- C. Bielow
- G. Mastrobuoni
- S. Kempa
- Journal of Proteome Research
- J Proteome Res 15 (3): 777-787
Mass spectrometry-based proteomics coupled to liquid chromatography has matured into an automatized, high-throughput technology, producing data on the scale of multiple gigabytes per instrument per day. Consequently, an automated quality control (QC) and quality analysis (QA), capable of detecting measurement bias, verifying consistency and avoiding propagation of error is paramount for instrument operators and scientists in charge of downstream analysis. We have developed an R-based quality control pipeline called Proteomics Quality Control (PTXQC) for bottom-up LC-MS data generated by the MaxQuant software pipeline. PTXQC creates a quality control report containing a comprehensive and powerful set of quality control metrics, augmented with automated scoring functions. The automated scores are collated to create an overview heatmap at the beginning of the report, giving valuable guidance also to non-specialists. Our software supports a wide range of experimental designs, including stable isotope labeling by amino acids in cell culture (SILAC), Tandem Mass Tags (TMT) and label-free data. Furthermore, we introduce new metrics to score MaxQuant's Match-between-runs (MBR) functionality by which peptide identifications can be transferred across Raw files based on accurate RT and m/z. Last but not least, PTXQC is easy to install and use and represents the first QC software capable of processing MaxQuant result tables. PTXQC is freely available at https://github.com/cbielow/PTXQC.