A network-based single-cell RNA-seq data analysis library
Ccnet, cell-cell network, is a single-cell RNA sequencing data analysis package based on non-uniform epsilon-neighborhood network (NEN).
- 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.
Install ccnet from pip:
pip install ccnet
Or, to build and install run from source:
python setup.py install
For the usage of ccnet, please refer to example, where we introduce the relevant analysis steps, including visualization, clustering, pseudotime ordering, finding trajectory-associated genes, etc.
Source Code: https://github.com/Just-Jia/ccNet.git
My email: email@example.com
The project is licensed under the GNU GPLv3 license.
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