Super-resolved spatial transcriptomics by deep data fusion

doi:10.1038/s41587-021-01075-3

Super-resolved spatial transcriptomics by deep data fusion

2021-11-29

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DOI：10.1038/s41587-021-01075-3

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Abstract

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The low resolution of spatial transcriptomics is substantially improved by including histology images. Current methods for spatial transcriptomics are limited by low spatial resolution. Here we introduce a method that integrates spatial gene expression data with histological image data from the same tissue section to infer higher-resolution expression maps. Using a deep generative model, our method characterizes the transcriptome of micrometer-scale anatomical features and can predict spatial gene expression from histology images alone.

Keywords:

CELL RNA-SEQ

SINGLE-CELL

GENE-EXPRESSION

TISSUE

VISUALIZATION

Super-resolved spatial transcriptomics by deep data fusion

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