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Muon — multimodal omics data analysis framework from the scverse ecosystem. Built on the MuData container for multi-modal single-cell experiments including CITE-seq, Multiome (RNA+ATAC), TEA-seq, and
Use with AI
Install the MCP server or CLI to instantly fetch Muon documentation:
Install command
claude mcp add biocontext7 -- npx @biocontext7/mcpOr share this page: biocontext7.com/tools/muon
mofapy2 is a Python package implementing Multi-Omics Factor Analysis v2 (MOFA+) for unsupervised integration of multi-omics datasets. It identifies latent factors that capture sources of variation sha
2 shared topics • 1 shared operation
Mowgli — multi-omics Wasserstein integrated analysis using group NMF to jointly factorize paired multi-omics data (RNA, ATAC, protein/ADT) from single-cell experiments. Learns shared and modality-spec
2 shared topics • 1 shared operation
Use when working with SATURN for cross-species single-cell RNA-seq integration that combines AnnData count matrices with protein embedding TorchDicts. SATURN trains macrogene representations with k-me
2 shared topics • 1 shared operation
spatialdata is the scverse Python framework for managing, analyzing, and visualizing multi-modal spatial omics datasets. Provides a unified SpatialData object that stores images, segmentation labels,
2 shared topics • 1 shared operation
totalVI and MultiVI — deep generative models from scvi-tools for multi-modal single-cell integration. totalVI jointly models scRNA-seq and protein (CITE-seq) data via a variational autoencoder for den
2 shared topics • 1 shared operation