Table 4.
NN classifiera | Input Type |
Encoder Layer 1d |
Encoder Layer 2 |
Encoder Layer 3 |
Encoder Layer 4 |
Accuracy of 10-fold cross validation |
---|---|---|---|---|---|---|
Superset | Genesb | 2334 | 200 | 88.79% | ||
Gene set | Genes | 2334 | 87.69% | |||
2-layer fc | Genes | 2334 | 200 | 47.86% | ||
2-layer fc | Genes | 2000 | 500 | 37.98% | ||
4-layer fc | Genes | 2000 | 200 | 100 | 50 | 46.06% |
2-layer fc | PCc | 400 | 100 | 87.57% | ||
4-layer fc | PC | 200 | 200 | 100 | 25 | 87.57% |
a2-, 4-layer fc: 2- or 4- layer fully connected AE
bGenes input is the 15,183 genes of TCGA BRCA RNA-seq data
cPC input is the top 500 principal components of PCA analysis
dThe encoder layer 1 of superset and gene set classifier is the gene set layer (not a fully connected layer)