Fig. 5From: A machine learning one-class logistic regression model to predict stemness for single cell transcriptomics and spatial omicsSpatial 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 sampleBack to article page