Accurate single-molecule spot detection for image-based spatial transcriptomics with weakly supervised deep learning

doi:10.1016/j.cels.2024.04.006

Accurate single-molecule spot detection for image-based spatial transcriptomics with weakly supervised deep learning

2024-05-01

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DOI：10.1016/j.cels.2024.04.006

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Image -based spatial transcriptomics methods enable transcriptome-scale gene expression measurements with spatial information but require complex, manually tuned analysis pipelines. We present Polaris, an analysis pipeline for image -based spatial transcriptomics that combines deep -learning models for cell segmentation and spot detection with a probabilistic gene decoder to quantify single -cell gene expression accurately. Polaris offers a unifying, turnkey solution for analyzing spatial transcriptomics data from multiplexed error -robust FISH (MERFISH), sequential fluorescence in situ hybridization (seqFISH), or in situ RNA sequencing (ISS) experiments. Polaris is available through the DeepCell software library (https:// github.com/vanvalenlab/deepcell-spots) and https://www.deepcell.org.

Keywords:

GENE-EXPRESSION

LOCALIZATION

TISSUE

Accurate single-molecule spot detection for image-based spatial transcriptomics with weakly supervised deep learning

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