DiagnoMass: A proteomics hub for pinpointing discriminative spectral clusters

Motivation: There are several well-established paradigms for identifying and pinpointing discriminative peptides/ proteins using shotgun proteomic data; examples are peptide-spectrum matching, de novo sequencing, open searches, and even hybrid approaches. Such an arsenal of complementary paradigms can provide deep data coverage, albeit some unidentified discriminative peptides remain. Results: We present DiagnoMass, software tool that groups similar spectra into spectral clusters and then shortlists those clusters that are discriminative for biological conditions. DiagnoMass then communicates with proteomic tools to attempt the identification of such clusters. We demonstrate the effectiveness of DiagnoMass by analyzing proteomic data from Escherichia coli, Salmonella, and Shigella, listing many high-quality discriminative spectral clusters that had thus far remained unidentified by widely adopted proteomic tools. DiagnoMass can also classify proteomic profiles. We anticipate the use of DiagnoMass as a vital tool for pinpointing biomarkers. Availability: DiagnoMass and related documentation, including a usage protocol, are available at http://www. diagnomass.com.

Automated summary

DiagnoMass is a software tool that groups similar spectra into spectral clusters and then identifies those clusters that are discriminative for biological conditions. It has been successfully used to identify high-quality discriminative spectral clusters that were previously unidentified by widely adopted proteomic tools in Escherichia coli, Salmonella, and Shigella data. DiagnoMass can also classify proteomic profiles and is expected to be a vital tool for pinpointing biomarkers.