Abstract
AbstractRecent 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.
Funder
American Association for Cancer Research
U.S. Department of Health & Human Services | NIH | National Cancer Institute
Virginia and D.K. Ludwig Fund for Cancer Research
Publisher
Springer Science and Business Media LLC
Subject
Biomedical Engineering,Molecular Medicine,Applied Microbiology and Biotechnology,Bioengineering,Biotechnology
Cited by
57 articles.
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