Attention-based deep clustering method for scRNA-seq cell type identification
Fig 6
a. UMAP visualization of the clustering results on the BRCA datasets. b. Comparison of cell distribution between the predicted clusters and the ground truth cell lines. In the heat map, each row represents a class of cells from the same cell line, and each column represents a class of cells from the same predicted cluster. There was generally a one-to-one correspondence between cell lines and predicted clusters for ideal clustering results. c. Expression dot plot of identified DEGs in different cell lines. Based on the predicted cell labels, DEGs of all clusters were calculated by the Wilcoxon test (cluster 15 only contains 30 cells, so it was excluded). Top 1 DEGs of predicted clusters were selected as the potential marker genes. d. The pot plot was drawn to visualize the expression in each cell line and the most of cell lines can be distinguished obtained DEGs. BCAS3 was specifically expressed in cluster 18, i.e. MCF7 and KPL1. e. The UMAP visualization of the sub-clustering results on the cluster 18 by AttentionAE-sc, which was consist of these two cell lines.