Research Paper Volume 16, Issue 7 pp 6455—6477
Machine learning for identifying tumor stemness genes and developing prognostic model in gastric cancer
Figure 1. ssGSEA algorithm was used to identify the differential genes of tumor stemness in TCGA samples. (A) Distribution map of high and low score groups of TCGA samples. (B) tSNE was used to analyze the distribution between high and low stemness score groups. (C) Volcano plot of differentially expressed genes between high and low stemness score groups.