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SC2Spa: a deep learning based approach to map transcriptome to spatial origins at cellular resolution

Authors: Linbu Liao; Esha Madan; António M. Palma; Hyobin Kim; Amit Kumar; Praveen Bhoopathi; Robert Winn; +5 Authors

SC2Spa: a deep learning based approach to map transcriptome to spatial origins at cellular resolution

Abstract

{"references": ["Karaiskos N, Wahle P, Alles J, Boltengagen A, Ayoub S, Kipar C, Kocks C, Rajewsky N, Zinzen RP: The Drosophila embryo at single-cell transcriptome resolution. Science 2017, 358:194-199.", "Stickels RR, Murray E, Kumar P, Li J, Marshall JL, Di Bella DJ, Arlotta P, Macosko EZ, Chen F: Highly sensitive spatial transcriptomics at near-cellular resolution with Slide-seqV2. Nature Biotechnology 2020.", "St\u00e5hl PL, Salm\u00e9n F, Vickovic S, Lundmark A, Navarro JF, Magnusson J, Giacomello S, Asp M, Westholm JO, Huss M, et al: Visualization and analysis of gene expression in tissue sections by spatial transcriptomics. Science 2016, 353:78-82.", "Chen A, Liao S, Cheng MN, Ma KL, Wu L, Lai YW, Qiu XJ, Yang J, Xu JS, Hao SJ, et al: Spatiotemporal transcriptomic atlas of mouse organogenesis using DNA nanoball-patterned arrays. Cell 2022, 185:1777-+.", "Kleshchevnikov V, Shmatko A, Dann E, Aivazidis A, King HW, Li T, Elmentaite R, Lomakin A, Kedlian V, Gayoso A, et al: Cell2location maps fine-grained cell types in spatial transcriptomics. Nat Biotechnol 2022, 40:661-671.", "Saunders A, Macosko EZ, Wysoker A, Goldman M, Krienen FM, de Rivera H, Bien E, Baum M, Bortolin L, Wang SY, et al: Molecular Diversity and Specializations among the Cells of the Adult Mouse Brain. Cell 2018, 174:1015-+.", "Li R, Ferdinand JR, Loudon KW, Bowyer GS, Laidlaw S, Muyas F, Mamanova L, Neves JB, Bolt L, Fasouli ES, et al: Mapping single-cell transcriptomes in the intra-tumoral and associated territories of kidney cancer. Cancer Cell 2022, 40:1583-1599 e1510.", "Janesick A, Shelansky R, Gottscho AD, Wagner F, Rouault M, Beliakoff G, Oliveira MFd, Kohlway A, Abousoud J, Morrison CA, et al: High resolution mapping of the breast cancer tumor microenvironment using integrated single cell, spatial and in situ analysis of FFPE tissue. bioRxiv 2022:2022.2010.2006.510405."]}

All data and analysis involved in the manuscript "SC2Spa: a deep learning based approach to map transcriptome to spatial origins at cellular resolution"

Keywords

Spatial transcriptomics, scRNA-seq, Spatial inference

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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impulse
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