single-cell-multiomics-integration

What problem does it solve?

This Skill enables comprehensive integration of multiple single-cell omics datasets, facilitating combined analysis and interpretation of diverse modalities.

Core Features & Use Cases

• Paired multi-omics integration: Perform joint factor analysis of RNA and ATAC data from the same cells using MOFA.
• Unpaired data alignment: Use GLUE to align separate modalities from different experiments before joint analysis.
• Batch correction across multiple studies: Apply SIMBA to harmonize multi-batch single-modality data.
• Cell label transfer: Utilize TOSICA for transferring annotations from a reference to new datasets.
• Trajectory inference: Implement StaVIA/VIA for pseudotime and lineage analysis with velocity data.

Quick Start

Load your multimodal datasets and select the appropriate integration method based on data pairing and desired analysis goal, then run the corresponding workflow steps described in the guide.