Multimodal omics analysis framework
Project description
MuData – multimodal data
Please refer to the MuData documentation here.
Data structure
In the same vein as AnnData is designed to represent unimodal annotated datasets in Python, MuData
is designed to provide functionality to load, process, and store multimodal omics data.
MuData
.obs -- annotation of observations (cells, samples)
.var -- annotation of features (genes, genomic loci, etc.)
.obsm -- multidimensional cell annotation,
incl. a boolean for each modality
that links .obs to the cells of that modality
.varm -- multidimensional feature annotation,
incl. a boolean vector for each modality
that links .var to the features of that modality
.mod
AnnData
.X -- data matrix (cells x features)
.obs -- cells metadata (assay-specific)
.var -- annotation of features (genes, peaks, genomic sites)
.obsm
.varm
.uns
.uns
Overview
Input
MuData
can be thought of as a multimodal container, in which every modality is an AnnData object:
from mudata import MuData
mdata = MuData({'rna': adata_rna, 'atac': adata_atac})
If multimodal data from 10X Genomics is to be read, convenient readers are provided by muon
that return a MuData
object with AnnData objects inside, each corresponding to its own modality:
import muon as mu
mu.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'
I/O with .h5mu
files
MuData
objects represent modalities as collections of AnnData objects. These collections can be saved to disk and retrieved using HDF5-based .h5mu
files, which design is based on .h5ad
file structure.
import mudata as md
mdata_pbmc.write("pbmc_10k.h5mu")
mdata = md.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 = md.read("pbmc_10k.h5mu/rna")
md.write("pbmc_10k.h5mu/rna", adata)
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