%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