Quantitative Performance Evaluator for Proteomics (QPEP): Web-based Application for Reproducible Evaluation of Proteomics Preprocessing Methods.
Dario StrbenacLing ZhongMark J RafteryPenghao WangSusan R WilsonNicola J ArmstrongJean Y H YangPublished in: Journal of proteome research (2017)
Tandem mass spectrometry is one of the most popular techniques for quantitation of proteomes. There exists a large variety of options in each stage of data preprocessing that impact the bias and variance of the summarized protein-level values. Using a newly released data set satisfying a replicated Latin squares design, a diverse set of performance metrics has been developed and implemented in a web-based application, Quantitative Performance Evaluator for Proteomics (QPEP). QPEP has the flexibility to allow users to apply their own method to preprocess this data set and share the results, allowing direct and straightforward comparison of new methodologies. Application of these new metrics to three case studies highlights that (i) the summarization of peptides to proteins is robust to the choice of peptide summary used, (ii) the differences between iTRAQ labels are stronger than the differences between experimental runs, and (iii) the commercial software ProteinPilot performs equivalently well at between-sample normalization to more complicated methods developed by academics. Importantly, finding (ii) underscores the benefits of using the principles of randomization and blocking to avoid the experimental measurements being confounded by technical factors. Data are available via ProteomeXchange with identifier PXD003608.
Keyphrases
- tandem mass spectrometry
- mass spectrometry
- electronic health record
- big data
- high performance liquid chromatography
- liquid chromatography
- high resolution
- ultra high performance liquid chromatography
- data analysis
- gas chromatography
- simultaneous determination
- ms ms
- small molecule
- amino acid
- deep learning
- high resolution mass spectrometry
- decision making