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ccnet

Ccnet, cell-cell network, is a single-cell RNA sequencing data analysis package based on non-uniform epsilon-neighborhood network (NEN).

Features

  • Different from the traditional analysis of scRNA-seq data, which performs visualization, clustering and trajectory inference using methods based on different theories, ccnet accomplishes the three targets in a consistent manner.
  • NEN network combines the advantages of both k-neighbors (KNN) and epsilon-neighborhood (EN) to represent the intrinsic manifold of data.

Installation

Install ccnet from pip:

pip install ccnet

Or, to build and install run from source:

python setup.py install

Usage

For the usage of ccnet, please refer to the example, where we introduce the relevant analysis steps, including visualization, clustering, pseudotime ordering, finding trajectory-associated genes, etc.

Contribute

Source Code: https://github.com/Just-Jia/ccNet.git

Contacts

My email: junbo_jia@163.com

License

The project is licensed under the GNU GPLv3 license.

Release files for ccnet 1.0.3

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for ccnet 1.0.3
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ccnet-1.0.3.tar.gz 93.3 kB Details

Built distribution (wheel)

Table of built distributions (wheels) for ccnet 1.0.3
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ccnet-1.0.3-cp38-cp38-win_amd64.whl CPython 3.8 CPython 3.8 Windows x86-64 Details

Total release size: 165.2 kB

Release files / ccnet-1.0.3.tar.gz

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Size 93.3 kB
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Release files / ccnet-1.0.3-cp38-cp38-win_amd64.whl

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