henhaobio
Sign in

Journal of Proteome ResearchBioinformaticsPeer-reviewed journal article

Automated Assignment of Proteoform Classification Levels

Zach RolfsiD, Lloyd M. SmithiD

PDFDOIPreprint

Abstract

Proteoform identification is required to fully understand the biological diversity present in a sample. However, these identifications are often ambiguous because of the challenges in analyzing full length proteins by mass spectrometry. A five-level proteoform classification system was recently developed to delineate the ambiguity of proteoform identifications and to allow for comparisons across software platforms and acquisition methods. Widespread adoption of this system requires software tools to provide classification of the proteoform identifications. We describe here implementation of the five-level classification system in the software program MetaMorpheus, which provides both bottom-up and top-down identifications. Additionally, we developed a stand-alone program called ProteoformClassifier that allows users to classify proteoform results from any search program, provided that the program writes output that includes the information necessary to evaluate proteoform ambiguity. This stand-alone program includes a small test file and database to evaluate if a given program provides sufficient information to evaluate ambiguity. If the program does not, then ProteoformClassifier provides meaningful feedback to assist developers with implementing the classification system. We tested currently available top-down software programs and found that none of them other than MetaMorpheus provided sufficient information regarding identification ambiguity to permit classification.

Citations
4
FWCI
0.27
Field percentile
37th percentile

Reproducibility ledger

Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.

Sign in to file a reproducibility report.

Similarity Map
SelectedSame fieldCross-field
THISMahmud '26Basharat '23Wang '25Bludau '21Schiebenhoe '26Kou '15
61% semantic matchBioinformatics
Araf Mahmud, Zhihao Zhang, Si Wu+1 more·bioRxiv·Sep 15, 2026