simo-multiomics-integration-agent - AI Multi-omics Spatial Integration
Spatial integration of multi-omics datasets using probabilistic alignment
Tags
Updated: 2026-03-20Capabilities
Typical Inputs
Typical Outputs
What this skill does
- normalize single-cell multi-omics data
- learn joint latent representations
- compute cell-to-spot assignment probabilities
- transfer modalities to spatial coordinates
- identify spatial niches
- quantify mapping uncertainty
Inputs
- spatial transcriptomics data
- scRNA-seq reference data
- scATAC-seq reference data
- scMethyl reference data
Outputs
- integrated spatial multi-omics object
- spatial cell type assignments
- spatial niche maps
- uncertainty maps
Requirements
- Python 3.10+
- Scanpy
- Squidpy
- Muon
- scvi-tools
- SnapATAC2
- PyTorch
- GPyTorch