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Accurate single-molecule spot detection for image-based spatial transcriptomics with weakly supervised deep learning
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DOI：10.1016/j.cels.2024.04.006.png)
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摘要
En 中文
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.
Keyword:
GENE-EXPRESSION
LOCALIZATION
TISSUE
期刊
IF:
7.7
论文数:
1.4K
被引数:
1.0W
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