scMultiome

Single-Cell Multimodal Integration Pipeline for scRNA-seq + scATAC-seq

A complete end-to-end pipeline integrating paired scRNA-seq and scATAC-seq data (10x Multiome, SHARE-seq, SNARE-seq) using scGLUE and MOFA+, with automatic cell type annotation and gene regulatory network (GRN) inference.

Features

• Multimodal Integration: scGLUE (graph-linked unified embedding) + MOFA+ (multi-omics factor analysis)
• Cell Type Annotation: Marker-based annotation validated across both RNA and ATAC modalities
• GRN Inference: Peak → gene regulatory links via GLUE cosine similarity + TF motif scanning
• Standard Output: UMAP plots, cluster labels, peak-gene links, GRN edges, reproducible .h5mu bundle

Quick Start

Installation

pip install muon scanpy scglue anndata mofapy2 leidenalg python-igraph \
matplotlib seaborn pandas numpy scipy \
--break-system-packages -q

Run on PBMC Demo Data (auto-downloads)

from multiome import run_multiome_skill

mdata, metrics, grn = run_multiome_skill(
out_dir="multiome_results_demo",
run_scglue=True,
run_mofa=True,
run_grn=True,
max_epochs=100  # reduce for faster demo
)

With Your Own Data