TopPICR: A Companion R Package for Top-Down Proteomics Data Analysis.

Area of Science:

• Proteomics
• Biochemistry
• Computational Biology

Background:

• Top-down proteomics analyzes intact proteins, retaining information on post-translational modifications and isoforms.
• Challenges include instrumentation limits, complex spectra interpretation, and quantification method development.
• TopPIC is a recognized tool for proteoform identification.

Purpose of the Study:

• To extend TopPIC's capabilities for label-free proteoform quantification.
• To develop a user-friendly R package (TopPICR) for this purpose.
• To integrate TopPICR with existing bioinformatics workflows.

Main Methods:

• Development of the TopPICR R package for label-free quantification.
• Implementation of key steps: identification filtering, protein accession inference, retention time alignment, mass recalibration, feature clustering, and match-between-runs quantification.
• Outputting results as an MSnSet object for Bioconductor compatibility.

Main Results:

• TopPICR successfully performs label-free quantification of proteoforms.
• The pipeline integrates seamlessly with Bioconductor packages for downstream analysis.
• Visualization tools for proteoforms within parent protein sequences are provided.

Conclusions:

• TopPICR enhances top-down proteomics by enabling robust label-free quantification.
• The package facilitates comprehensive proteoform analysis and data interpretation.
• Demonstrated utility on breast tumor xenograft datasets.