SMODER documentation

Welcome to the documentation for SMODER, a Python toolkit for spatial multi-omics deconvolution.

SMODER integrates spatial transcriptomics with an additional spatial modality, such as chromatin accessibility peaks or protein measurements, to infer cell-type composition and related multi-omic signals across spatial locations.

Contents

Main contents

• Installation
  • Requirements
  • Install from PyPI
  • Install from GitHub
  • Create a Python environment
  • Current recommended execution method
  • Data preparation
• Data
  • Required input files
  • Example directory layout
  • How to obtain the data
  • How to prepare data
  • Example
  • Notes
• Tutorials
  • SMODER Tutorial 01: Mouse Brain H3K27ac Quick Start
  • SMODER Tutorial 02: Mouse Brain H3K27ac Result Visualization
  • SMODER Tutorial 03: Simulated Human Melanoma Result Visualization
  • SMODER Tutorial 04: HBC Result Visualization
• API Reference
  • Core model
  • Pipelines
  • Preprocessing
  • Postprocessing
  • Visualization
  • Configuration

Indices and tables

• Index

• Module Index

• Search Page