A variational autoencoder trained with priors from canonical pathways increases the interpretability of transcriptome data
Fig 2
Reconstruction performances using correlation coefficients between input and output transcriptomes.
A-E: The clustered pair-wise correlation heatmaps of the selected input and their reconstructed output for A: simpleAE, B: simpleVAE, C: priorVAE, D: beta-simpleVAE, E: and beta-priorVAE. Selected input samples and their corresponding reconstruction output are enumerated as 1–20. ‘_Train’ represents the input train sample and ‘_Recon’ represents the reconstructed output. F: The average correlation between the input and its corresponding reconstruction output.