Introduction

Welcome to the Nico Documentation!

NiCo ( Ni che Co variation) is a tool designed for the comprehensive analysis of imaging- and sequencing-based spatial transcriptomics data. This documentation provides detailed instructions on how to use the tool, including installation, usage examples, and API references.

Key Features:

  • Cell Type Annotation: Accurate annotation of cell types in the spatial modality by label transfer.

  • Visualization of Cell Types in Space: Generation of UMAP plots and spatial maps to visualize cell types.

  • Spatial Neighborhood Analysis: Identification and analysis of cell type-cell type interactions within spatial niche neighborhoods.

  • Inference of Cell State Covariation: Analysis of molecular crosstalk of cell types co-localized in niches using latent variable regression.

  • Visualization of Ligand-Receptor Pairs: NiCo visualizes ligand-receptor pairs associated with covarying latent variables of interacting cell types.

  • Visualization of Pathways: NiCo visualizes enriched pathways in the top correlating genes associated with latent variables.

Getting Started:

To get started with NiCo, follow the installation instructions and refer to the examples and tutorials for detailed examples.

Github Tutorials:

The tutorials in Jupyter notebook format for finding covariation in selected colocalized cell type are available here, and the Python scripts for finding the covariation in all colocalized cell types is available here.

Contributing:

We welcome contributions to the project. If you would like to contribute, please refer to the contributing guidelines.

Support:

For support, please check the FAQ section.