Attention-based deep clustering method for scRNA-seq cell type identification
Fig 5
Hyperparameters search and the ablation experiment.
a. Comparison of different methods for cell connectivity calculations. When compared to the UMAP method, the ’gauss’ method demonstrated superior performance. b. Comparison of different settings for the number of attention heads. c. Comparison of different settings for the resolution parameter in the Leiden algorithm. d. Comparison of different settings for the number of highly variable genes. e. Model ablation experiment of AttentionAE-sc in 8 scRNA-seq datasets. Four conditions were tested, including the absence of the information fusion block (wo attn), the absence of the ZINB loss function (wo zinb), the absence of residual connections (wo res), and the absence of GAE (wo gnn).