Cited by 112Single-cell and spatial transcriptomicsGene expression and cancer classificationGenomics and Phylogenetic Studies

From tissues to cell types and back: single-cell gene expression analysis of tissue architecture

Chen, Xi, Teichmann, Sarah A., Meyer, Kerstin B.·2018·Annual Review of Biomedical Data Science

Abstract

With the recent transformative developments in single-cell genomics and, in particular, single-cell gene expression analysis, it is now possible to study tissues at the single-cell level, rather than having to rely on data from bulk measurements. Here we review the rapid developments in single-cell RNA sequencing (scRNA-seq) protocols that have the potential for unbiased identification and profiling of all cell types within a tissue or organism. In addition, novel approaches for spatial profiling of gene expression allow us to map individual cells and cell types back into the three-dimensional context of organs. The combination of in-depth single-cell and spatial gene expression data will reveal tissue architecture in unprecedented detail, generating a wealth of biological knowledge and a better understanding of many diseases.

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Crossref · 10.1146/annurev-biodatasci-080917-013452

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  • Single-cell RNA-seq enables the quantification of RNA abundance at the resolution of individual cells.

    “Single-cell RNA-seq (scRNA-seq) enables the quantification of RNA abundance at the resolution of individual cells4.”

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Authors
Chen, X., Teichmann, S. A., & Meyer, K. B.
Affiliations
  • Wellcome Sanger Institute (GB)
  • European Bioinformatics Institute (GB)
Venue
Annual Review of Biomedical Data Science
Published
2018-07-20
Volume
1
Issue
1
Pages
29-51
ISSN
2574-3414 (ISSN-L)
OpenAlex
W2803942859
Cited by
112
References
127
Citations by year
2026: 1 · 2025: 6 · 2024: 14 · 2023: 12 · 2022: 17 · 2021: 20 · 2020: 21 · 2019: 17 · 2018: 4
FWCI
1.55
Type
journal article
Language
en
Open access
closed
Locations
Annual Review of Biomedical Data Science (publishedVersion)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene expression and cancer classification
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
Keywords
single-cell RNA sequencing, tissue structure, cell types, spatial gene expression profiling, single-cell genomics, cell type annotation, spatial transcriptomics

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