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Table 3 Unknown cell-type clustering performance of the different models analyzed for the LPGO experiments (P = 4). Although our pathway-based models are nearly ten times smaller (sparse), the performance is very close to the PPI-based NN. The mean of 20 splits was reported

From: Integrating pathway knowledge with deep neural networks to reduce the dimensionality in single-cell RNA-seq data

Architecture Number of nodes
(2nd hidden layer)
Homogeneity Completeness V-measure ARI AMI Fowlkes-Mallows Average
Dense 0.801 0.799 0.798 0.725 0.786 0.814 0.787
Dense with pathways 0.804 0.797 0.798 0.718 0.786 0.811 0.786
Dense with PPI 0.811 0.804 0.805 0.728 0.794 0.817 0.793
Dense with PPI and GRN 0.820 0.808 0.812 0.746 0.802 0.827 0.802
Signaling pathways 0.797 0.788 0.790 0.716 0.778 0.809 0.780
Signaling pathways 100 0.775 0.803 0.786 0.729 0.774 0.820 0.781