Single-Cell Virtual Cytometer allows user-friendly and versatile analysis and visualization of multimodal single cell RNAseq datasets - Archive ouverte HAL
Article Dans Une Revue NAR Genomics and Bioinformatics Année : 2020

Single-Cell Virtual Cytometer allows user-friendly and versatile analysis and visualization of multimodal single cell RNAseq datasets

Résumé

The development of single-cell transcriptomic technologies yields large datasets comprising multi-modal informations, such as transcriptomes and im-munophenotypes. Despite the current explosion of methods for pre-processing and integrating multi-modal single-cell data, there is currently no user-friendly software to display easily and simultaneously both immunophenotype and transcriptome-based UMAP/t-SNE plots from the pre-processed data. Here, we introduce Single-Cell Virtual Cytome-ter, an open-source software for flow cytometry-like visualization and exploration of pre-processed multi-omics single cell datasets. Using an original CITE-seq dataset of PBMC from an healthy donor, we illustrate its use for the integrated analysis of tran-scriptomes and epitopes of functional maturation in human peripheral T lymphocytes. So this free and open-source algorithm constitutes a unique resource for biologists seeking for a user-friendly analytic tool for multimodal single cell datasets.
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Dates et versions

hal-02861405 , version 1 (09-06-2020)

Identifiants

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Frédéric Pont, Marie Tosolini, Qing Gao, Marion Perrier, Miguel Madrid-Mencía, et al.. Single-Cell Virtual Cytometer allows user-friendly and versatile analysis and visualization of multimodal single cell RNAseq datasets. NAR Genomics and Bioinformatics, 2020, 2 (2), ⟨10.1093/nargab/lqaa025⟩. ⟨hal-02861405⟩
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