magic-impute 1.5.0

MAGIC

Markov Affinity-based Graph Imputation of Cells (MAGIC) is an algorithm for denoising and imputation of single cells applied to single-cell RNA sequencing data, as described in Van Dijk D et al. (2018), Recovering Gene Interactions from Single-Cell Data Using Data Diffusion, Cell https://www.cell.com/cell/abstract/S0092-8674(18)30724-4.

For R and MATLAB implementations of MAGIC, see https://github.com/KrishnaswamyLab/MAGIC.

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.