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)
| File | Size | Uploaded | |
|---|---|---|---|
| ccnet-1.0.3.tar.gz | 93.3 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| 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
| Download URL | ccnet-1.0.3.tar.gz |
|---|---|
| Size | 93.3 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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| Uploaded via |
twine/3.7.1 importlib_metadata/4.8.1 pkginfo/1.8.2 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.60.0 CPython/3.8.6
|
Release files / ccnet-1.0.3-cp38-cp38-win_amd64.whl
| Download URL | ccnet-1.0.3-cp38-cp38-win_amd64.whl |
|---|---|
| Size | 71.8 kB |
| Tags | CPython 3.8 Windows x86-64 |
|
SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/3.7.1 importlib_metadata/4.8.1 pkginfo/1.8.2 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.60.0 CPython/3.8.6
|