Table 4 Pathway enrichment of gene sets under different models(THCA dataset)
From: Identifying driver pathways based on a parameter-free model and a partheno-genetic algorithm
K | MWSM | \(r_{pe}(\%)\) |
|---|---|---|
2 | BRAF NRAS | 100.0 |
3 | BRAF NRAS HRAS | 100.0 |
4 | BRAF NRAS HRAS PTEN | 100.0 |
5 | BRAF NRAS HRAS GLUD1 CNTLN | 60.0 |
6 | BRAF NRAS HRAS LIPJ CNTLN ZCCHC2 | 50.0 |
7 | BRAF NRAS HRAS SLC25A45 CNTLN DOCK6 PRKG1 | 42.9 |
8 | BRAF NRAS HRAS GLUD1 CNTLN DOCK6 SLC1A6 SLC25A45 | 37.5 |
K | SMCM | \(r_{pe}(\%)\) |
|---|---|---|
2 | BRAF NRAS | 100.0 |
3 | BRAF NRAS HRAS | 100.0 |
4 | BRAF NRAS HRAS MRPS16 | 75.0 |
5 | BRAF NRAS HRAS PTEN CNTLN | 80.0 |
6 | BRAF NRAS HRAS TDRD7 DOK5 IFIT3 | 50.0 |
7 | BRAF NRAS HRAS EIF3L SLC25A45 RUFY2 ABHD16A | 42.9 |
8 | BRAF NRAS HRAS TG ZCCHC2 ZNF385D PRKG1 SEC14L2 | 37.5 |
K | SMCMN | \(r_{pe}(\%)\) |
|---|---|---|
2 | BRAF NRAS | 100.0 |
3 | BRAF NRAS HRAS | 100.0 |
4 | BRAF NRAS HRAS RAF1 | 100.0 |
5 | BRAF NRAS HRAS PTEN PIK3CG | 80.0 |
6 | BRAF NRAS HRAS PIK3CA KRAS RAF1 | 100.0 |
7 | BRAF NRAS HRAS PIK3CA PTEN PIK3R5 MUC16 | 71.4 |
8 | BRAF NRAS HRAS PIK3CA PTEN KRAS TP53 DIS3 | 75.0 |