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Fig. 5 | BMC Genomics

Fig. 5

From: A machine learning one-class logistic regression model to predict stemness for single cell transcriptomics and spatial omics

Fig. 5

Spatial analysis of stemness model A) Each spot from the section placed on Visium barcoded array is represented with i) a cluster projection ii) stemness score pathology classification for each spot of the Visium sample and distribution plots of stemness score across classified regions. B Cluster projection, stemness score, cell type prediction for each segmented cell’s centroid location and distribution plot of stemness score per annotated cell types of Xenium sample. C Cluster projection, stemness score, cell type annotation for each segmented cell’s centroid location and distribution plot of stemness score per annotated cell types of the MERSCOPE sample. D Cell type annotation, stemness score for each segmented cell’s centroid and distribution plot of stemness score per annotated cell type of the PhenoCycler sample. E Cell type annotation, stemness score for each segmented cell’s centroid and distribution plot of stemness score per annotated cell type of the CosMX sample

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