Table 2 Molecular subtypes classification performances using LFs learned via supervised VAE/MMD-VAE.
From: Integrated multi-omics analysis of ovarian cancer using variational autoencoders
Method | Omics_data | Accuracy | Precision | Recall | f1 score |
|---|---|---|---|---|---|
V-VAE | CNV | 58.3 ± 0.3 | 0.63 ± 0.01 | 0.58 ± 0.03 | 0.579 ± 0.03 |
MMD-VAE | CNV | 54.3 ± 0.31 | 0.58 ± 0.02 | 0.54 ± 0.02 | 0.53 ± 0.03 |
V-VAE | mRNA | 95.7 ± .5 | 0.95 ± 0.008 | 0.95 ± 0.05 | 0.95 ± 0.006 |
MMD-VAE | mRNA | 93.8 ± .97 | 0.93 ± 0.006 | 0.93 ± 0.005 | 0.93 ± 0.006 |
V-VAE | Methylation | 72.3 ± .8 | 0.73 ± 0.02 | 0.72 ± 0.009 | 0.71 ± 0.006 |
MMD-VAE | Methylation | 75.2 ± .9 | 0.75 ± 0.019 | 0.75 ± 0.018 | 0.75 ± 0.015 |
V-VAE | CNV_mRNA | 93.7 ± .27 | 0.93 ± 0.01 | 0.93 ± 0.008 | 0.93 ± 0.007 |
MMD-VAE | CNV_mRNA | 93.7 ± .37 | 0.94 ± 0.006 | 0.93 ± 0.007 | 0.93 ± 0.007 |
V-VAE | mRNA_methylation | 87.1 ± 1.1 | 0.87 ± 0.009 | 0.87 ± 0.008 | 0.87 ± 0.005 |
MMD-VAE | mRNA_methylation | 93.2 ± .97 | 0.93 ± 0.02 | 0.93 ± 0.008 | 0.93 ± 0.005 |
V-VAE | CNV_mRNA_methylation | 89.4 ± .6 | 0.89 ± 0.02 | 0.89 ± 0.006 | 0.89 ± 0.004 |
MMD-VAE | CNV_mRNA_methylation | 95.5 ± .37 | 0.95 ± 0.02 | 0.95 ± 0.008 | 0.95 ± 0.009 |
