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Article

MAPLE: A Hybrid Framework for Multi-Sample Spatial Transcriptomics Data

2022-03-02

Abstract excerpt

High throughput spatial transcriptomics (HST) technologies provide unprecedented opportunity to identify spatially resolved cell sub-populations in tissue samples. However, existing methods preclude joint analysis of multiple HST samples, do not allow for differential abundance analysis (DAA), and ignore uncertainty quantification. To address this, we developed MAPLE: a hybrid deep learning and Bayesian modeling f...

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Literature Corpus work
fb44da8f-df63-5997-8156-f15299daa42d
DOI
10.1101/2022.02.28.482296
Open publication

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MAPLE: A Hybrid Framework for Multi-Sample Spatial Transcriptomics DataDOI 10.1101/2022.02.28.482296
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