RabadanLab / scTDA

An object oriented python library for topological data analysis of high-throughput single-cell RNA-seq data

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scTDA

This fork is no longer maintained. Please visit github.com/pcamara/scTDA to install the latest version of scTDA.

scTDA is an object oriented python library for topological data analysis of high-throughput single-cell RNA-seq data. It includes tools for the preprocessing, analysis, and exploration of single-cell RNA-seq data based on topological representations.

To install scTDA run:

pip install scTDA

Alternatively, you can download the source code and run:

python setup.py install

For optimal visualization results it is strongly recommended to have Graphviz tools and PyGraphviz installed.

scTDA can be imported using the command:

import scTDA

A tutorial illustrating the basic scTDA workflow can be found in doc/scTDA Tutorial.html. The source notebook and data files for the tutorial can be downloaded here.

More details on the scTDA algorithm can be found in:

Rizvi, A. H.*, Camara, P. G.*, Kandror, E. K., Roberts, T. J., Scheiren, I., Maniatis, T., and Rabadan, R., "Single-Cell Topological RNA-Seq Analysis Reveals Insights Into Cellular Differentiation and Development", Nat. Biotechnol. (2017). In press. [* These authors contributed equally to this work.]

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An object oriented python library for topological data analysis of high-throughput single-cell RNA-seq data

License:GNU General Public License v3.0


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