Validation of MS/MS Identifications and Label-Free Quantification Using Proline

Abstract

In the proteomics field, the production and publication of reliable mass spectrometry (MS)-based label-free quantitative results is a major concern. Due to the intrinsic complexity of bottom-up proteomics experiments (requiring aggregation of data relating to both precursor and fragment peptide ions into protein information, and matching this data across samples), inaccuracies and errors can occur throughout the data-processing pipeline. In a classical label-free quantification workflow, the validation of identification results is critical since errors made at this first stage of the workflow may have an impact on the following steps and therefore on the final result. Although false discovery rate (FDR) of the identification is usually controlled by using the popular target–decoy method, it has been demonstrated that this method can sometimes lead to inaccurate FDR estimates. This protocol shows how Proline can be used to validate identification results by using the method based on the Benjamini–Hochberg procedure and then quantify the identified ions and proteins in a single software environment providing data curation capabilities and computational efficiency.