proteomicscopylot 0.1.1

ProteomicsCoPYlot project

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title: Proteomics CoPYlot sdk: docker app_port: 7860

Proteomics CoPYlot (Python Version)

Proteomics CoPYlot is a Python-based tool for proteomics data analysis and visualization, designed to simplify common workflows and provide interactive plots and light statistics for your experimental results. It can be run locally as a Python script, executable or accessed via the web at proteomics-data.com.

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Features

• Upload and analyze Spectronaut, DIA-NN, or MaxQuant output files
• Generate quality control (QC) plots: coverage, missing values, intensity distribution, and more
• Interactive visualizations with adjustable plot size, resolution, and hover-names
• Export presentation-ready figures directly from the interface
• Simple statistical summaries for quick assessment of datasets

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Installation

# Clone the repository
git clone https://github.com/JonasMarx3007/ProteomisCoPYlot.git

# Navigate to the project folder
cd ProteomisCoPYlot

# Install dependencies
pip install -r requirements.txt

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Example Workflow

1. Upload your proteomics dataset (TSV or compatible format)
2. Explore proteins and phosphosites interactively in the Streamlit interface
3. Generate quality control plots with customizable details
4. Export figures for reports or presentations

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Dependencies

Python ≥ 3.8

Required Python packages:

• streamlit
• matplotlib
• pandas
• numpy
• scikit-learn
• statsmodels
• plotly
• gprofiler-official
• biopython
• matplotlib-venn
• seaborn

Install via pip:

pip install streamlit matplotlib pandas numpy scikit-learn statsmodels plotly gprofiler-official biopython matplotlib-venn seaborn

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Usage

Run the locally using Streamlit:

streamlit run app.py

Open http://localhost:8501 in your browser to interact with the application. Or alternatively run the run_app.py.

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License

This project is licensed under the MIT License — see the LICENSE file for details.