials: LP
authors.lastname: van den Heuvel
authors.forename: Lutgarde M C
authors.initials: LM
authors.lastname: Buydens
authors.forename: Ron
authors.initials: R
authors.lastname: Wehrens
mesh_terms: D015415:Biomarkers / Q000378:metabolism*; D002853:Chromatography, Liquid; D016002:Discriminant Analysis; D006801:Humans; D013058:Mass Spectrometry; D040901:Proteomics
chemical_list: D015415:Biomarkers