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Integrating single-cell and spatial transcriptomics to elucidate intercellular tissue dynamics
by
Khavari, Paul A
, Guo, Margaret G
, Ji, Andrew L
, Longo, Sophia K
in
Algorithms
/ Bar codes
/ Communication
/ Computer applications
/ Disease
/ Gene expression
/ Homeostasis
/ Hybridization
/ Ligands
/ Ribonucleic acid
/ RNA
/ Spatial data
/ Spatial distribution
/ Transcription
/ Transcriptomes
/ Transcriptomics
2021
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Integrating single-cell and spatial transcriptomics to elucidate intercellular tissue dynamics
by
Khavari, Paul A
, Guo, Margaret G
, Ji, Andrew L
, Longo, Sophia K
in
Algorithms
/ Bar codes
/ Communication
/ Computer applications
/ Disease
/ Gene expression
/ Homeostasis
/ Hybridization
/ Ligands
/ Ribonucleic acid
/ RNA
/ Spatial data
/ Spatial distribution
/ Transcription
/ Transcriptomes
/ Transcriptomics
2021
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While trying to remove the title from your shelf something went wrong :( Kindly try again later!
Do you wish to request the book?
Integrating single-cell and spatial transcriptomics to elucidate intercellular tissue dynamics
by
Khavari, Paul A
, Guo, Margaret G
, Ji, Andrew L
, Longo, Sophia K
in
Algorithms
/ Bar codes
/ Communication
/ Computer applications
/ Disease
/ Gene expression
/ Homeostasis
/ Hybridization
/ Ligands
/ Ribonucleic acid
/ RNA
/ Spatial data
/ Spatial distribution
/ Transcription
/ Transcriptomes
/ Transcriptomics
2021
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Integrating single-cell and spatial transcriptomics to elucidate intercellular tissue dynamics
Journal Article
Integrating single-cell and spatial transcriptomics to elucidate intercellular tissue dynamics
2021
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Overview
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.
Publisher
Nature Publishing Group
Subject
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