生物
计算生物学
转录组
核糖核酸
单细胞分析
细胞
空间组织
进化生物学
遗传学
基因
基因表达
作者
Sophia K. Longo,Margaret Guo,Andrew L. Ji,Paul A. Khavari
标识
DOI:10.1038/s41576-021-00370-8
摘要
Single-cell RNA sequencing (scRNA-seq) identifies cell subpopulations within tissue but does not capture their spatial distribution nor reveal local networks of intercellular communication acting in situ. A suite of recently developed techniques that localize RNA within tissue, including multiplexed in situ hybridization and in situ sequencing (here defined as high-plex RNA imaging) and spatial barcoding, can help address this issue. However, no method currently provides as complete a scope of the transcriptome as does scRNA-seq, underscoring the need for approaches to integrate single-cell and spatial data. Here, we review efforts to integrate scRNA-seq with spatial transcriptomics, including emerging integrative computational methods, and propose ways to effectively combine current methodologies. Combining single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics can localize transcriptionally characterized single cells within their native tissue context. This Review discusses methodologies and tools to integrate scRNA-seq with spatial transcriptomics approaches, and illustrates the types of insights that can be gained.
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