Table 1.
Summary of TCGA projects and associated cancer-type-specific pathways from MSigDB.
Fig 1.
Cancer-type-specific pathways.
Procedure to identify lists of preselected, target, and positive-control pathways using TCGA-BRCA (breast cancer) as example. See S2 Table for full details.
Fig 2.
Significant TCGA-BRCA positive control pathways across different weight parameter choices.
(a) Gene-set permutation with p—value < 0.05. (b) Gene-set permutation with p—value < 0.01. (c) Phenotype permutation with p—value < 0.05. (d) Phenotype permutation with p—value < 0.01. GSEA enrichment statistics: classic (“cl”), weight parameter p = 1 (“p1”), weight parameter p = 1.5 (“p1.5”), and weight parameter p = 2 (“p2”).
Fig 3.
Significant TCGA-BRCA positive control pathways using gene-set (“gs”) and phenotype (“ph”) permutation approaches for different enrichment statistics.
The significance criterion was p—value < 0.05. (a) Classic (unweighted). (b) Weight parameter p = 1. (c) Weight parameter p = 1.5. (d) Weight parameter p = 2.
Fig 4.
ROC curves for different GSEA and ORA approaches using 72 TCGA-BRCA positive control pathways and 1000 randomized negative controls.
(a) Gene-set permutation GSEA. (b) Phenotype permutation GSEA. (c) Signed ORA. (d) Unsigned ORA. GSEA approaches used different enrichment statistics, as indicated. ORA approaches used Bonferroni and Benjamini-Hochberg (B-H) adjusted q-values as different inclusion criteria to select differentially expressed genes, as indicated.
Fig 5.
AUC across TCGA projects for different GSEA and ORA approaches using cancer-type-specific positive control pathways and 1000 randomized negative controls.
(a) Gene-set permutation GSEA. (b) Phenotype permutation GSEA. (c) Signed ORA. (d) Unsigned ORA. GSEA approaches used different enrichment statistics, as indicated. ORA approaches used Bonferroni and Benjamini-Hochberg (B-H) adjusted q-values as different inclusion criteria to select differentially expressed genes, as indicated.
Fig 6.
Pathway-level enrichment evidence scores for thyroid cancer and hepatocellular carcinoma cohorts.
(a) Comparison between significant target pathways in REBC-THYR vs TCGA-THCA. (b) Contingency table of grouped EES intervals in REBC-THYR vs TCGA-THCA (Fisher’s exact test p—value = 2.5 × 10−6). (c) Comparison between significant target pathways in MO-HCC vs TCGA-LIHC. (d) Contingency table of grouped EES intervals in MO-HCC vs TCGA-LIHC (Fisher’s exact test p—value = 4.4 × 10−15). Distance to the diagonal is represented with increasingly darker shades of blue.
Fig 7.
Gene-level enrichment evidence scores for thyroid cancer cohorts.
(a) Comparison between EES leading-edge genes in REBC-THYR vs TCGA-THCA for genes in LUI_THYROID_CANCER_CLUSTER_1, previously identified as a high-consensus tumor-enriched pathway in thyroid cancer. (b) Contingency table of grouped EES intervals for the same case as in panel (a) (Fisher’s exact test p—value = 4.6 × 10−8). (c) Network representation showing seven core thyroid cancer pathways and high-consensus leading-edge genes (|EES| ≥ 3 in at least one of the cohorts). Only genes connected to two or more pathways are shown.