Fig. 5
From: Machine learning unveils key Redox signatures for enhanced breast Cancer therapy
Single-cell analysis of cellular heterogeneity and AIARS level. (A) UMAP visualization showing various clusters within a dataset, each color representing a different cluster, suggesting distinct subpopulations based on gene expression or cellular phenotypes. (B) UMAP plot color-coded to represent different cell types within the sample. (C) Violin plots for specific marker genes across different cell types, showing the distribution of expression levels, which can indicate the relative abundance or activity of these cells. (D) Bar chart comparing the proportion of each cell type between normal and tumor samples. (E) UMAP density plot indicating the expression of the AIARS across different cell populations, with warmer colors representing higher expression levels. (F) Violin plot displaying the distribution of AIARS across various cell types. (G) Heatmap generated by CopyKAT depicting the inferred copy number variations across a range of genes (rows) and individual cells or samples (columns), with the color intensity reflecting the degree of aneuploidy or copy number alterations. (H) Violin plot contrasting the AIARS score between diploid and aneuploid cells within the epithelial cell population, indicating significant differences between these two genomic states