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muon is a multimodal omics Python framework.

Documentation |Tutorials |Publication

muon is designed aroundMuData (multimodal data) objects — in the same vein asscanpy andAnnData are designed to work primarily with scRNA-seq data in Python. Individual modalities inMuData are naturally represented withAnnData objects.

MuData class and.h5mu files I/O operations are part ofthe standalone mudata library.

MuData class is implemented in themudata library and is exposed inmuon:

frommuonimportMuDatamdata=MuData({'rna':adata_rna,'atac':adata_atac})

Ifmultimodal data from 10X Genomics is to be read,muon provides a reader that returns aMuData object with AnnData objects inside, each corresponding to its own modality:

importmuonasmumu.read_10x_h5("filtered_feature_bc_matrix.h5")# MuData object with n_obs × n_vars = 10000 × 80000# 2 modalities#   rna:10000 x 30000#     var:'gene_ids', 'feature_types', 'genome', 'interval'#   atac:10000 x 50000#     var:'gene_ids', 'feature_types', 'genome', 'interval'#     uns:'atac', 'files'

Basic.h5mu files I/O functionality is implemented inmudata and is exposed inmuon. AMuData object represents modalities as collections ofAnnData objects, and these collections can be saved on disk and retrieved using HDF5-based.h5mu files, which design is based on.h5ad file structure.

mdata.write("pbmc_10k.h5mu")mdata=mu.read("pbmc_10k.h5mu")

It allows to effectively use the hierarchical nature of HDF5 files and to read/write AnnData object directly from/to.h5mu files:

adata=mu.read("pbmc_10k.h5mu/rna")mu.write("pbmc_10k.h5mu/rna",adata)

muon incorporates a set of methods for multimodal omics analysis. These methods address the challenge of taking multimodal data as their input. For instance, while for a unimodal analysis one would use principal components analysis,muon comes with a method to runmulti-omics factor analysis:

# Unimodalimportscanpyasscsc.tl.pca(adata)# Multimodalimportmuonasmumu.tl.mofa(mdata)

Individual assays are stored as AnnData object, which enables the use of all the defaultscanpy functionality per assay:

importscanpyasscsc.tl.umap(mdata.mod["rna"])

Typically, a modality inside a container can be referred to with a variable to make the code more concise:

rna=mdata.mod["rna"]sc.pl.umap(rna)

muon comes with a set of modules that can be used hand in hand with scanpy's API. These modules are named after respective sequencing protocols and comprise special functions that might come in handy. It is also handy to import them as two letter abbreviations:

# ATAC module:frommuonimportatacasac# Protein (epitope) module:frommuonimportprotaspt

Some implementation details are noted inDESIGN.md.

Contributions in the form ofissues,pull requests ordiscussions are welcome.

If you usemuon in your work, please cite themuon publication as follows:

MUON: multimodal omics analysis framework

Danila Bredikhin, Ilia Kats, Oliver Stegle

Genome Biology 2022 Feb 01. doi:10.1186/s13059-021-02577-8.

You can cite the scverse publication as follows:

The scverse project provides a computational ecosystem for single-cell omics data analysis

Isaac Virshup, Danila Bredikhin, Lukas Heumos, Giovanni Palla, Gregor Sturm, Adam Gayoso, Ilia Kats, Mikaela Koutrouli, Scverse Community, Bonnie Berger, Dana Pe’er, Aviv Regev, Sarah A. Teichmann, Francesca Finotello, F. Alexander Wolf, Nir Yosef, Oliver Stegle & Fabian J. Theis

Nat Biotechnol. 2023 Apr 10. doi:10.1038/s41587-023-01733-8.

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