杠杆(统计)
计算生物学
背景(考古学)
计算机科学
领域(数学)
转录组
空间语境意识
功能(生物学)
数据科学
生物
空间分析
基因表达
基因
数据挖掘
生物信息学
人工智能
遗传学
地理
古生物学
遥感
数学
纯数学
作者
Lambda Moses,Lior Pachter
出处
期刊:Nature Methods
[Springer Nature]
日期:2022-03-10
卷期号:19 (5): 534-546
被引量:623
标识
DOI:10.1038/s41592-022-01409-2
摘要
The function of many biological systems, such as embryos, liver lobules, intestinal villi, and tumors, depends on the spatial organization of their cells. In the past decade, high-throughput technologies have been developed to quantify gene expression in space, and computational methods have been developed that leverage spatial gene expression data to identify genes with spatial patterns and to delineate neighborhoods within tissues. To comprehensively document spatial gene expression technologies and data-analysis methods, we present a curated review of literature on spatial transcriptomics dating back to 1987, along with a thorough analysis of trends in the field, such as usage of experimental techniques, species, tissues studied, and computational approaches used. Our Review places current methods in a historical context, and we derive insights about the field that can guide current research strategies. A companion supplement offers a more detailed look at the technologies and methods analyzed: https://pachterlab.github.io/LP_2021/ .
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