Super-resolved spatial transcriptomics by deep data fusion

Ludvig Bergenstråhle, Bryan He, Joseph Bergenstråhle, Xesús Abalo, Reza Mirzazadeh, Kim Thrane, Andrew L. Ji, Alma Andersson, Ludvig Larsson, Nathalie Stakenborg, Guy Boeckxstaens, Paul Khavari, James Zou, Joakim Lundeberg, Jonas Maaskola

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. The low resolution of spatial transcriptomics is substantially improved by including histology images.

External IDs:doi:10.1038/s41587-021-01075-3