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

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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

DOI 10.1146/annurev-biodatasci-080917-013452

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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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Reviewer #3 (Public Review): Deciphering deep-sea chemosynthetic symbiosis by single-nucleus RNA-sequencing
(2024) · eLife · doi:10.7554/elife.88294.3.sa1
Reviewer #2 (Public Review): Deciphering deep-sea chemosynthetic symbiosis by single-nucleus RNA-sequencing
(2024) · eLife · doi:10.7554/elife.88294.3.sa2
Author response: Deciphering deep-sea chemosynthetic symbiosis by single-nucleus RNA-sequencing
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eLife Assessment: Deciphering deep-sea chemosynthetic symbiosis by single-nucleus RNA-sequencing
Paz‐García, D. A. (2024) · eLife · doi:10.7554/elife.88294.3.sa4

Authors: Chen, X., Teichmann, S. A., & Meyer, K. B.
Affiliations: Wellcome Sanger Institute (GB)
European Bioinformatics Institute (GB)
ORCID: Chen, Xi
Teichmann, Sarah A.
Meyer, Kerstin B.
Venue: Annual Review of Biomedical Data Science
Publisher: Annual Reviews
Published: 2018-07-20
Volume: 1
Issue: 1
Pages: 29-51
ISSN: 2574-3414 (ISSN-L)
DOI: 10.1146/annurev-biodatasci-080917-013452
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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From Tissues to Cell Types and Back: Single-Cell Gene Expression Analysis of Tissue Architecture

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