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Scalable spatial transcriptomics through computational array reconstruction
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Acknowledgements
We thank D. Sun, R. Raichur and S. Alakwe for assistance with tissue handling and library preparation; D. Cable for the initial computational implementation of the idea; and K. Cao, J. Zhang, M. Dai, X. Ye and P. Yadollahpour for discussion on the computational algorithm. We thank L. Gaffney for helping with schematics and illustrations. This work was supported by the National Institutes of Health (grant R01HG010647 to F.C. and E.Z.M.) and a subaward from NHGRI TDCC (U24HG011735 to F.C. and E. Z. M.). F.C. also acknowledges support from the Searle Scholars Award, the Burroughs Wellcome Fund CASI award and the Merkin Institute. This research was supported by the New York Stem Cell Foundation. F.C. is a New York Stem Cell Foundation – Robertson Investigator.
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Competing interests
F.C. is an academic founder of Curio Biosciences and Doppler Biosciences and scientific advisor for Amber Bio. F.C.’s interests were reviewed and managed by the Broad Institute in accordance with their conflict-of-interest policies. C.H., M.B. and F.C. are listed as inventors on a patent application related to the work. E.Z.M. is an academic founder of Curio Biosciences. The remaining authors declare no competing interests.
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Nature Biotechnology thanks Song Chen and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.
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Extended data
Extended Data Fig. 1 Simulation of diffusion and reconstruction with UMAP.
a, Simulated locations of capture beads and diffusible beads in a 3 mm circle. b, Simulated diffusion pattern of a capture bead on its associated diffusible beads, colored by simulated UMI counts. The distribution plots on the top and right represents the diffusion distribution on the x and y axis respectively. c, Simulated locations of capture beads, colored by a two dimensional color gradient depending on the locations. d, UMAP reconstructed locations of capture beads, colored the same as in c. e, Absolute error of capture beads plotted in ground truth locations. f, Displacement vectors of capture beads. Each arrow starts from the capture bead’s ground truth location and ends at the reconstruction location. g, Histogram plot of capture beads’ absolute error.
Extended Data Fig. 2 Slide-seq reconstruction metrics.
a, Absolute error of capture beads plotted in ground truth locations. b, Displacement vectors of capture beads. Each arrow starts from the capture bead’s ground truth location and ends at the reconstruction location. c, Histogram plot of capture beads’ absolute errors. d, Spatial location of capture beads in ground truth, colored by decomposed cell types. e, Relative RMS error of measurement lengths as a function of measurement length. Data shown in Fig. 1f (blue) and two biological replicates (orange and green) are presented. Solid lines represent average values across beads and shaded areas represent one standard deviation. f, CA1 width measured in ground truth and reconstruction (N = 3 biological replicates). Data shown in Fig. 1f (blue) and two biological replicates (orange and green) are shown. Gray lines showed the mean width of each group. g, Neighborhood enrichment analysis between cell-type pairs in reconstruction (left) and ground truth (right). The enrichment scores are plotted in the same color scale, higher scores represent more enriched in the neighborhoods. h, Barcode matching between Slide-seq library and in situ sequencing barcode list or reconstruction barcode list. Bead barcodes with >20 UMI counts were matched with hamming distance ≤1. Blue rectangle represents total barcodes from in situ sequencing and dark blue represents barcodes matched with Slide-seq library barcodes (shown as green rectangle). Yellow rectangle represents total barcodes from reconstruction and dark yellow represents barcodes matched with Slide-seq library barcodes. i, Violin plot of UMI count per bead with the same Slide-seq library matched to reconstruction results and in situ sequencing results. Scale bars: 500 µm.
Extended Data Fig. 3 Slide-tags Reconstruction metric.
a, Absolute error of capture beads plotted in ground truth locations. b, Displacement vectors of capture beads. Each arrow starts from the capture bead’s ground truth location and ends at the reconstruction location. c, Histogram plot of capture bead locations’ absolute errors. d, Spatial representation of reconstruction error on each nucleus. e, Displacement vectors of located nuclei. Each arrow starts from the nuclei’s ground truth location and ends at the reconstruction location. f, Histogram plot of nuclei locations’ absolute errors. f, RMS error of measurement lengths between bead pairs as a function of measurement length. Solid lines represent average values, and shaded areas represent one standard deviation.
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Hu, C., Borji, M., Marrero, G.J. et al. Scalable spatial transcriptomics through computational array reconstruction.
Nat Biotechnol (2025). https://doi.org/10.1038/s41587-025-02612-0
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DOI: https://doi.org/10.1038/s41587-025-02612-0
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