FLiPPR: A Processor for Limited Proteolysis (LiP) Mass Spectrometry Data Sets Built on FragPipe

Area of Science:

• Proteomics
• Structural Biology
• Bioinformatics

Background:

• Limited proteolysis mass spectrometry (LiP-MS) offers proteome-wide protein structural information.
• LiP-MS data analysis presents unique challenges and can be time-consuming compared to standard proteomics workflows.
• Existing methods may not fully leverage missing data or provide robust statistical analysis for structural changes.

Purpose of the Study:

• To introduce FLiPPR (FragPipe LiP Processor), a novel tool for streamlined LiP-MS data analysis.
• To enhance the robustness and reduce redundancy in LiP-MS datasets through advanced processing techniques.
• To lower the barrier for LiP-MS adoption and standardize its statistical analysis.

Main Methods:

• FLiPPR processes data output from the FragPipe quantitative proteomics software.
• It employs a specific data imputation heuristic to utilize missing data for identifying structural changes.
• The tool incorporates a data merging scheme and protein-centric multiple hypothesis correction.

Main Results:

• FLiPPR formalizes data imputation for more significant structural change reporting.
• Introduces data merging and protein-centric multiple hypothesis correction for robust datasets.
• Reanalysis of published data with the FragPipe/FLiPPR workflow strengthens statistical trends.

Conclusions:

• FLiPPR facilitates LiP-MS data analysis, making protein structure insights more accessible.
• The tool standardizes statistical procedures and systematizes output for LiP-MS data.
• FLiPPR aims to enable larger-scale integration of LiP-MS data in future research.