pepsipy 0.1.0

A package to calculate peptide features.

PEPSI: PEPtide Sequence Information

[!NOTE] This repository is still a work in progress.

PEPSI is an open-source Python package that provides methods for computing a wide range of peptide features, including sequence composition, charge, hydrophobicity, and other physicochemical properties. All features can be calculated on an entire dataset or on a single peptide sequence of interest. Additionally, PEPSI offers a selection of visualisations, such as hydropathy profile or amino acid classification. This work was conducted as part of the project 'Veni, Vidi, Visualization: Improving Analysis Communication for a Million-Dollar Machine' at the Data Analytics and Computational Statistics Chair, Hasso Plattner Institute.

💻 Python package	📊 Web-based dashboard	Miscellaneous
Installation Usage	Installation Usage	Third-party resources License

💻 Python package

Installation

[!CAUTION] The release of the package on PyPI is still pending. See related issue for any updates.

1. Make sure you have pip installed
2. Update pip in your console
   python -m pip install --upgrade pip
3. Install PEPSI
   pip install pepsi
4. Import and use PEPSI in your project!

Usage

1. Initialize a calculator instance

   import pandas as pd
   from pepsi import Calculator
   calc = Calculator(
      dataset=pd.read_csv("data/peptides.csv"),
      metadata=pd.read_csv("data/metadata.csv"),
      seq="SVIDQSRVLNLGPITR",
   )
   

2. Select desired features and plots with related parameters

   calc.set_feature_params(
      gravy=True,
      molecular_weight=True,
   )
   calc.set_plot_params(
      hydropathy_profile=True,
      classification=True,
      classification_classify_by="charge",
   )
   

3. Compute and show results

   print(calc.get_features())
   plots = calc.get_plots()
   for plot in plots:
      plot.show()
   

📊 Web-based dashboard

Installation

1. Make sure you have a virtual environment manager installed, e.g., Conda (recommended), or any other manager such as venv or Poetry.
2. Clone this repository and enter the frontend folder
   

   git clone https://github.com/ronjakrg/thesis-pepsi-package.git
   cd thesis-pepsi-package/frontend
   

3. Create a virtual environment and install all necessary requirements
   

   conda create pepsi
   conda activate pepsi
   pip install -r requirements.txt
   

4. Start the server
   

   python manage.py runserver
   

5. Open http://127.0.0.1:8000/ in the browser of your choice to use the PEPSI Dashboard!

Usage

1. Select a dataset and a metadata file (must be uploaded to the /data folder) and a peptide sequence of interest.
2. Select desired features and plots with related parameters
3. Click on 'Calculate' and inspect results

Third-party resources

Type	Name	DOI	Saved in
Dataset	Urinary peptidomics in youths with and without type 1 diabetes	10.1074/mcp.RA119.001858	- /data/peptides.csv - /data/metadata.csv
Code	Isoelectric Point Calculator 2.0	10.1093/nar/gkab295	- /src/pepsi/external/ipc-2.0.1

License

This project is licensed under the MIT License.