Super-resolved spatial transcriptomics by deep data fusion

• 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. 

Ämnesord

NATURVETENSKAP  -- Fysik -- Subatomär fysik (hsv//swe)

NATURAL SCIENCES  -- Physical Sciences -- Subatomic Physics (hsv//eng)

NATURVETENSKAP  -- Biologi -- Genetik (hsv//swe)

NATURAL SCIENCES  -- Biological Sciences -- Genetics (hsv//eng)

MEDICIN OCH HÄLSOVETENSKAP  -- Klinisk medicin -- Cancer och onkologi (hsv//swe)

MEDICAL AND HEALTH SCIENCES  -- Clinical Medicine -- Cancer and Oncology (hsv//eng)

NATURVETENSKAP  -- Biologi (hsv//swe)

NATURAL SCIENCES  -- Biological Sciences (hsv//eng)

Nyckelord

Gene expression

'current

Gene Expression Data

Generative model

High resolution

Histological images

Image data

Spatial resolution

Tissue sections

Transcriptomes

Transcriptomics

Data fusion

transcriptome

Publikations- och innehållstyp

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