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

Github Tutorials:
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The tutorials in Jupyter notebook format for finding covariation in selected colocalized cell type are `available here, <https://github.com/ankitbioinfo/nico_tutorial>`_
and the Python scripts for finding the covariation in all colocalized cell types is `available here. <https://github.com/ankitbioinfo/nico_tutorial/blob/main/nico_analysis_highres_image_tech.py>`_

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

Support:
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For support, please check the FAQ section.