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

Research output: Contribution to journalArticlepeer-review

12 Scopus citations

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.

Original languageEnglish
Pages (from-to)476-479
Number of pages4
JournalNature Biotechnology
Volume40
Issue number4
DOIs
StatePublished - Apr 2022
Externally publishedYes

Fingerprint

Dive into the research topics of 'Super-resolved spatial transcriptomics by deep data fusion'. Together they form a unique fingerprint.

Cite this