| Literature DB >> 29474909 |
Xiaoping Han1, Renying Wang2, Yincong Zhou3, Lijiang Fei2, Huiyu Sun2, Shujing Lai2, Assieh Saadatpour4, Ziming Zhou2, Haide Chen2, Fang Ye2, Daosheng Huang5, Yang Xu5, Wentao Huang5, Mengmeng Jiang2, Xinyi Jiang2, Jie Mao6, Yao Chen7, Chenyu Lu8, Jin Xie9, Qun Fang10, Yibin Wang11, Rui Yue11, Tiefeng Li6, He Huang12, Stuart H Orkin13, Guo-Cheng Yuan4, Ming Chen3, Guoji Guo14.
Abstract
Single-cell RNA sequencing (scRNA-seq) technologies are poised to reshape the current cell-type classification system. However, a transcriptome-based single-cell atlas has not been achieved for complex mammalian systems. Here, we developed Microwell-seq, a high-throughput and low-cost scRNA-seq platform using simple, inexpensive devices. Using Microwell-seq, we analyzed more than 400,000 single cells covering all of the major mouse organs and constructed a basic scheme for a mouse cell atlas (MCA). We reveal a single-cell hierarchy for many tissues that have not been well characterized previously. We built a web-based "single-cell MCA analysis" pipeline that accurately defines cell types based on single-cell digital expression. Our study demonstrates the wide applicability of the Microwell-seq technology and MCA resource.Entities:
Keywords: Microwell-seq; cell type classification; cellular heterogeneity; cross-tissue cellular network; mammalian cell map; mouse cell atlas; scMCA analysis; single cell RNA-seq; single-cell analysis; transcriptome analysis
Mesh：
Year: 2018 PMID： 29474909 DOI： 10.1016/j.cell.2018.02.001
Source DB: PubMed Journal: Cell ISSN： 0092-8674 Impact factor: 41.582