# NiCo
Developed by Ankit Agrawal (c) Grün lab 2023
Find covariation patterns between interacting cell types from image-based single cell resolution spatial transcriptomics data.
A package that performs cell type annotations on spatial transcriptomics data, finds the niche interactions and covariation patterns between interacting cell types.
Ready for use! Tutorials and Documentation are available!
## Install the NiCo package using the conda environment.
```shell
conda create -n nicoUser python=3.11
conda activate nicoUser
pip install nico-sc-sp
pip install jupyterlab
```
# Required packages built upon
By default, these packages should install automatically.
But if any version conflict exists, the user can install the specific version independently using pip command.
```shell
scanpy==1.9.6
seaborn==0.12.2
scipy==1.11.3
matplotlib==3.7.3
numpy==1.26.1
gseapy==1.0.6
xlsxwriter==3.1.9
numba==0.58.1
pydot==1.4.2
KDEpy==1.1.8
pygraphviz==1.11
networkx==3.2.1
scikit-learn==1.3.2
pandas==2.1.1
leidenalg
```
# Import the functions from the Python prompt in the following way.
```python
from nico import Annotations as sann
from nico import Interactions as sint
from nico import Covariations as scov
```
# Documentations
Please follow the NiCo documentation here.
https://nico-sc-sp.readthedocs.io/en/latest/
# Tutorials
Please follow the NiCo tutorial here.
https://github.com/ankitbioinfo/nico_tutorial
# Check out more:
Thanks to the following two utils packages used to develop NiCo.
SCTransformPy
https://github.com/atarashansky/SCTransformPy
pyliger
https://github.com/welch-lab/pyliger
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"description": "\n# NiCo\n\nDeveloped by Ankit Agrawal (c) Gr\u00fcn lab 2023\n\nFind covariation patterns between interacting cell types from image-based single cell resolution spatial transcriptomics data.\n\n\nA package that performs cell type annotations on spatial transcriptomics data, finds the niche interactions and covariation patterns between interacting cell types.\n\nReady for use! Tutorials and Documentation are available!\n\n\n## Install the NiCo package using the conda environment. \n\n```shell\nconda create -n nicoUser python=3.11\nconda activate nicoUser\npip install nico-sc-sp\npip install jupyterlab\n```\n\n# Required packages built upon\nBy default, these packages should install automatically.\nBut if any version conflict exists, the user can install the specific version independently using pip command.\n```shell\nscanpy==1.9.6\nseaborn==0.12.2\nscipy==1.11.3\nmatplotlib==3.7.3\nnumpy==1.26.1\ngseapy==1.0.6\nxlsxwriter==3.1.9\nnumba==0.58.1\npydot==1.4.2\nKDEpy==1.1.8\npygraphviz==1.11\nnetworkx==3.2.1\nscikit-learn==1.3.2\npandas==2.1.1\nleidenalg\n```\n\n# Import the functions from the Python prompt in the following way. \n\n```python\nfrom nico import Annotations as sann\nfrom nico import Interactions as sint\nfrom nico import Covariations as scov\n```\n\n# Documentations\n\nPlease follow the NiCo documentation here.\n\nhttps://nico-sc-sp.readthedocs.io/en/latest/\n\n# Tutorials\nPlease follow the NiCo tutorial here.\n\nhttps://github.com/ankitbioinfo/nico_tutorial\n\n\n# Check out more:\nThanks to the following two utils packages used to develop NiCo.\n\nSCTransformPy\n\nhttps://github.com/atarashansky/SCTransformPy\n\npyliger\n\nhttps://github.com/welch-lab/pyliger\n",
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