Interpretable Deep Embeddings for Single-cell RNA-seq Clustering Analysis via Gene Attention

This work presents a ZINB model-based denoising autoencoder that offers interpretable deep embeddings through a gene attention mechanism for single-cell RNA-seq clustering. Our method performs a dimensionality reduction into a latent space that embeds semantic information from gene expression inputs...