%0 Journal Article
%A Bloemberg, Tom G.
%A J. C. T. Wessels, Hans
%A Dael, Maurice van
%A Gloerich, Jolein
%A P. van den Heuvel, Lambert
%A M. C. Buydens, Lutgarde
%A Wehrens, Ron
%D 2011
%T Pinpointing Biomarkers in Proteomic LC/MS Data by Moving-Window Discriminant Analysis
%U https://acs.figshare.com/articles/journal_contribution/Pinpointing_Biomarkers_in_Proteomic_LC_MS_Data_by_Moving_Window_Discriminant_Analysis/2634292
%R 10.1021/ac200334s.s001
%2 https://ndownloader.figshare.com/files/4285840
%K data sets
%K multivariate alternative
%K discriminant analysis
%K LC
%K Pinpointing Biomarkers
%K method
%K proteomic
%K measurement techniques
%K MS
%X 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.
%I ACS Publications