SMODER documentation

SMODER is a Python toolkit for spatial multi-omics deconvolution.

It provides reusable components for preprocessing, feature engineering, graph construction, model training, postprocessing, and spatial result visualization.

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
  • Result visualization and postprocessing
• Results
  • Simulated human melanoma dataset
  • Mouse brain RNA + H3K27ac peak example
  • Human breast cancer RNA + ADT example
• API Reference
  • Core model
  • Pipelines
  • Preprocessing
  • Postprocessing
  • Visualization
  • Configuration
• SMODER modules
  • omics_reconstruct()
  • get_cell_type_proportions()
  • plot_all_cell_type_proportions()
  • plot_cell_type_proportion_panel()
  • plot_embedding_spatial_clustering()
  • plot_reconstruction_heatmaps()

Indices and tables

• Index

• Module Index

• Search Page