Single-Cell Virtual Cytometer allows user-friendly and versatile analysis and visualization of multimodal single cell RNAseq datasets. Issue 2 (20th April 2020)

• Record Type: Journal Article
• Authors: Pont, Frédéric; Tosolini, Marie; Gao, Qing; Perrier, Marion; Madrid-Mencía, Miguel; Huang, Tse Shun; Neuvial, Pierre; Ayyoub, Maha; Nazor, Kristopher; Fournié, Jean-Jacques
• Is Part Of: NAR genomics and bioinformatics. Volume 2:Issue 2(2020)
• Publication Date: 2020-04-20
• Subjects: Genomics -- Periodicals; Bioinformatics -- Periodicals; 572.8
• DOI: 10.1093/nargab/lqaa025
• Languages: English
• ISSNs: 2631-9268

Abstract

Abstract: The development of single-cell transcriptomic technologies yields large datasets comprising multimodal informations, such as transcriptomes and immunophenotypes. Despite the current explosion of methods for pre-processing and integrating multimodal 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 Cytometer, 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 transcriptomes 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.