In PMBio/MuDataMAE: Serialization for MultiAssayExperiment Objects

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Introduction

Multimodal data format — MuData — has been introduced to address the need for cross-platform standard for sharing large-scale multimodal omics data. Importantly, it develops ideas of and is compatible with AnnData standard for storing raw and derived data for unimodal datasets.

In Bioconductor, multimodal datasets have been stored in MultiAssayExperiment (MAE) objects. This MuData package provides functionality to read data from MuData files into MAE objects as well as to save MAE objects into H5MU files.

Installation

The most recent dev build can be installed from GitHub:

library(remotes)
remotes::install_github("ilia-kats/MuData")

Stable version of MuData will be available in future bioconductor versions.

Loading libraries

library(MuData)
library(MultiAssayExperiment)

library(rhdf5)

Writing H5MU files

We'll use a simple MAE object from the MultiAssayExperiment package that we'll then save in a H5MU file.

data(miniACC)
miniACC

We will now write its contents into an H5MU file with WriteH5MU:

writeH5MU(miniACC, "miniacc.h5mu")

Reading H5MU files

We can manually check the top level of the structure of the file:

rhdf5::h5ls("miniacc.h5mu", recursive = FALSE)

Or dig deeper into the file:

h5 <- rhdf5::H5Fopen("miniacc.h5mu")
h5&'mod'
rhdf5::H5close()

Creating MAE objects from H5MU files

This package provides ReadH5MU to create an object with data from an H5MU file. Since H5MU structure has been designed to accommodate more structured information than MAE, only some data will be read. For instance, MAE has no support for loading multimodal embeddings or pairwise graphs.

acc <- readH5MU("miniacc.h5mu")
acc

Importantly, we recover the information from the original MAE object:

head(colData(miniACC)[,1:4])
head(colData(acc)[,1:4])

Features metadata is also recovered:

head(rowData(miniACC[["gistict"]]))
head(rowData(acc[["gistict"]]))

Backed objects

It is possible to read H5MU files while keeping matrices (both .X and .layers) on disk.

acc_b <- readH5MU("miniacc.h5mu", backed = TRUE)
assay(acc_b, "RNASeq2GeneNorm")[1:5,1:3]

The data in the assay is a DelayedMatrix object:

class(assay(acc_b, "RNASeq2GeneNorm"))

This is in contrast to the acc object that has matrices in memory:

assay(acc, "RNASeq2GeneNorm")[1:5,1:3]
class(assay(acc, "RNASeq2GeneNorm"))

References

• Muon: multimodal omics analysis framework preprint

• mudata (Python) documentation

• muon documentation and web page

Session Info

sessionInfo()

PMBio/MuDataMAE documentation built on Oct. 20, 2023, 12:14 p.m.