High-resolution alignment of single-cell and spatial transcriptomes with CytoSPACE
Milad R. Vahid, Erin L. Brown, Chloé B. Steen, Wubing Zhang, Hyun Soo Jeon, Minji Kang, Andrew J. Gentles, Aaron M. Newman
Abstract
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.
Topics & Concepts
TranscriptomeComputational biologySingle-cell analysisBiologySpatial analysisImage resolutionCellComputer scienceGene expressionGeneGeneticsArtificial intelligenceRemote sensingGeographySingle-cell and spatial transcriptomicsImmune cells in cancer