cntools 1.0.0

A package for identifying cellular neighborhoods

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 v2.0.1.

Installation guide

As we need a conda package pydot=1.4.2 (not a pip one), the package can be installed by

conda create -n cntools python=3.8 pydot=1.4.2
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 cn/*/CNE folder. Expected analysis outputs are in the 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.