Implementation of Statistical Process Control for Proteomic Experiments Via LC MS/MS

Abstract

Statistical process control (SPC) is a robust set of tools that aids in the visualization, detection, and identification of assignable causes of variation in any process that creates products, services, or information. A tool has been developed termed Statistical Process Control in Proteomics (SProCoP) which implements aspects of SPC (e.g., control charts and Pareto analysis) into the Skyline proteomics software. It monitors five quality control metrics in a shotgun or targeted proteomic workflow. None of these metrics require peptide identification. The source code, written in the R statistical language, runs directly from the Skyline interface which supports the use of raw data files from several of the mass spectrometry vendors. It provides real time evaluation of the chromatographic performance (e.g., retention time reproducibility, peak asymmetry, and resolution); and mass spectrometric performance (targeted peptide ion intensity and mass measurement accuracy for high resolving power instruments) via control charts. Thresholds are experiment- and instrument-specific and are determined empirically from user-defined quality control standards that enable the separation of random noise and systematic error. Finally, Pareto analysis provides a summary of performance metrics and guides the user to metrics with high variance. The utility of these charts to evaluate proteomic experiments is illustrated in two case studies.

Multiplexed peptide analysis using data-independent acquisition and Skyline

“…It is recommended that QC samples be analyzed every 4–5 injections to monitor system performance 48 .…”

Design Service of QFD And SPC Methods in the Process Performance Potential Gain and Customers Value in a Company

“…The variability decrease is the key aspect of the quality improvement [17]- [20] There are two types of causes variation, assignable and standard. The assignable causes are not the regular part of the process, and we can identify them.…”

Clinical translation of MS-based, quantitative plasma proteomics: status, challenges, requirements, and potential

“…While both tools are designed for analysis of Tier 2 assaysl, Qualis-SIS was developed with the FDA requirements for standard curve generation and analysis in mind, as required for assays seeking FDA clearance/approval [95], and therefore also serves as a good resource for Tier 1 assay measurements. To help evaluate QC performance data, a statistical visualization tool -termed Statistical Process Control in Proteomics (SProCoP) tool [104] -is available through Skyline.…”