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Super-resolved spatial transcriptomics by deep data fusion. Nature biotechnology Bergenstrahle, L., He, B., Bergenstrahle, J., Abalo, X., Mirzazadeh, R., Thrane, K., Ji, A. L., Andersson, A., Larsson, L., Stakenborg, N., Boeckxstaens, G., Khavari, P., Zou, J., Lundeberg, J., Maaskola, J. 2021

Abstract

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.

View details for DOI 10.1038/s41587-021-01075-3

View details for PubMedID 34845373