NiCo: Niche analysis of single-cell resolution of spatial cells

NiCo spatial analysis

Infer cellular crosstalk from imaging-based spatial transcriptomics and scRNAseq data

The Niche Covariation (NiCo) package is developed for the integration of single-cell resolution spatial transcriptomics and scRNA-seq data to (1) perform cell type annotations in the spatial modality by label transfer, (2) predict niche cell type interactions within local neighborhoods, and (3) infer cell state covariation and the underlying molecular crosstalk in the niche. NiCo infers factors capturing cell state variability in both modalities and identifies genes correlated to these latent factors for the prediction of ligand-receptor interactions and factor-associated pathways.

Highlights of NiCo

  1. Annotations of cell types in spatial data by label transfer

  2. Prediction of niche interactions using neighborhood analysis

  3. Covariation analysis of latent factors across niche cell types

  4. Prediction of ligand-receptor interactions mediating niche crosstalk

  5. Inference of pathways aassociated with covarying cell states

Installation

Note

Please install using following commands:

conda create -n nicoUser python=3.11
conda activate nicoUser
pip install nico-sc-sp
pip install jupyterlab

For more details, follow the python package index guidelines from nico-sc-sp pypi

Tutorials

Please prepare the input files with scRNA-seq count data and cell type annotation (cluster partition), spatial count data, and spatial cell coordinates to run the complete NiCo tutorials.

Nico tutorials are available here

Contents:

Indices and tables