Pont Frédéric, Tosolini Marie, Gao Qing, Perrier Marion, Madrid-Mencía Miguel, Huang Tse Shun, Neuvial Pierre, Ayyoub Maha, Nazor Kristopher, Fournié Jean-Jacques
Centre de Recherches en Cancérologie de Toulouse, INSERM UMR1037, Toulouse, France; Université Toulouse III Paul-Sabatier, Toulouse, France; ERL 5294 CNRS, Toulouse, France, Institut Universitaire du Cancer-Oncopole de Toulouse, Toulouse, France, laboratoire d'Excellence Toulouse Cancer, TOUCAN.
Biolegend, San Diego, CA 92121, USA.
NAR Genom Bioinform. 2020 Apr 20;2(2):lqaa025. doi: 10.1093/nargab/lqaa025. eCollection 2020 Jun.
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.
单细胞转录组技术的发展产生了包含多模态信息（如转录组和免疫表型）的大型数据集。尽管目前用于预处理和整合多模态单细胞数据的方法激增，但目前还没有用户友好的软件能够轻松、同时显示来自预处理数据的免疫表型和基于转录组的UMAP/t-SNE图。在这里，我们介绍单细胞虚拟细胞仪，这是一款用于流式细胞仪样可视化和探索预处理多组学单细胞数据集的开源软件。使用来自健康供体的原始PBMC的CITE-seq数据集，我们展示了其在人类外周血T淋巴细胞功能成熟的转录组和表位综合分析中的应用。因此，这种免费的开源算法为寻求多模态单细胞数据集用户友好分析工具的生物学家提供了独特的资源。
