Minimum information about a proteomics experiment - Quality Control
Quality control (QC) is increasingly recognized as a crucial aspect of mass spectrometry based proteomics. As a result, software tools for computing quality control metrics for mass spectrometry data started to proliferate in recent years. However, As the different tools that compute the diverse metrics from experimental LC-MS/MS data can extract only a limited number of QC features, it is a challenging task to compare and interactively analyze the outputs of these tools. In addition, the data reported by different individuals is often missing key pieces essential for a full understanding of the experiment and the possibility of meta-analysis. Here, we propose MIAPE-QC, the Minimal Information. Adherence to this reporting guideline will result in increased clarity of publications and support the effectiveness and accuracy of investigations based on the experimental proteomics data.
- Collected qc metrics and mapping metrics throuh existing CVs.
- Extracted minimal metrics for MIAPE-QC (extracted 40 QC metrics from all the metrics collected from QC tools and 9 essential parameters/descriptors from experimental reprots and MIAPE-like documents)
- Added title, authors and abstract as a start point of MIAPE-QC based on Martin's suggestion.
- Added some metrics to the QC Wishing list after talked with experts and experimenters in Beijing (Phenix Center).
- Updated the old version of MIAPE-QC list.
- Adjust the classification of metrics and parameters in MIAPE-QC.
- Complete the definition/details/reasons of all the terms shown in the checklist.