flippr 0.2.1

FragPipe Limited-Proteolysis Processor (FLiPPR) is modular, fast, and easy-to-use data processing tool for LiP-MS & LFQ-based experiments analyzed in FragPipe

Table of Contents

• Overview
• Support
• Installation
• Usage
• License
• Citation

Overview

FLiPPR (FragPipe Limited-Proteolysis Processor) is modular, fast, and easy-to-use data processing tool for LiP-MS experiments analyzed in FragPipe.

FLiPPR is:

• Super Fast: FLiPPR utilizes Polars in the back-end to ensure all CPU cores contribute to your data processing.
• Convinent to Use: FragPipe produces standarized outputs, FLiPPR takes full advantage of this feat and integrates seemlessly with any FragPipe LFQ DDA or DIA anaylsis.
• Flexible and Expandable: Experiments introduce unique and novel variables, FLiPPR ensures compatibility with all experimental setups and gives you full control of the data processing pipeline.

Support

FLiPPR requires python ≥3.10 To learn more about how FLiPPR can help you analyze your LiP-MS or LFQ data, head over to the FLiPPR docs

Installation

    # Initial install
    python -m pip install flippr

    # Update to latest release
    python -m pip install -U flippr

Usage

1. Start a Study

import flippr

study = flippr.Study(lip = "path/to/fragpipe_output", method="dda")

2. View the experimental sample annotations

print(study.samples)
# >>> { 'LiP': {'WT', '1x_Drug', '5x_Drug'}

3. Add an experimental process

study.add_process(pid="1x", ctrl="WT", test="1x_Drug", n_rep=3)

study.add_process(pid="5x", ctrl="WT", test="5x_Drug", n_rep=3)

4. Run your study

results = study.run()

results
# >>> {'1x': <flippr.Results>, '5x': <flippr.Results>}

5. View or save your results as Polars DataFrames

results["1x"].ion

# View higher-order results
results["1x"].modified_peptide
results["1x"].peptide
results["1x"].cut_site

# View protein-level summary of all data
results["1x"].protein_summary

Learn about all the ways FLiPPR can analyze your data by heading over to the FLiPPR docs

License

This project is licensed under the CC BY-NC-ND 4.0 License. Feel free to use the code according to the terms specified in the license.

Thank you for your interest in FLiPPR! If you encounter any issues or have suggestions, please open an issue. We appreciate your feedback!

Citation

If you found this work helpful in your research, please cite us!

FLiPPR: A Processor for Limited Proteolysis (LiP) Mass Spectrometry Data Sets Built on FragPipe
Edgar Manriquez-Sandoval, Joy Brewer, Gabriela Lule, Samanta Lopez, and Stephen D. Fried
Journal of Proteome Research
DOI: 10.1021/acs.jproteome.3c00887