A package for identifying cellular neighborhoods
Project description
CNTools
System requirements
The software denpendencies are listed in pyproject.toml
. The software is independent of operating systems. The version the software has been tested on is v2.0.5.
Installation guide
As we need a conda package pydot=1.4.2 (not a pip one), the package should be installed by
conda create -n cntools python=3.8 pydot=1.4.2
python -m pip install cntools
Instructions for use
Idenfity and smooth cellular neighborhoods
See tests/test_crc.ipynb
for CRC dataset, tests/test_t2d.ipynb
for T2D dataset, and tests/test_hlt.ipynb
for HLT dataset.
Analyze cellular neighborhoods
See jupyter notebooks in the tests/analysis
folder.
Demo
Run tests/test_crc.ipynb
, tests/test_t2d.ipynb
, and tests/test_hlt.ipynb
for CN identification and smoothing. Run jupyter notebooks in the tests/analysis/
folder for CN analyses. Expected CN outputs are in the tests/cn/*/CNE/
folder. Expected analysis outputs are in the tests/analysis_res/*/CNE/
folder.
Acknowledgements
Our implementation adapts the code of Spatial LDA, Schurch et al. (2020), and Bhate et al. (2022) as cellular neighborhood identification and analysis methods. We thank the authors for sharing their code.
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