SpatialFeatures
Bioc removedEntropy-based subcellular and supercellular features for molecule-resolved spatial omics datasets
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Description
This package uses molecule-level information to extract new cell-level features as an alternative to simply calculating gene counts. By using four categories, sub-sector, super-sector, super-sector and super-concentric segmentations of cells, SpatialFeatures then uses entropy as a metric to arrive at a cell-by-gene level feature. Overall, this means that we can extract more nuanced information from molecule-resolved spatial gene expression for further downstream analysis with SingleCellExperiment.
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People
- Shila Ghazanfar author maintainer contributor
- Guan Gui contributor
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