原位
电池类型
打字
计算生物学
生物
概率逻辑
细胞
计算机科学
遗传学
人工智能
化学
有机化学
作者
Xiaoyan Qian,Kenneth D. Harris,Thomas Hauling,Dimitris Nicoloutsopoulos,Ana B. Muñoz‐Manchado,Nathan Skene,Jens Hjerling‐Leffler,Mats Nilsson
出处
期刊:Nature Methods
[Springer Nature]
日期:2019-11-18
卷期号:17 (1): 101-106
被引量:208
标识
DOI:10.1038/s41592-019-0631-4
摘要
Understanding the function of a tissue requires knowing the spatial organization of its constituent cell types. In the cerebral cortex, single-cell RNA sequencing (scRNA-seq) has revealed the genome-wide expression patterns that define its many, closely related neuronal types, but cannot reveal their spatial arrangement. Here we introduce probabilistic cell typing by in situ sequencing (pciSeq), an approach that leverages previous scRNA-seq classification to identify cell types using multiplexed in situ RNA detection. We applied this method by mapping the inhibitory neurons of mouse hippocampal area CA1, for which ground truth is available from extensive previous work identifying their laminar organization. Our method identified these neuronal classes in a spatial arrangement matching ground truth, and further identified multiple classes of isocortical pyramidal cell in a pattern matching their known organization. This method will allow identifying the spatial organization of closely related cell types across the brain and other tissues.
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