SingleCellMultiModal
is an R package that provides a
convenient and user-friendly representation of multi-modal data using
MultiAssayExperiment
. This package introduces a suite of
single-cell multimodal landmark datasets for benchmarking and testing
multimodal analysis methods via the ExperimentHub
Bioconductor package. The scope of this package is to provide efficient
access to a selection of curated, pre-integrated, publicly available
landmark datasets for methods development and benchmarking.
Your citations are crucial in keeping our software free and open source. To cite our package see the citation (Eckenrode et al. (2023)) in the Reference section. You may also browse to the publication at PLoS Computational Biology.
Users can obtain integrative representations of multiple modalities
as a MultiAssayExperiment
, a common core Bioconductor data
structure relied on by dozens of multimodal data analysis packages.
MultiAssayExperiment
harmonizes data management of multiple
experimental assays performed on an overlapping set of specimens.
Although originally developed for patient data from multi-omics cancer
studies, the MultiAssayExperiment
framework naturally
applies also to single cells. A schematic of the data structure can be
seen below. In this context, “patients” are replaced by “cells”. We use
MultiAssayExperiment
because it provides a familiar user
experience by extending SummarizedExperiment
concepts and
providing open ended compatibility with standard data classes present in
Bioconductor such as the SingleCellExperiment
.
Want to contribute to the SingleCellMultiModal
package?
We welcome contributions from the community. Please refer to our Contributing
Guidelines for more details.
For more information on the MultiAssayExperiment
data
structure, please refer to Ramos et al.
(2017) as well as the MultiAssayExperiment
vignette.