bio-workflows-multiome-pipeline

Joint scRNA-seq and scATAC-seq integration for 10X Multiome datasets is performed by loading both modalities, applying modality-specific QC, and using weighted nearest neighbor (WNN) analysis to generate integrated cell clusters.

You can identify gene-peak linkages and regulatory elements driving cell-type differences by applying joint RNA and ATAC processing with Seurat and Signac during downstream multiome analyses.

Automating end-to-end multiome RNA and ATAC analysis requires orchestrating single-cell data loading, preprocessing, multimodal integration, and scATAC analysis modules while enforcing QC checkpoints at RNA, ATAC, and joint analysis stages.

The multiome pipeline handles modality-specific preprocessing by independently filtering RNA and ATAC data through dedicated QC checkpoints before applying weighted nearest neighbor (WNN) integration.

A joint scRNA and scATAC clustering workflow yields integrated cell clusters, marker genes, and accessible regions, enabling the identification of regulatory elements driving cell-type differences through gene-peak linkage analyses.