ArticlePLoS computational biology2023
Curated single cell multimodal landmark datasets for R/Bioconductor.
Article in PLoS computational biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Systematic evaluation of single-cell multimodal data integration enhances cell type resolution and discovery of clinically relevant states in complex tissues.Genome biology · 2026Article
- Key Considerations on CITE-Seq for Single-Cell Multiomics.Proteomics · 2025Review
- Benchmarking large-scale single-cell RNA-seq analysis.bioRxiv : the preprint server for biology · 2025Article
- robin2: accelerating single-cell data clustering evaluation.Bioinformatics advances · 2025Article
- EpiCHAOS: a metric to quantify epigenomic heterogeneity in single-cell data.Genome biology · 2024Article
- Stabilized mosaic single-cell data integration using unshared features.Nature biotechnology · 2024Article
- SpatialExperiment: infrastructure for spatially-resolved transcriptomics data in R using Bioconductor.Bioinformatics (Oxford, England) · 2022Article
Corrections and comments
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Authors and funding
12 authors.
Funding
Abstract
backgroundThe majority of high-throughput single-cell molecular profiling methods quantify RNA expression; however, recent multimodal profiling methods add simultaneous measurement of genomic, proteomic, epigenetic, and/or spatial information on the same cells. The development of new statistical and computational methods in Bioconductor for such data will be facilitated by easy availability of landmark datasets using standard data classes.
resultsWe collected, processed, and packaged publicly available landmark datasets from important single-cell multimodal protocols, including CITE-Seq, ECCITE-Seq, SCoPE2, scNMT, 10X Multiome, seqFISH, and G&T. We integrate data modalities via the MultiAssayExperiment Bioconductor class, document and re-distribute datasets as the SingleCellMultiModal package in Bioconductor's Cloud-based ExperimentHub. The result is single-command actualization of landmark datasets from seven single-cell multimodal data generation technologies, without need for further data processing or wrangling in order to analyze and develop methods within Bioconductor's ecosystem of hundreds of packages for single-cell and multimodal data.
conclusionsWe provide two examples of integrative analyses that are greatly simplified by SingleCellMultiModal. The package will facilitate development of bioinformatic and statistical methods in Bioconductor to meet the challenges of integrating molecular layers and analyzing phenotypic outputs including cell differentiation, activity, and disease.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.