Fig. 5
From: CMOT: Cross-Modality Optimal Transport for multimodal inference
Cross-modality inference between gene expression and chromatin accessibility can distinguish cancer types. A Cell-wise Pearson correlation (y-axis) of inferred and measured gene expression by different methods (x-axis): CMOT (p = 25%, 50%, 75%, 100%), Seurat, MOFA + (Additional File 1: Tables S22-S25). B Silhouette score (x-axis) across measured and inferred gene expressions (x-axis), and measured chromatin peaks (Additional File 1: Table S26). C PCA of inferred gene expression. D Gene-wise correlation between the inferred and measured expression, comparing CMOT (y-axis) with MOFA + and Seurat (x-axis). Dots: Genes; Numbers: Gene numbers above and below the dotted line. E Peak-wise AUROC, comparing CMOT (y-axis) with MOFA + and Seurat (x-axis). Dots: Peaks; Numbers: Peak numbers above and below the dotted line. P-values are calculated by a one-sided Wilcoxon rank-sum test