Integrating single-cell and spatial transcriptomics to elucidate intercellular tissue dynamics.
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IF: 59.581
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Cited by: 311
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Abstract

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.

Keywords

ISS
Spatial Transcriptomics

MeSH terms

Animals
Cell Communication
Computational Biology
Humans
Sequence Analysis, RNA
Single-Cell Analysis
Software
Transcriptome

Authors

Longo, Sophia K
Guo, Margaret G
Ji, Andrew L
Khavari, Paul A

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