Research Paper Volume 12, Issue 18 pp 18297—18321

Glioblastoma cell differentiation trajectory predicts the immunotherapy response and overall survival of patients


Figure 2. Identification of 13 cell clusters with diverse annotations revealing high cellular heterogeneity in GBM tumors based on single-cell RNA-seq data. (A) After quality control of the 2,343 cells from the tumor cores of 4 human GBM samples, 2,149 cells were included in the analysis. (B) The numbers of detected genes were significantly related to the sequencing depth, with a Pearson’s correlation coefficient of 0.61. (C) The variance diagram shows 19,752 corresponding genes throughout all cells from GBMs. The red dots represent highly variable genes, and the black dots represent nonvariable genes. The top 10 most variable genes are marked in the plot. (D) PCA did not demonstrate clear separations of cells in GBMs. (E) PCA identified the 20 PCs with an estimated P value < 0.05. (F) The tSNE algorithm was applied for dimensionality reduction with the 20 PCs, and 13 cell clusters were successfully classified. (G) The differential analysis identified 8,025 marker genes. The top 20 marker genes of each cell cluster are displayed in the heatmap. A total of 96 genes are listed beside of the heatmap after omitting the same top marker genes among clusters. The colors from purple to yellow indicate the gene expression levels from low to high.