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Fig. 4 | Genome Biology

Fig. 4

From: siVAE: interpretable deep generative models for single-cell transcriptomes

Fig. 4

Co-expressed genes tend to co-localize in the feature embedding space. a The gene co-expression network used to simulate single-cell expression data for this experiment. The network consists of five tightly correlated groups of 50 genes each, along with 50 isolated, disconnected genes. Nodes represent genes, edges represent strong correlations. b Scatterplot of the feature embeddings inferred by siVAE trained on the dataset simulated from the network in a. Each point represents a gene, colored and labeled by the community it belongs to in a. c Scatterplot of the cell-embedding space inferred by siVAE trained on the fetal liver atlas dataset. Each point represents a cell and is colored based on its pre-defined cell type. d Scatterplot of feature embeddings inferred by siVAE trained on the fetal liver atlas dataset. Each point represents a marker gene and is colored based on its prior known association to a cell type

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