Fig. 6

Quality control, filtering, and principal component analysis of scRNA-seq data. A Quality control was performed on 2012 cells from three BNST patient tissue samples. The three scatter plots show the number of nFeature_RNA, nCount_RNA, and percent. Mt in each cell. B Correlation between nCount and percent.mt (left plot), and correlation between nCount and nFeature (right plot). C Highly variable genes in the samples were selected through variance analysis (red dots represent highly variable genes, black dots represent unchanged genes). D P-values of PCA analysis results for 15 PCs. E Performance of cells from different sample sources in PCA principal component analysis (each dot represents a cell, and different colors represent different samples). F-G Heatmaps of feature genes and their expression levels based on the first two PCs of PCA analysis