1. Smoother: a unified and modular framework for incorporating structural dependency in spatial omics data.
- Author
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Su J, Reynier JB, Fu X, Zhong G, Jiang J, Escalante RS, Wang Y, Aparicio L, Izar B, Knowles DA, and Rabadan R
- Subjects
- Humans, Male, Tumor Microenvironment, Fibroblasts, Prostate
- Abstract
Spatial omics technologies can help identify spatially organized biological processes, but existing computational approaches often overlook structural dependencies in the data. Here, we introduce Smoother, a unified framework that integrates positional information into non-spatial models via modular priors and losses. In simulated and real datasets, Smoother enables accurate data imputation, cell-type deconvolution, and dimensionality reduction with remarkable efficiency. In colorectal cancer, Smoother-guided deconvolution reveals plasma cell and fibroblast subtype localizations linked to tumor microenvironment restructuring. Additionally, joint modeling of spatial and single-cell human prostate data with Smoother allows for spatial mapping of reference populations with significantly reduced ambiguity., (© 2023. The Author(s).)
- Published
- 2023
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