title: Intersession reproducibility of mass spectrometry profiles and its effect on accuracy of multivariate classification models.
abstract: BACKGROUND
  The 'reproducibility' of mass spectrometry proteomic profiling has become an intensely controversial topic. The mere mention of concern over the 'reproducibility' of data generated from any particular platform can lead to the anxiety over the generalizability of its results and its role in the future of discovery proteomics. In this study, we examine the reproducibility of proteomic profiles generated by surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF-MS) across multiple data-generation sessions. We analyze the problem in terms of the reproducibility of signals, reproducibility of discriminative features and reproducibility of multivariate classification models on profiles for serum samples from early lung cancer and healthy control subjects.
  
  
  RESULTS
  Proteomic profiles in individual data-generation sessions experience within-session variability. We show that combining data from multiple sessions introduces additional (inter-session) noise. While additional noise can affect the discriminative analysis, we show that its average effect on profiles in our study is relatively small. Moreover, for the purposes of prediction on future (previously unseen) data, classifiers trained on multi-session data are able to adapt to inter-session noise and improve their classification accuracy.
authors.affiliation: Department of Computer Science, Intelligent Systems Program, University of Pittsburgh Cancer Institute and Genomics and Proteomics Core Laboratories, University of Pittsburgh, Pittsburgh, PA 15260, USA.
authors.forename: Richard
authors.initials: R
authors.lastname: Pelikan
authors.forename: William L
authors.initials: WL
authors.lastname: Bigbee
authors.forename: David
authors.initials: D
authors.lastname: Malehorn
authors.forename: James
authors.initials: J
authors.lastname: Lyons-Weiler
authors.forename: Milos
authors.initials: M
authors.lastname: Hauskrecht
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D014408:Biomarkers, Tumor / Q000097:blood*; D001774:Blood Chemical Analysis / Q000379:methods; D016000:Cluster Analysis; D005260:Female; D006801:Humans; D008175:Lung Neoplasms / Q000097:blood* / Q000175:diagnosis; D008297:Male; D013058:Mass Spectrometry / Q000379:methods*; D008875:Middle Aged; D015999:Multivariate Analysis; D009363:Neoplasm Proteins / Q000097:blood*; D010449:Peptide Mapping / Q000379:methods*; D015203:Reproducibility of Results; D018401:Sample Size; D012680:Sensitivity and Specificity
chemical_list: D014408:Biomarkers, Tumor; D009363:Neoplasm Proteins