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randomly
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A Library for Denoising Single-Cell Data with Random Matrix Theory

Last updated May 13, 2026
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README

======== Randomly ========

.. image:: https://img.shields.io/pypi/v/randomly.svg :target: https://pypi.python.org/pypi/randomly

.. image:: https://img.shields.io/travis/luisaparicio/randomly.svg :target: https://travis-ci.org/luisaparicio/randomly

.. image:: https://readthedocs.org/projects/randomly/badge/?version=latest :target: https://randomly.readthedocs.io/en/latest/?badge=latest :alt: Documentation Status

.. image:: https://pyup.io/repos/github/luisaparicio/randomly/shield.svg :target: https://pyup.io/repos/github/luisaparicio/randomly/ :alt: Updates

A Library for Denoising Single-Cell Data with Random Matrix Theory

  • Free software: MIT license
  • Instructions and Tutorial: http://52.201.223.58:1234/

Features


Randomly only works with Python 3 (not Python 2). The easiest way to install Randomly is via the command line with pip:

.. code-block:: shell pip install randomly

It's convenient to run Randomly in a Jupyter Notebook_.

You can find detailed instructions and a hosted tutorial or one that can be run from your local machine.

.. _Jupyter Notebook: http://jupyter.org/ .. _hosted: http://52.201.223.58:1234/ .. _local: https://github.com/RabadanLab/randomlypage

Credits


This package was created with Cookiecutter and the audreyr/cookiecutter-pypackage project template.

.. _Cookiecutter: https://github.com/audreyr/cookiecutter .. _audreyr/cookiecutter-pypackage: https://github.com/audreyr/cookiecutter-pypackage

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