https://github.com/gagneurlab/autocorrection

The autoencoder implementation for the OUTRIDER package
https://github.com/gagneurlab/autocorrection

autoencoder expression-analysis outlier-detection pyhton rna-seq

Last synced: about 1 month ago
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The autoencoder implementation for the OUTRIDER package

• Host: GitHub
• URL: https://github.com/gagneurlab/autocorrection
• Owner: gagneurlab
• License: mit
• Created: 2018-03-24T00:52:07.000Z (about 7 years ago)
• Default Branch: master
• Last Pushed: 2018-05-09T03:02:28.000Z (about 7 years ago)
• Last Synced: 2025-03-25T14:38:56.303Z (2 months ago)
• Topics: autoencoder, expression-analysis, outlier-detection, pyhton, rna-seq
• Language: Jupyter Notebook
• Homepage:
• Size: 30.1 MB
• Stars: 2
• Watchers: 4
• Forks: 3
• Open Issues: 0
• Metadata Files:
  • Readme: README.rst
  • Changelog: CHANGELOG.rst
  • Contributing: CONTRIBUTING.rst
  • License: LICENSE
  • Authors: AUTHORS.rst

Awesome Lists containing this project

README

        
========

Overview

========

.. start-badges

.. list-table::

    :stub-columns: 1

    * - package

      - | |Version| |Build| |Wheel| |License|

.. |version| image:: https://img.shields.io/pypi/v/autoCorrection.svg

    :alt: PyPI Package latest release

    :target: https://pypi.python.org/pypi/autoCorrection

.. |Build| image::  https://travis-ci.org/gagneurlab/autoCorrection.svg?branch=master

    :alt: Build status

    :target: https://travis-ci.org/gagneurlab/autoCorrection

.. |wheel| image:: https://img.shields.io/pypi/wheel/autoCorrection.svg

    :alt: PyPI Wheel

    :target: https://pypi.python.org/pypi/autoCorrection

.. |License| image:: https://img.shields.io/github/license/mashape/apistatus.svg?maxAge=2592000

    :alt: License MIT

    :target: https://github.com/gagneurlab/autoCorrection/blob/master/LICENSE

.. end-badges

* Free software: MIT license

Activate virtual environment

==================

Together with the autoCorrection package you will get

        'tensorflow',

        'keras',

        'numpy',

        'kopt',

        'scipy',

        'h5py',

        'sklearn',

        'pandas',

        'statsmodels',

        'pytest'

packages automatically installed, if not present.

If you don't wannt to install these packages globally, please use virtual environment.

If you have problems with virtualenv, installing using conda may help:

(Installation of conda: https://conda.io/docs/user-guide/install/index.html)

Make sure you are using python 3.

    conda create -n mypyth3 python=3.6

    source activate mypyth3

    conda install virtualenv

activate new environment in active python 3 environment:

    virtualenv env-with-autoCorrection

    source env-with-autoCorrection/bin/activate

Check if you are still using python 3:

    python --version

Package Installation

============

::

    pip install autoCorrection

Deactivate virtual environment

============

::

    deactivate

Usage

============

::

    #in python:

    python

    import autoCorrection

    import numpy as np

    counts = np.random.negative_binomial(n = 20, p=0.2, size = (10,8))

    sf = np.ones((10,8))

    corrector = autoCorrection.correctors.AECorrector()

    c = corrector.correct(counts = counts, size_factors = sf)

    #in R:

    library(reticulate)

    autoCorrection <- import("autoCorrection")

    corrected <- autoCorrection$correctors$AECorrector(model_name, model_directory)$correct(COUNTS, SIZE_FACTORS, only_predict=FALSE)

Documentation

=============

https://i12g-gagneurweb.in.tum.de/public/docs/autocorrection/