iBench: A ground truth approach for advanced validation of mass spectrometry identification method

The discovery of many noncanonical peptides detectable with sensitive mass spectrometry inside, outside, and on cells shepherded the development of novel methods for their identification, often not supported by a systematic benchmarking with other methods. We here propose iBench, a bioinformatic tool that can construct ground truth proteomics datasets and cognate databases, thereby generating a training court wherein methods, search engines, and proteomics strategies can be tested, and their performances estimated by the same tool. iBench can be coupled to the main database search engines, allows the selection of customized features of mass spectrometry spectra and peptides, provides standard benchmarking outputs, and is open source. The proof-of-concept application to tryptic proteome digestions, immunopeptidomes, and synthetic peptide libraries dissected the impact that noncanonical peptides could have on the identification of canonical peptides by Mascot search with rescoring via Percolator (Mascot+Percolator).

Automated summary

The discovery of noncanonical peptides using mass spectrometry has led to the development of new methods for their identification, often without proper benchmarking. This article presents iBench, a bioinformatic tool that can construct proteomics datasets and databases, allowing for testing and performance estimation of various methods and strategies. iBench can be used with database search engines, offers customizable features, provides benchmarking outputs, and is open source. In a proof-of-concept application, iBench was used to analyze the impact of noncanonical peptides on the identification of canonical peptides using Mascot search with rescoring via Percolator (Mascot+Percolator).