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Museum of spatial transcriptomics

Moses, Lambda and Pachter, Lior (2022) Museum of spatial transcriptomics. Nature Methods, 19 (5). pp. 534-546. ISSN 1548-7091. doi:10.1038/s41592-022-01409-2.

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The function of many biological systems, such as embryos, liver lobules, intestinal villi, and tumors, depends on the spatial organization of their cells. In the past decade, high-throughput technologies have been developed to quantify gene expression in space, and computational methods have been developed that leverage spatial gene expression data to identify genes with spatial patterns and to delineate neighborhoods within tissues. To comprehensively document spatial gene expression technologies and data-analysis methods, we present a curated review of literature on spatial transcriptomics dating back to 1987, along with a thorough analysis of trends in the field, such as usage of experimental techniques, species, tissues studied, and computational approaches used. Our Review places current methods in a historical context, and we derive insights about the field that can guide current research strategies. A companion supplement offers a more detailed look at the technologies and methods analyzed:

Item Type:Article
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URLURL TypeDescription ReadCube access Paper ItemCode ItemDatabase ItemCode Correction ReadCube access - Publisher Correction
Moses, Lambda0000-0002-7092-9427
Pachter, Lior0000-0002-9164-6231
Additional Information:© 2022 Nature Publishing Group. Received 28 June 2021; Accepted 26 January 2022; Published 10 March 2022. This work was supported by a grant from the National Institute of Mental Health (NIMH), National Institute of Health (NIH), of the U.S. Department of Health & Human Services (number U19MH114830, L.P.). We thank the following people for providing feedback for earlier versions of this paper and the supplement: D. Furth from the Cold Spring Harbor Laboratories, L. Cai from the California Institute of Technology, and G. Victora from the Rockefeller University. Data availability: The database of spatial transcriptomics literature can be accessed at The version used as of writing is in the metadata.xlsx file in the frozen DOI version of the GitHub repository to reproduce the figures in this paper and render the supplementary website: Code availability: All code used to generate figures in this paper and render the supplementary website is in the GitHub repository: The frozen DOI version of the repository as of final submission of this paper is on Zenodo: Contributions: L.P. suggested the project. L.M. curated the database, performed the analyses of the metadata, and wrote the manuscript and the supplement, which have been proofread and edited by L.P. The authors declare no competing interests. Peer review information: Nature Methods thanks Sten Linnarsson, Quan Nguyen and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Lei Tang was the primary editor on this article and managed its editorial process and peer review in collaboration with the rest of the editorial team.
Errata:Moses, L., Pachter, L. Publisher Correction: Museum of spatial transcriptomics. Nat Methods (2022).
Funding AgencyGrant Number
Subject Keywords:Fluorescence in situ hybridization; RNA sequencing; Software
Issue or Number:5
Record Number:CaltechAUTHORS:20210513-122736659
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Official Citation:Moses, L., Pachter, L. Museum of spatial transcriptomics. Nat Methods 19, 534–546 (2022).
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:109117
Deposited By: Tony Diaz
Deposited On:13 May 2021 19:45
Last Modified:12 Oct 2022 15:01

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