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bioRxiv · 10.1101/2023.09.03.556122

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

Laubscher, E.·Wang, X.·Razin, N.·Dougherty, T.·Xu, R.·Ombelets, L.·Pao, E.·Moffitt, J.·Yue, Y.·Van Valen, D. A.
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Abstract

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 MERFSIH, seqFISH, or ISS experiments. Polaris is available through the DeepCell software library (https://github.com/vanvalenlab/deepcell-spots) and https://www.deepcell.org.

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Laubscher, E., Wang, X., Razin, N., Dougherty, T., Xu, R., Ombelets, L., Pao, E., Moffitt, J., Yue, Y., Van Valen, D. A.. 2023-09-05. Accurate single-molecule spot detection for image-based spatial transcriptomics with weakly supervised deep learning. https://doi.org/10.1101/2023.09.03.556122

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