转录组
生物
计算生物学
电池类型
单元格排序
基因表达谱
核糖核酸
单细胞分析
基因表达
细胞生物学
基因
细胞
肝细胞
医学
肝病
内科学
病理
生物信息学
肝星状细胞
肝细胞
遗传学
作者
Angela Chu,Joel D. Schilling,Kevin R. King,Ariel E. Feldstein
出处
期刊:Hepatology
[Wiley]
日期:2021-01-01
卷期号:73 (1): 437-448
被引量:17
摘要
Single cell transcriptomics has emerged as a powerful lens through which to study the molecular diversity of complex tissues such as the liver, during health and disease, both in animal models and in humans. The earliest gene expression methods measured bulk tissue RNA, but the results were often confusing because they derived from the combined transcriptomes of many different cell types in unknown proportions. To better delineate cell-type-specific expression, investigators developed cell isolation, purification, and sorting protocols, yet still, the RNA derived from ensembles of cells obscured recognition of cellular heterogeneity. Profiling transcriptomes at the single-cell level has opened the door to analyses that were not possible in the past. In this review, we discuss the evolution of single cell transcriptomics and how it has been applied for the study of liver physiology and pathobiology to date.
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