Deep learning and alignment of spatially resolved single-cell transcriptomes with Tangram
Name
s41592-021-01264-7.pdf
Description
Published version
Size
16.68 MB
Format
Adobe PDF
Checksum (MD5)
d8e717b414991889b19928b614c27600
Author(s)
Biancalani, Tommaso
Scalia, Gabriele
Buffoni, Lorenzo
Avasthi, Raghav
Lu, Ziqing
Sanger, Aman
Tokcan, Neriman
Vanderburg, Charles R
Segerstolpe, Åsa
Zhang, Meng
Date Issued
2021
Journal
Nature Methods
Publisher
Springer Science and Business Media LLC
Citation
Biancalani, Tommaso, Scalia, Gabriele, Buffoni, Lorenzo, Avasthi, Raghav, Lu, Ziqing et al. 2021. "Deep learning and alignment of spatially resolved single-cell transcriptomes with Tangram." Nature Methods, 18 (11).
Version
Final published version
Abstract
AbstractCharting an organs’ biological atlas requires us to spatially resolve the entire single-cell transcriptome, and to relate such cellular features to the anatomical scale. Single-cell and single-nucleus RNA-seq (sc/snRNA-seq) can profile cells comprehensively, but lose spatial information. Spatial transcriptomics allows for spatial measurements, but at lower resolution and with limited sensitivity. Targeted in situ technologies solve both issues, but are limited in gene throughput. To overcome these limitations we present Tangram, a method that aligns sc/snRNA-seq data to various forms of spatial data collected from the same region, including MERFISH, STARmap, smFISH, Spatial Transcriptomics (Visium) and histological images. Tangram can map any type of sc/snRNA-seq data, including multimodal data such as those from SHARE-seq, which we used to reveal spatial patterns of chromatin accessibility. We demonstrate Tangram on healthy mouse brain tissue, by reconstructing a genome-wide anatomically integrated spatial map at single-cell resolution of the visual and somatomotor areas.
MIT Department
Massachusetts Institute of Technology. Department of Biology
Terms of Use
Creative Commons Attribution 4.0 International license
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DOI of Published Version
https://doi.org/10.1038/S41592-021-01264-7
