Curated single cell multimodal landmark datasets for R/Bioconductor

Kelly B. Eckenrode, Dario Righelli, Marcel Ramos, Ricard Argelaguet, Christophe Vanderaa, Ludwig Geistlinger, Aedin C. Culhane, Laurent Gatto, Vincent Carey, Martin Morgan, Davide Risso, Levi Waldron

Research output: Contribution to journalArticlepeer-review

Abstract

Background The 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. Results We 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. Conclusions We 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.

Original languageEnglish
Article numbere1011324
Pages (from-to)e1011324
JournalPLoS Computational Biology
Volume19
Issue number8 August
DOIs
Publication statusPublished - Aug 2023
Externally publishedYes

Fingerprint

Dive into the research topics of 'Curated single cell multimodal landmark datasets for R/Bioconductor'. Together they form a unique fingerprint.

Cite this