Deciphering tissue structure and function using spatial transcriptomics.

> 商业许可源文 · EUROPE_PMC · [CC-BY](https://creativecommons.org/licenses/by/)

书目信息

引用：Walker BL, Cang Z, Ren H, Bourgain-Chang E, Nie Q. (2022). Deciphering tissue structure and function using spatial transcriptomics. Communications biology. PMID 35273328 · PMC8913632 · DOI 10.1038/s42003-022-03175-5

证据类型：REVIEW

主题：rna-seq、spatial-omics

被引次数（采集时）：99

原始记录：[Europe PMC](https://europepmc.org/article/MED/35273328)

来源许可：[CC-BY](https://creativecommons.org/licenses/by/)

作者摘要（按来源许可复用）

The rapid development of spatial transcriptomics (ST) techniques has allowed the measurement of transcriptional levels across many genes together with the spatial positions of cells. This has led to an explosion of interest in computational methods and techniques for harnessing both spatial and transcriptional information in analysis of ST datasets. The wide diversity of approaches in aim, methodology and technology for ST provides great challenges in dissecting cellular functions in spatial contexts. Here, we synthesize and review the key problems in analysis of ST data and methods that are currently applied, while also expanding on open questions and areas of future development.

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