Singapore Immunology Network (SIgN), Agency for Science, Technology and Research (A*STAR), 8A Biomedical Grove, Immunos Building, Level 3, Singapore 138648, Singapore.
Shanghai Institute of Immunology, Shanghai JiaoTong University School of Medicine, Shanghai 200025, China.
Nucleic Acids Res. 2022 Jan 7;50(D1):D596-D602. doi: 10.1093/nar/gkab1020.
The ability to study cellular heterogeneity at single cell resolution is making single-cell sequencing increasingly popular. However, there is no publicly available resource that offers an integrated cell atlas with harmonized metadata that users can integrate new data with. Here, we present DISCO (https://www.immunesinglecell.org/), a database of Deeply Integrated Single-Cell Omics data. The current release of DISCO integrates more than 18 million cells from 4593 samples, covering 107 tissues/cell lines/organoids, 158 diseases, and 20 platforms. We standardized the associated metadata with a controlled vocabulary and ontology system. To allow large scale integration of single-cell data, we developed FastIntegration, a fast and high-capacity version of Seurat Integration. We also developed CELLiD, an atlas guided automatic cell type identification tool. Employing these two tools on the assembled data, we constructed one global atlas and 27 sub-atlases for different tissues, diseases, and cell types. DISCO provides three online tools, namely Online FastIntegration, Online CELLiD, and CellMapper, for users to integrate, annotate, and project uploaded single-cell RNA-seq data onto a selected atlas. Collectively, DISCO is a versatile platform for users to explore published single-cell data and efficiently perform integrated analysis with their own data.
单细胞分辨率研究细胞异质性的能力使得单细胞测序越来越受欢迎。然而,目前还没有公开的资源提供集成的细胞图谱,其中包含协调的元数据,用户可以将新数据与之集成。在这里,我们介绍了 DISCO(https://www.immunesinglecell.org/),这是一个深度整合的单细胞组学数据数据库。DISCO 的当前版本整合了来自 4593 个样本的超过 1800 万个细胞,涵盖 107 种组织/细胞系/类器官、158 种疾病和 20 种平台。我们使用受控词汇表和本体系统对相关元数据进行了标准化。为了允许大规模整合单细胞数据,我们开发了 FastIntegration,这是一种快速且大容量的 Seurat 整合版本。我们还开发了 CELLiD,这是一种图谱引导的自动细胞类型识别工具。在组装的数据上使用这两个工具,我们构建了一个全局图谱和 27 个针对不同组织、疾病和细胞类型的子图谱。DISCO 提供了三个在线工具,即 Online FastIntegration、Online CELLiD 和 CellMapper,供用户将上传的单细胞 RNA-seq 数据集成、注释和投射到选定的图谱上。总之,DISCO 是一个多功能平台,供用户探索已发表的单细胞数据,并有效地对自己的数据进行集成分析。