Attention-based deep clustering method for scRNA-seq cell type identification
Fig 3
Evaluations of cell embedding.
a. Clustering performance of AttentionAE-sc and four methods based on community detection algorithm using Silhouette scores as metrics. Each box contains the results of 16 datasets (run 5 times by different random seeds). In the box diagram, the dotted line represents the median score, and the upper or lower solid lines represent the maximum or minimum score. b. Comparison of UMAP visualization from different methods on the dataset Romanov. AttentionAE-sc learned more clustering-friendly embedding for single-cell clustering.