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single-to-spatial-mapping

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Map scRNA-seq atlases onto spatial transcriptomics slides using omicverse's Single2Spatial workflow for deep-forest training, spot-level assessment, and marker visualisation.

When to use

• converting single-cell references into spatially resolved profiles
• training deep-forest models on scRNA-seq and spatial data
• reconstructing spot-level proportions
• visualising marker expression
• assessing spot-level outputs
• plotting cell-type maps
• loading pretrained weights
• exporting spatial AnnData results

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