Get to know muon

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muon is a Python framework for multimodal omics analysis. While there are many features that muon brings to the table, there are three key areas that its functionality is focused on.

Multimodal data containers

muon introduces multimodal data containers (muon.MuData class) allowing Python users to work with increasigly complex datasets efficiently and to build new workflows and computational tools around it.

MuData object with n_obs × n_vars = 10110 × 110101
 2 modalities
  atac: 10110 x 100001
  rna: 10110 x 10100

MuData objects enable multimodal information to be stored & accessed naturally, embrace AnnData for the individual modalities, and can be serialized to .h5mu files. Learn more about multimodal objects as well as file formats for storing & sharing them.

Multi-omics methods

muon brings multi-omics methods availability to a whole new level: state-of-the-art methods for multi-omics data integration are just a function call away.

import muon as mu
mu.tl.mofa(mdata)

Learn more about variaous multimodal integration methods that can be readily applied to muon.MuData objects.

Methods crafted for omics

muon features methods for specific omics such as ATAC-seq and CITE-seq making it an extendable solution and enabling growth in an open-source environment.

from muon import atac as ac
ac.pp.tfidf(mdata.mod['atac'])

from muon import prot as pt
pt.pp.dsb(mdata.mod['prot'])

There is atac module for chromatin accessibility data and prot module for CITE-seq data as well as additional functionality that make individual omics analysis easier.