High-resolution alignment of single-cell and spatial transcriptomes with CytoSPACE

Recent studies have emphasized the importance of single-cell spatial biology, yet available assays for spatial transcriptomics have limited gene recovery or low spatial resolution. Here we introduce CytoSPACE, an optimization method for mapping individual cells from a single-cell RNA sequencing atla...

Full description

Saved in:
Bibliographic Details
Published inNature biotechnology Vol. 41; no. 11; pp. 1543 - 1548
Main Authors Vahid, Milad R, Brown, Erin L, Steen, Chloé B, Zhang, Wubing, Jeon, Hyun Soo, Kang, Minji, Gentles, Andrew J, Newman, Aaron M
Format Journal Article
LanguageEnglish
Published United States Nature Publishing Group 01.11.2023
Nature Publishing Group US
Subjects
Biotechnology
Brief Communication
Cancer
Cartography
Cells
Communication
Datasets
Gene expression
Gene Expression Profiling
Gene mapping
Gene sequencing
Immune Tolerance
Integer programming
Medical research
Noise tolerance
Optimization
Ribonucleic acid
RNA
Single-Cell Analysis
Spatial discrimination
Spatial resolution
Transcriptome - genetics
Transcriptomes
Transcriptomics
Online AccessGet full text

Cover

More Information
Summary:Recent studies have emphasized the importance of single-cell spatial biology, yet available assays for spatial transcriptomics have limited gene recovery or low spatial resolution. Here we introduce CytoSPACE, an optimization method for mapping individual cells from a single-cell RNA sequencing atlas to spatial expression profiles. Across diverse platforms and tissue types, we show that CytoSPACE outperforms previous methods with respect to noise tolerance and accuracy, enabling tissue cartography at single-cell resolution.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
ISSN:1087-0156
1546-1696
1546-1696
DOI:10.1038/s41587-023-01697-9