seurat-multimodal-analysis

What problem does it solve?

This skill provides a comprehensive, end-to-end workflow for multimodal single-cell analysis in R using Seurat and Signac, enabling integrated interpretation of RNA, ADT, and ATAC data within a single consistent framework.

Core Features & Use Cases

• Multi-assay object management (RNA, ADT, ATAC, peaks) and seamless integration across modalities.
• Weighted Nearest Neighbors (WNN) analysis for joint embeddings and robust clustering of multimodal data.
• CITE-seq processing (RNA + protein) and 10x Multiome workflows with chromatin accessibility analysis via Signac.
• Gene activity scoring, motif analysis with ChromVAR, peak-gene linkage, and Azimuth bridge/reference mapping for cell type annotation.
• Cross-modality integration for unpaired data and multi-sample integration workflows.

Quick Start

Load a Seurat object with RNA, ADT, and ATAC assays and run the included multimodal workflow to generate a WNN-based UMAP with basic cluster annotation.