pertpy - Perturbation Analysis in Python

Pertpy is a scverse ecosystem framework for analyzing large-scale single-cell perturbation experiments. It provides tools for harmonizing perturbation datasets, automating metadata annotation, calculating perturbation distances, and efficiently analyzing how cells respond to various stimuli like genetic modifications, drug treatments, and environmental changes.

Documentation

Please read the documentation for installation, tutorials, use cases, and more.

Installation

We recommend installing and running pertpy on a recent version of Linux (e.g. Ubuntu 24.04 LTS). No particular hardware beyond a standard laptop is required.

You can install pertpy in less than a minute via pip from PyPI:

pip install pertpy

if you want to use tascCODA, please install pertpy as follows:

pip install 'pertpy[tcoda]'

If you want to use the differential gene expression interface, please install pertpy by running:

pip install 'pertpy[de]'

Citation

Lukas Heumos, Yuge Ji, Lilly May, Tessa Green, Xinyue Zhang, Xichen Wu, Johannes Ostner, Stefan Peidli, Antonia Schumacher, Karin Hrovatin, Michaela Mueller, Faye Chong, Gregor Sturm, Alejandro Tejada, Emma Dann, Mingze Dong, Mojtaba Bahrami, Ilan Gold, Sergei Rybakov, Altana Namsaraeva, Amir Ali Moinfar, Zihe Zheng, Eljas Roellin, Isra Mekki, Chris Sander, Mohammad Lotfollahi, Herbert B. Schiller, Fabian J. Theis bioRxiv 2024.08.04.606516; doi: https://doi.org/10.1101/2024.08.04.606516

pertpy is part of the scverse® project (website, governance) and is fiscally sponsored by NumFOCUS. If you like scverse® and want to support our mission, please consider making a tax-deductible donation to help the project pay for developer time, professional services, travel, workshops, and a variety of other needs.