=======================================================
Markov Affinity-based Graph Imputation of Cells (MAGIC)
=======================================================
.. image:: https://img.shields.io/pypi/v/magic-impute.svg
:target: https://pypi.org/project/magic-impute/
:alt: Latest PyPi version
.. image:: https://img.shields.io/cran/v/Rmagic.svg
:target: https://cran.r-project.org/package=Rmagic
:alt: Latest CRAN version
.. image:: https://img.shields.io/github/workflow/status/KrishnaswamyLab/MAGIC/Unit%20Tests/master?label=Github%20Actions
:target: https://github.com/KrishnaswamyLab/MAGIC/actions
:alt: GitHub Actions Build
.. image:: https://img.shields.io/readthedocs/magic.svg
:target: https://magic.readthedocs.io/
:alt: Read the Docs
.. image:: https://zenodo.org/badge/DOI/10.1016/j.cell.2018.05.061.svg
:target: https://www.cell.com/cell/abstract/S0092-8674(18)30724-4
:alt: Cell Publication DOI
.. image:: https://img.shields.io/twitter/follow/KrishnaswamyLab.svg?style=social&label=Follow
:target: https://twitter.com/KrishnaswamyLab
:alt: Twitter
.. image:: https://img.shields.io/github/stars/KrishnaswamyLab/MAGIC.svg?style=social&label=Stars
:target: https://github.com/KrishnaswamyLab/MAGIC/
:alt: GitHub stars
Markov Affinity-based Graph Imputation of Cells (MAGIC) is an algorithm for denoising high-dimensional data most commonly applied to single-cell RNA sequencing data. MAGIC learns the manifold data, using the resultant graph to smooth the features and restore the structure of the data.
To see how MAGIC can be applied to single-cell RNA-seq, elucidating the epithelial-to-mesenchymal transition, read our `publication in Cell`_.
`David van Dijk, et al. Recovering Gene Interactions from Single-Cell Data Using Data Diffusion. 2018. Cell.`__
.. _`publication in Cell`: https://www.cell.com/cell/abstract/S0092-8674(18)30724-4
__ `publication in Cell`_
For R and MATLAB implementations of MAGIC, see
https://github.com/KrishnaswamyLab/MAGIC.
.. image:: https://raw.githubusercontent.com/KrishnaswamyLab/MAGIC/master/magic.gif
:align: center
:alt: Magic reveals the interaction between Vimentin (VIM), Cadherin-1 (CDH1), and Zinc finger E-box-binding homeobox 1 (ZEB1, encoded by colors).
*Magic reveals the interaction between Vimentin (VIM), Cadherin-1
(CDH1), and Zinc finger E-box-binding homeobox 1 (ZEB1, encoded by
colors).*
Installation
~~~~~~~~~~~~
Installation with pip
---------------------
To install with ``pip``, run the following from a terminal::
pip install --user magic-impute
Installation from GitHub
------------------------
To clone the repository and install manually, run the following from a
terminal::
git clone git://github.com/KrishnaswamyLab/MAGIC.git
cd MAGIC/python
python setup.py install --user
Usage
~~~~~
Example data
------------
The following code runs MAGIC on test data located in the MAGIC
repository::
import magic
import pandas as pd
import matplotlib.pyplot as plt
X = pd.read_csv("MAGIC/data/test_data.csv")
magic_operator = magic.MAGIC()
X_magic = magic_operator.fit_transform(X, genes=['VIM', 'CDH1', 'ZEB1'])
plt.scatter(X_magic['VIM'], X_magic['CDH1'], c=X_magic['ZEB1'], s=1, cmap='inferno')
plt.show()
magic.plot.animate_magic(X, gene_x='VIM', gene_y='CDH1', gene_color='ZEB1', operator=magic_operator)
Interactive command line
------------------------
We have included two tutorial notebooks on MAGIC usage and results
visualization for single cell RNA-seq data.
EMT data notebook:
http://nbviewer.jupyter.org/github/KrishnaswamyLab/magic/blob/master/python/tutorial_notebooks/emt_tutorial.ipynb
Bone Marrow data notebook:
http://nbviewer.jupyter.org/github/KrishnaswamyLab/magic/blob/master/python/tutorial_notebooks/bonemarrow_tutorial.ipynb
Help
~~~~
If you have any questions or require assistance using MAGIC, please
contact us at https://krishnaswamylab.org/get-help.
Raw data
{
"_id": null,
"home_page": "https://github.com/KrishnaswamyLab/MAGIC",
"name": "magic-impute",
"maintainer": "",
"docs_url": null,
"requires_python": ">=3.6",
"maintainer_email": "",
"keywords": "visualization,big-data,dimensionality-reduction,embedding,manifold-learning,computational-biology",
"author": "",
"author_email": "",
"download_url": "https://files.pythonhosted.org/packages/f8/ba/2b7c79ad9a2adedd09337ed10ad3bea8915d160e8039137f197a080949fb/magic-impute-3.0.0.tar.gz",
"platform": "",
"description": "=======================================================\nMarkov Affinity-based Graph Imputation of Cells (MAGIC)\n=======================================================\n\n.. image:: https://img.shields.io/pypi/v/magic-impute.svg\n :target: https://pypi.org/project/magic-impute/\n :alt: Latest PyPi version\n.. image:: https://img.shields.io/cran/v/Rmagic.svg\n :target: https://cran.r-project.org/package=Rmagic\n :alt: Latest CRAN version\n.. image:: https://img.shields.io/github/workflow/status/KrishnaswamyLab/MAGIC/Unit%20Tests/master?label=Github%20Actions\n :target: https://github.com/KrishnaswamyLab/MAGIC/actions\n :alt: GitHub Actions Build\n.. image:: https://img.shields.io/readthedocs/magic.svg\n :target: https://magic.readthedocs.io/\n :alt: Read the Docs\n.. image:: https://zenodo.org/badge/DOI/10.1016/j.cell.2018.05.061.svg\n :target: https://www.cell.com/cell/abstract/S0092-8674(18)30724-4\n :alt: Cell Publication DOI\n.. image:: https://img.shields.io/twitter/follow/KrishnaswamyLab.svg?style=social&label=Follow\n :target: https://twitter.com/KrishnaswamyLab\n :alt: Twitter\n.. image:: https://img.shields.io/github/stars/KrishnaswamyLab/MAGIC.svg?style=social&label=Stars\n :target: https://github.com/KrishnaswamyLab/MAGIC/\n :alt: GitHub stars\n\nMarkov Affinity-based Graph Imputation of Cells (MAGIC) is an algorithm for denoising high-dimensional data most commonly applied to single-cell RNA sequencing data. MAGIC learns the manifold data, using the resultant graph to smooth the features and restore the structure of the data.\n\nTo see how MAGIC can be applied to single-cell RNA-seq, elucidating the epithelial-to-mesenchymal transition, read our `publication in Cell`_.\n\n`David van Dijk, et al. Recovering Gene Interactions from Single-Cell Data Using Data Diffusion. 2018. Cell.`__\n\n.. _`publication in Cell`: https://www.cell.com/cell/abstract/S0092-8674(18)30724-4\n\n__ `publication in Cell`_\n\nFor R and MATLAB implementations of MAGIC, see\nhttps://github.com/KrishnaswamyLab/MAGIC.\n\n.. image:: https://raw.githubusercontent.com/KrishnaswamyLab/MAGIC/master/magic.gif\n :align: center\n :alt: Magic reveals the interaction between Vimentin (VIM), Cadherin-1 (CDH1), and Zinc finger E-box-binding homeobox 1 (ZEB1, encoded by colors).\n\n*Magic reveals the interaction between Vimentin (VIM), Cadherin-1\n(CDH1), and Zinc finger E-box-binding homeobox 1 (ZEB1, encoded by\ncolors).*\n\nInstallation\n~~~~~~~~~~~~\n\nInstallation with pip\n---------------------\n\nTo install with ``pip``, run the following from a terminal::\n\n pip install --user magic-impute\n\nInstallation from GitHub\n------------------------\n\nTo clone the repository and install manually, run the following from a\nterminal::\n\n git clone git://github.com/KrishnaswamyLab/MAGIC.git\n cd MAGIC/python\n python setup.py install --user\n\nUsage\n~~~~~\n\nExample data\n------------\n\nThe following code runs MAGIC on test data located in the MAGIC\nrepository::\n\n import magic\n import pandas as pd\n import matplotlib.pyplot as plt\n X = pd.read_csv(\"MAGIC/data/test_data.csv\")\n magic_operator = magic.MAGIC()\n X_magic = magic_operator.fit_transform(X, genes=['VIM', 'CDH1', 'ZEB1'])\n plt.scatter(X_magic['VIM'], X_magic['CDH1'], c=X_magic['ZEB1'], s=1, cmap='inferno')\n plt.show()\n magic.plot.animate_magic(X, gene_x='VIM', gene_y='CDH1', gene_color='ZEB1', operator=magic_operator)\n\nInteractive command line\n------------------------\n\nWe have included two tutorial notebooks on MAGIC usage and results\nvisualization for single cell RNA-seq data.\n\nEMT data notebook:\nhttp://nbviewer.jupyter.org/github/KrishnaswamyLab/magic/blob/master/python/tutorial_notebooks/emt_tutorial.ipynb\n\nBone Marrow data notebook:\nhttp://nbviewer.jupyter.org/github/KrishnaswamyLab/magic/blob/master/python/tutorial_notebooks/bonemarrow_tutorial.ipynb\n\nHelp\n~~~~\n\nIf you have any questions or require assistance using MAGIC, please\ncontact us at https://krishnaswamylab.org/get-help.\n\n\n",
"bugtrack_url": null,
"license": "GNU General Public License Version 2",
"summary": "MAGIC",
"version": "3.0.0",
"split_keywords": [
"visualization",
"big-data",
"dimensionality-reduction",
"embedding",
"manifold-learning",
"computational-biology"
],
"urls": [
{
"comment_text": "",
"digests": {
"blake2b_256": "7503aa7f512ec227f333a1c3d0e57b375cf3e93ff7f14b1f8b117870c7f4c842",
"md5": "ae8b60e1e78d76fdad3bfa20eb6eba92",
"sha256": "9682a23ec970174bd9c0583c1c3fc7a5ed94898f03682a839c4c2f58eb332698"
},
"downloads": -1,
"filename": "magic_impute-3.0.0-py3-none-any.whl",
"has_sig": false,
"md5_digest": "ae8b60e1e78d76fdad3bfa20eb6eba92",
"packagetype": "bdist_wheel",
"python_version": "py3",
"requires_python": ">=3.6",
"size": 15655,
"upload_time": "2021-03-11T17:49:40",
"upload_time_iso_8601": "2021-03-11T17:49:40.013397Z",
"url": "https://files.pythonhosted.org/packages/75/03/aa7f512ec227f333a1c3d0e57b375cf3e93ff7f14b1f8b117870c7f4c842/magic_impute-3.0.0-py3-none-any.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": "",
"digests": {
"blake2b_256": "f8ba2b7c79ad9a2adedd09337ed10ad3bea8915d160e8039137f197a080949fb",
"md5": "29d58e2c7ee20ae4eecaf6b5e41b707f",
"sha256": "0c3f6d17baf586c412c174709a19164f04e693fd1933a8c0399ae5c5bf1cfd7a"
},
"downloads": -1,
"filename": "magic-impute-3.0.0.tar.gz",
"has_sig": false,
"md5_digest": "29d58e2c7ee20ae4eecaf6b5e41b707f",
"packagetype": "sdist",
"python_version": "source",
"requires_python": ">=3.6",
"size": 17116,
"upload_time": "2021-03-11T17:49:41",
"upload_time_iso_8601": "2021-03-11T17:49:41.202785Z",
"url": "https://files.pythonhosted.org/packages/f8/ba/2b7c79ad9a2adedd09337ed10ad3bea8915d160e8039137f197a080949fb/magic-impute-3.0.0.tar.gz",
"yanked": false,
"yanked_reason": null
}
],
"upload_time": "2021-03-11 17:49:41",
"github": true,
"gitlab": false,
"bitbucket": false,
"github_user": "KrishnaswamyLab",
"github_project": "MAGIC",
"travis_ci": false,
"coveralls": false,
"github_actions": true,
"lcname": "magic-impute"
}
JSON
