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Fig. 5 | Genome Biology

Fig. 5

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

Fig. 5

siVAE analysis yields insight into the underlying gene co-expression network structure of a cell population. a Scatterplot showing the correlation between ground truth degree centrality and predicted degree centrality based on either siVAE estimates or by computing node degree when a network is inferred using the MRNET or CLR algorithms. Each point represents a gene. b Average ground truth degree centrality of the top 50 genes ranked by predicted degree centrality across different methods. Higher average ground truth degree centrality indicates better concordance between the ground truth and predictions. c Bar plot indicating the prediction accuracy (% of variance explained) of the neighborhood gene sets when predicting each query gene, averaged over the 152 query genes with the highest predicted degree centrality in the fetal liver atlas dataset. Blue bars denote methods based on dimensionality reduction, while orange bars denote methods based on explicit gene regulatory network inference. d Heatmap indicating the pairwise Jaccard index (overlap) between neighborhood genes identified by pairs of methods. e Heatmap indicating the mean pairwise correlation in expression between neighborhood gene sets identified by pairs of methods

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