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Pytometry

Flow & mass cytometry analytics.

Install / Use

/learn @scverse/Pytometry
About this skill

Quality Score

0/100

Supported Platforms

Universal

README

pytometry: Flow & mass cytometry analytics

Tests Documentation

This package provides efficient and scalable handling of flow and mass cytometry data analysis. It provides

  • the functionality to read in flow data in the fcs file format as anndata objects
  • flow and mass cytometry specific preprocessing tools
  • access to the entire scanpy workflow functionality
  • GPU support through rapids-singlecell

Getting started

Please refer to the documentation. In particular, the

Installation

You need to have Python 3.11 or newer installed on your system. If you don't have Python installed, we recommend installing Mambaforge.

There are several alternative options to install pytometry:

  1. Install the latest release of pytometry from PyPI.
pip install pytometry
  1. Install the latest development version:
pip install git+https://github.com/scverse/pytometry.git@main
  1. Install locally for development:

Please refer to the Contributing Guide.

Release notes

See GitHub releases.

Contact

For questions and help requests, you can reach out in the scverse discourse. If you found a bug, please use the issue tracker.

Citation

Pytometry is currently a pre-print on bioRxiv.

pytometry 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.

<div align="center"> <a href="https://numfocus.org/project/scverse"> <img src="https://raw.githubusercontent.com/numfocus/templates/master/images/numfocus-logo.png" width="200" > </a> </div>

Related Skills

View on GitHub
GitHub Stars60
CategoryData
Updated1mo ago
Forks13

Languages

Python

Security Score

95/100

Audited on Feb 25, 2026

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