Fig. 2

Relationship between features in low-dimensional latent space by deep autoencoder and representative network metrics in the PIN. The X-axis is the latent space dimension and the Y-axis is Spearman’s correlation coefficient between a given low-dimensional feature and a given network metric (see Supplementary Figure 1 for the original data). The gray background dimensions (58, 86, 88, and 89) indicate almost no correlation to the representative network metrics. Several dimensions without the box (e.g., dimension 6 and 7) are n.a. because the encoded numerical values for all genes are zero