Dataset Information

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

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.

SUBMITTER: Laubscher E

PROVIDER: S-EPMC10508757 | biostudies-literature | 2024 Feb

REPOSITORIES: biostudies-literature

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

Laubscher Emily E Wang Xuefei Julie XJ Razin Nitzan N Dougherty Tom T Xu Rosalind J RJ Ombelets Lincoln L Pao Edward E Graf William W Moffitt Jeffrey R JR Yue Yisong Y Van Valen David D

bioRxiv : the preprint server for biology 20240205

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 transcript ...[more]

PMID: 37732188

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Dataset Information

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

Publications

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

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