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. 2022 Apr;40(4):476-479.
doi: 10.1038/s41587-021-01075-3. Epub 2021 Nov 29.

Super-resolved spatial transcriptomics by deep data fusion

Ludvig Bergenstråhle  1 , Bryan He  2 , Joseph Bergenstråhle  1 , Xesús Abalo  1 , Reza Mirzazadeh  1 , Kim Thrane  1 , Andrew L Ji  3 , Alma Andersson  1 , Ludvig Larsson  1 , Nathalie Stakenborg  4 , Guy Boeckxstaens  4 , Paul Khavari  3 , James Zou  2 , Joakim Lundeberg  5 , Jonas Maaskola  1   6
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Super-resolved spatial transcriptomics by deep data fusion

Ludvig Bergenstråhle et al. Nat Biotechnol. 2022 Apr.

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.

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