Deep learning and alignment of spatially resolved single-cell transcriptomes with Tangram.
Journal
Nature methods
ISSN: 1548-7105
Titre abrégé: Nat Methods
Pays: United States
ID NLM: 101215604
Informations de publication
Date de publication:
11 2021
11 2021
Historique:
received:
13
08
2020
accepted:
11
08
2021
pubmed:
30
10
2021
medline:
29
12
2021
entrez:
29
10
2021
Statut:
ppublish
Résumé
Charting 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.
Identifiants
pubmed: 34711971
doi: 10.1038/s41592-021-01264-7
pii: 10.1038/s41592-021-01264-7
pmc: PMC8566243
mid: NIHMS1732416
doi:
Substances chimiques
Chromatin
0
Types de publication
Journal Article
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
1352-1362Subventions
Organisme : NIH HHS
ID : OT2 OD026673
Pays : United States
Organisme : NIMH NIH HHS
ID : U19 MH114821
Pays : United States
Organisme : NIMH NIH HHS
ID : U19 MH114830
Pays : United States
Organisme : Howard Hughes Medical Institute
Pays : United States
Commentaires et corrections
Type : CommentIn
Informations de copyright
© 2021. The Author(s).
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