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.

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.

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.

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