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.
if (!requireNamespace("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("SingleCellMultiModal")
library(SingleCellMultiModal)
library(MultiAssayExperiment)
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.
Eckenrode, Kelly B, Dario Righelli, Marcel Ramos, Ricard Argelaguet, Christophe Vanderaa, Ludwig Geistlinger, Aedin C Culhane, et al. 2023. “Curated Single Cell Multimodal Landmark Datasets for R/Bioconductor.” PLoS Comput. Biol. 19 (8): e1011324.
Ramos, Marcel, Lucas Schiffer, Angela Re, Rimsha Azhar, Azfar Basunia, Carmen Rodriguez, Tiffany Chan, et al. 2017. “Software for the Integration of Multiomics Experiments in Bioconductor.” Cancer Res. 77 (21): e39–e42.