Embryo-scale, single-cell spatial transcriptomics Article Swipe
YOU?
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· 2021
· Open Access
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· DOI: https://doi.org/10.1126/science.abb9536
Localizing gene expression Single-cell RNA sequencing can provide information about cellular relationships based on shared transcriptomes, but most methods lose spatial information. Those methods that do retain spatial information can be limited to a specific set of genes and/or a small area. Srivatsan et al. introduce sci-Space, a spatial transcriptomic method that uses a grid of barcoded oligos on a slide that can be transferred to nuclei of an overlaid frozen tissue section to obtain both the spatial origin and the transcriptome of thousands of single cells per slide. The researchers used sci-Space to create a spatial atlas of mouse E14 sagittal sections, revealing spatially expressed genes across cell types. This application illustrates how sci-Space complements existing approaches in spatial genomics. Science , abb9536, this issue p. 111
Related Topics
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1126/science.abb9536
- OA Status
- green
- Cited By
- 247
- References
- 42
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W3176766013
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W3176766013Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1126/science.abb9536Digital Object Identifier
- Title
-
Embryo-scale, single-cell spatial transcriptomicsWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2021Year of publication
- Publication date
-
2021-07-01Full publication date if available
- Authors
-
Sanjay Srivatsan, Mary C. Regier, Eliza Barkan, Jennifer M. Franks, Jonathan S. Packer, Parker Grosjean, Madeleine Duran, Sarah H. Saxton, Jon J. Ladd, Malte Spielmann, Carlos Lois, Paul D. Lampe, Jay Shendure, Kelly R. Stevens, Cole TrapnellList of authors in order
- Landing page
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https://doi.org/10.1126/science.abb9536Publisher landing page
- Open access
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YesWhether a free full text is available
- OA status
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greenOpen access status per OpenAlex
- OA URL
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https://www.ncbi.nlm.nih.gov/pmc/articles/9118175Direct OA link when available
- Concepts
-
Embryo, Scale (ratio), Transcriptome, Computational biology, Biology, Computer science, Cell biology, Geography, Genetics, Gene expression, Cartography, GeneTop concepts (fields/topics) attached by OpenAlex
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247Total citation count in OpenAlex
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2025: 35, 2024: 60, 2023: 71, 2022: 65, 2021: 16Per-year citation counts (last 5 years)
- References (count)
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42Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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