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Fig. 1 | Clinical Proteomics

Fig. 1

From: Quality assessment and interference detection in targeted mass spectrometry data using machine learning

Fig. 1

Targeted MS workflow with manual and automated peak quality assessment. a Targeted MS workflows such as selected reaction monitoring (SRM), multiple reaction monitoring (MRM) and parallel reaction monitoring (PRM) generate chromatographic peak groups, representing relative abundance of transitions (peptide and fragment ion pairs). Several factors such as poor chromatography, interference and matrix effects can compromise the quality of these peaks and subsequently the accuracy of the reported quantitative results. Therefore, the peaks undergo manual inspection by a trained analyst to identify such anomalies, a process that is oftentimes time-consuming and subjective. b In the developed automated QC process, a dataset of pre-annotated peaks is used to build a model to predict the quality of the chromatographic peaks generated from SRM, MRM and PRM workflows

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