Molecular & Cellular Proteomics · 2009 · 187 citations · 22 references
Life SciencesBiochemistryAnalytical ChemistryMass Spectrometric AnalysisProteomicsMass SpectrometryMass Spectrometry Data AnalysisMass Spectrometry-based ProteomicsPeptide AnalysisProteomic Quality ControlQuantitative ProteomicsAnalytical Variability AssessmentInterlaboratory ComparisonsInterlaboratory StudyLiquid Chromatography-mass SpectrometryLiquid Chromatography-mass Spectrometry AnalysisQuality AssessmentQuality Metrics For ProteomicsTandem Mass Spectrometry
A major unmet need in LC-MS/MS-based proteomics analyses is a set of tools for quantitative assessment of system performance and evaluation of technical variability. Here we describe 46 system performance metrics for monitoring chromatographic performance, electrospray source stability, MS1 and MS2 signals, dynamic sampling of ions for MS/MS, and peptide identification. Applied to data sets from replicate LC-MS/MS analyses, these metrics displayed consistent, reasonable responses to controlled perturbations. The metrics typically displayed variations less than 10% and thus can reveal even subtle differences in performance of system components. Analyses of data from interlaboratory studies conducted under a common standard operating procedure identified outlier data and provided clues to specific causes. Moreover, interlaboratory variation reflected by the metrics indicates which system components vary the most between laboratories. Application of these metrics enables rational, quantitative quality assessment for proteomics and other LC-MS/MS analytical applications.
22
Mathematical Analysis of Random Noise
S. O. Rice · Bell System Technical Journal · 1944 · 5.5K citations
Mathematical Analysis of Random Noise
S. O. Rice · Bell System Technical Journal · 1945 · 2.9K citations
TANDEM: matching proteins with tandem mass spectra
Robertson Craig, Ronald C. Beavis · Bioinformatics · 2004 · 2.6K citations · Full text