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

被引：52

作者：

Vahid, Milad R. ^{[1
,2
]}

Brown, Erin L. ^{[1
,2
]}

Steen, Chloe B. ^{[2
,3
,4
]}

Zhang, Wubing ^{[1
,2
]}

Jeon, Hyun Soo ^{[5
]}

Kang, Minji ^{[1
,2
]}

Gentles, Andrew J. ^{[2
,6
,7
,8
]}

Newman, Aaron M. ^{[1
,2
,6
]}

机构：

[1] Stanford Univ, Inst Stem Cell Biol & Regenerat Med, Stanford, CA 94305 USA

[2] Stanford Univ, Dept Biomed Data Sci, Stanford, CA 94305 USA

[3] Oslo Univ Hosp, Inst Canc Res, Dept Canc Immunol, Oslo, Norway

[4] Oslo Univ Hosp, Dept Med Genet, Oslo, Norway

[5] Stanford Univ, Dept Comp Sci, Stanford, CA USA

[6] Stanford Univ, Stanford Canc Inst, Stanford, CA 94305 USA

[7] Stanford Univ, Dept Pathol, Stanford, CA USA

[8] Stanford Univ, Stanford Ctr Biomed Informat Res, Dept Med, Stanford, CA USA

来源：

NATURE BIOTECHNOLOGY | 2023年 / 41卷 / 11期

关键词：

EXPRESSION; DIVERSITY; IDENTIFICATION; LANDSCAPE; ALGORITHM; LINEAGE;

D O I：

10.1038/s41587-023-01697-9

中图分类号：

Q81 [生物工程学（生物技术）]; Q93 [微生物学];

学科分类号：

071005 ; 0836 ; 090102 ; 100705 ;

摘要：

CytoSPACE maps individual cells from a reference single-cell RNA sequencing atlas to spatial transcriptomics data. 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.

引用

页码：1543 / +

页数：33

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