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Slide-seq data

JZ Jiaqiang Zhu
SS Shiquan Sun
XZ Xiang Zhou
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Slide-seq is a technology which enables transcriptome-wide measurements with 10-micron spatial resolution by transferring RNA from tissue sections onto a surface covered in DNA-barcoded beads with known positions and inferring the locations of RNA using a sequencing-by-ligation strategy. We obtained the Slide-seq dataset collected on the mouse cerebellum from Broad Institute’s single-cell repository (https://singlecell.broadinstitute.org/single_cell/) with ID SCP354. We used the file “Puck_180430_6” which contains 18,671 genes measured on 25,551 beads with known spatial location information. The bead size is approaching the size of mammalian cells (10 microns), though each bead may overlap with multiple cells. After filtering out mitochondrial genes and genes that are not expressed on any bead, we analyzed a final set of 17,729 genes on 25,551 beads. The data is highly sparse with 99.46% entries being 0 (Additional file 1: Table S1).

Copyright and License information: The Author(s) ©2021
Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

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