title: An introduction to statistical process control in research proteomics.
abstract: BACKGROUND
  Statistical process control is a well-established and respected method which provides a general purpose, and consistent framework for monitoring and improving the quality of a process. It is routinely used in many industries where the quality of final products is critical and is often required in clinical diagnostic laboratories [1,2]. To date, the methodology has been little utilised in research proteomics. It has been shown to be capable of delivering quantitative QC procedures for qualitative clinical assays [3] making it an ideal methodology to apply to this area of biological research.
  
  
  OBJECTIVE
  To introduce statistical process control as an objective strategy for quality control and show how it could be used to benefit proteomics researchers and enhance the quality of the results they generate.
  
  
  RESULTS
  We demonstrate that rules which provide basic quality control are easy to derive and implement and could have a major impact on data quality for many studies.
  
  
  CONCLUSIONS
  Statistical process control is a powerful tool for investigating and improving proteomics research work-flows. The process of characterising measurement systems and defining control rules forces the exploration of key questions that can lead to significant improvements in performance.
  
  
  CONCLUSIONS
  This work asserts that QC is essential to proteomics discovery experiments. Every experimenter must know the current capabilities of their measurement system and have an objective means for tracking and ensuring that performance. Proteomic analysis work-flows are complicated and multi-variate. QC is critical for clinical chemistry measurements and huge strides have been made in ensuring the quality and validity of results in clinical biochemistry labs. This work introduces some of these QC concepts and works to bridge their use from single analyte QC to applications in multi-analyte systems. This article is part of a Special Issue entitled: Standardization and Quality Control in Proteomics.
authors.affiliation: Biosignatures Ltd., Keel House, Newcastle Upon Tyne, UK. Electronic address: David.Bramwell@biosignatures.com.
authors.forename: David
authors.initials: D
authors.lastname: Bramwell
mesh_terms: D056808:Biostatistics / Q000379:methods*; D006801:Humans; D040901:Proteomics / Q000379:methods* / Q000592:standards*; D011786:Quality Control
keywords: 2-DE; Control chart; FN; FP; False negative; False positive; LC–MS; QC; Quality control; Quantitative proteomics; SPC; Statistical process control; TN; TP; True negative; True positive; VSN; Variance Stabilisation Normalisation