Research Paper Volume 15, Issue 14 pp 6848—6864
The integration of machine learning and multi-omics analysis provides a powerful approach to screen aging-related genes and predict prognosis and immunotherapy efficacy in hepatocellular carcinoma
Figure 3. Single-cell analysis reveals the expression of differential genes in different cell types. (A) Using the tSNE algorithm to dimensionalize the samples into 12 clusters. (B) Heat map clearly showing the major differentially expressed genes in different clusters. (C) The Seurat package annotates different clusters with a total of 4 classes of cells. (D) The bubble diagram shows the expression of difference genes in different cells. (E) Visualization of 13 differential genes by single-cell sequencing.