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Ultra-fast spatial analysis toolkit for large-scale spatial single-cell data

Project description

SpatialTis

Documentation Status CI codecov pypi licence

SpatialTis is an ultra-fast spatial analysis toolkit for large-scale spatial single-cell data.

  • ✔️ Spatial Transcriptome (Non single-cell)
  • ✔️ Spatial Proteome (Single-cell)
  • 🦀 Core algorithms implements in Rust
  • 🚀 Parallel processing support

🔋 Highlighted spatial analysis

  • Cell neighbors search (KD-Tree/R-Tree/Delaunay)
  • Cell-Cell Interaction
  • Marker spatial co-expression
  • Spatial variable genes (current support: SOMDE)
  • GCNG: Inferring ligand-receptor using graph convolution network
  • Identify neighbor dependent markers

📦 Other analysis

  • Spatial distribution
  • Hotspot detection
  • Spatial auto-correlation
  • Spatial heterogeneity

Quick Start

Installation

pypi

Install the basics

pip install spatialtis

For the full features

pip install 'spatialtis[all]'

Install the current development version

pip install git+https://github.com/Mr-Milk/SpatialTis.git

Low level API

If you are interested in using low level algorithms yourself, Please refer to spatialtis_core It provides clear document for all exposed API.

Examples: IMC 1.8 millions cells

Easily run SpatialTis with large dataset in minutes.

Project details


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