GSEA Class2: Canonical Pathways enriched in each subtypes of mRNAseq_cNMF in BLCA-TP
Bladder Urothelial Carcinoma (Primary solid tumor)
02 April 2015  |  analyses__2015_04_02
Maintainer Information
Citation Information
Maintained by Juok Cho (Broad Institute)
Cite as Broad Institute TCGA Genome Data Analysis Center (2015): GSEA Class2: Canonical Pathways enriched in each subtypes of mRNAseq_cNMF in BLCA-TP. Broad Institute of MIT and Harvard. doi:10.7908/C16M35T3
Overview
Introduction

This pipeline performs Gene Set Enrichment Analysis (GSEA) using The Broad Institute GSEA tool with MSigDB - Class2: Canonical Pathways gene sets. For a given phenotype subtype, it shows what pathways are significantly enriched in each subtype by comparing gene expression profiles between subtypes. Here, the phenotype is mRNAseq_cNMF subtypes in BLCA-TP. This pipeline has the following features:

  1. For each subtype, calculates enrichment scores (ES) using signal to noise (S2N) that checks similarity between subtypes in expression level then calculates p values through permutation test.

  2. Lists pathways significantly enriched in each phenotype subtype and their enrichment scores (ES).

  3. Lists top 20 core genes enriched in each significant gene set and their enrichment scores (ES).

  4. Checks if the top core genes are up-regulated or down-regulated.

  5. Checks if the top core genes are high expressed or low expressed.

  6. Checks if the top core genes are significantly differently expressed genes.

Summary

Table 1.  Get Full Table basic data info

basic data info
Number of Gene Sets: 192
Number of samples: 408
Original number of Gene Sets: 404
Maximum gene set size: 388

Table 2.  Get Full Table pheno data info

phenotype info
pheno.type: 1 - 3 :[ clus1 ] 116
pheno.type: 2 - 3 :[ clus2 ] 182
pheno.type: 3 - 3 :[ clus3 ] 110

For the expression subtypes of 18215 genes in 409 samples, GSEA found enriched gene sets in each cluster using 408 gene sets in MSigDB canonical pathways. Top enriched gene sets are listed as below.

  • clus1

    • Top enriched gene sets are BIOCARTA NO1 PATHWAY, BIOCARTA ALK PATHWAY, BIOCARTA AT1R PATHWAY, BIOCARTA BCR PATHWAY, BIOCARTA BIOPEPTIDES PATHWAY, BIOCARTA HDAC PATHWAY, BIOCARTA EGF PATHWAY, BIOCARTA ERK PATHWAY, BIOCARTA FCER1 PATHWAY, BIOCARTA FMLP PATHWAY

    • And common core enriched genes are PIK3CG, AKT3, IGF1, PIK3CD, PIK3R5, FGFR1, LEF1, PDGFC, PDGFRA, PDGFRB

  • clus2

    • Top enriched gene sets are KEGG GLYCOLYSIS GLUCONEOGENESIS, KEGG PENTOSE AND GLUCURONATE INTERCONVERSIONS, KEGG FATTY ACID METABOLISM, KEGG STEROID HORMONE BIOSYNTHESIS, KEGG VALINE LEUCINE AND ISOLEUCINE DEGRADATION, KEGG TYROSINE METABOLISM, KEGG GLUTATHIONE METABOLISM, KEGG STARCH AND SUCROSE METABOLISM, KEGG GLYCEROPHOSPHOLIPID METABOLISM, KEGG ETHER LIPID METABOLISM

    • And common core enriched genes are UGT1A1, UGT1A10, UGT1A3, UGT1A4, UGT1A5, UGT1A6, UGT1A8, UGT1A9, UGT2A3, UGT2B10

  • clus3

    • Top enriched gene sets are BIOCARTA G1 PATHWAY, BIOCARTA EGF PATHWAY, BIOCARTA FAS PATHWAY, BIOCARTA RACCYCD PATHWAY, BIOCARTA MAPK PATHWAY, BIOCARTA P38MAPK PATHWAY, BIOCARTA IL1R PATHWAY, BIOCARTA TNFR1 PATHWAY, KEGG PYRIMIDINE METABOLISM, KEGG AMINOACYL TRNA BIOSYNTHESIS

    • And common core enriched genes are CDK6, CDKN1A, TFDP1, CDK7, PCNA, POLD1, POLD2, POLE2, POLE3, CHUK

Results
Subtype clus1 enriched pathways

Table 3.  Get Full Table This table shows top 10 pathways which are significantly enriched in cluster clus1. It displays only significant gene sets satisfying nom.p.val.threshold (-1), fwer.p.val.threshold (-1) , fdr.q.val.threshold (0.25) and the default table is sorted by Normalized Enrichment Score (NES). Further details on NES statistics, please visit The Broad GSEA website.

GeneSet(GS) Size(#genes) genes.ES.table ES NES NOM.p.val FDR.q.val FWER.p.val Tag.. Gene.. Signal FDR..median. glob.p.val
BIOCARTA NO1 PATHWAY 27 genes.ES.table 0.52 1.3 0.17 0.19 0.97 0.41 0.2 0.33 0.16 0
BIOCARTA ALK PATHWAY 33 genes.ES.table 0.48 1.4 0.09 0.16 0.96 0.33 0.22 0.26 0.13 0
BIOCARTA AT1R PATHWAY 32 genes.ES.table 0.39 1.4 0.13 0.18 0.97 0.5 0.38 0.31 0.15 0
BIOCARTA BCR PATHWAY 33 genes.ES.table 0.61 1.7 0.01 0.067 0.49 0.3 0.2 0.24 0 0.003
BIOCARTA BIOPEPTIDES PATHWAY 39 genes.ES.table 0.45 1.5 0.051 0.11 0.86 0.56 0.38 0.35 0.079 0
BIOCARTA HDAC PATHWAY 26 genes.ES.table 0.6 1.7 0.01 0.065 0.47 0.5 0.3 0.35 0 0.003
BIOCARTA EGF PATHWAY 30 genes.ES.table 0.42 1.3 0.23 0.23 0.99 0.5 0.39 0.31 0.2 0
BIOCARTA ERK PATHWAY 27 genes.ES.table 0.43 1.4 0.12 0.16 0.95 0.11 0.074 0.1 0.13 0
BIOCARTA FCER1 PATHWAY 37 genes.ES.table 0.59 1.7 0.018 0.068 0.57 0.27 0.2 0.22 0.034 0.002
BIOCARTA FMLP PATHWAY 35 genes.ES.table 0.59 1.9 0 0.098 0.17 0.23 0.14 0.2 0 0.022
genes ES table in pathway: BIOCARTA NO1 PATHWAY

Table S1.  Get Full Table This table shows a Running Enrichment Score (RES) of each gene in this pathway, that is, the enrichment score at this point in the ranked list of genes. All genes are ranked by Signal-to-Noise (S2N), a measure of similarity as default and are used to obtain ES matrix of all genes. In this way, GSEA tool uses expression pattern of not only overlapped genes but also not-overlapped genes to produce ES matrix.

Rank GENE SYMBOL DESC LIST.LOC S2N RES CORE_ENRICHMENT
1 IGF1 IGF1 IGF1 4 0.88 0.077 YES
2 FGFR1 FGFR1 FGFR1 249 0.64 0.12 YES
3 PIK3R5 PIK3R5 PIK3R5 353 0.61 0.17 YES
4 PDGFRA PDGFRA PDGFRA 691 0.53 0.19 YES
5 AKT3 AKT3 AKT3 775 0.51 0.23 YES
6 CREB3L1 CREB3L1 CREB3L1 837 0.5 0.27 YES
7 PDGFC PDGFC PDGFC 862 0.5 0.32 YES
8 LEF1 LEF1 LEF1 1081 0.46 0.34 YES
9 PDGFRB PDGFRB PDGFRB 1207 0.44 0.38 YES
10 PIK3CG PIK3CG PIK3CG 1254 0.44 0.41 YES
11 INSRR INSRR INSRR 1284 0.43 0.45 YES
12 CREB5 CREB5 CREB5 1367 0.42 0.48 YES
13 PIK3CD PIK3CD PIK3CD 1387 0.42 0.51 YES
14 TCF7L1 TCF7L1 TCF7L1 1770 0.37 0.52 YES
15 BCL2 BCL2 BCL2 2173 0.31 0.53 YES
16 TCF7 TCF7 TCF7 2429 0.28 0.54 YES
17 PDGFB PDGFB PDGFB 2464 0.28 0.56 YES
18 PDGFD PDGFD PDGFD 2879 0.24 0.56 NO
19 CREB3L3 CREB3L3 CREB3L3 4556 0.12 0.48 NO
20 NKX3-1 NKX3-1 NKX3-1 4583 0.12 0.49 NO
21 PDGFA PDGFA PDGFA 4589 0.12 0.5 NO
22 CREB3 CREB3 CREB3 5046 0.095 0.48 NO
23 E2F1 E2F1 E2F1 5449 0.079 0.46 NO
24 CREB3L2 CREB3L2 CREB3L2 5463 0.079 0.47 NO
25 MAPK3 MAPK3 MAPK3 5782 0.068 0.46 NO
26 E2F2 E2F2 E2F2 5902 0.064 0.46 NO
27 GRB2 GRB2 GRB2 6063 0.06 0.46 NO
28 FOXO1 FOXO1 FOXO1 6166 0.057 0.45 NO
29 ARAF ARAF ARAF 6619 0.047 0.43 NO
30 CDKN1B CDKN1B CDKN1B 6754 0.044 0.43 NO
31 PTEN PTEN PTEN 6762 0.044 0.43 NO
32 BAD BAD BAD 7053 0.038 0.42 NO
33 TP53 TP53 TP53 7102 0.037 0.42 NO
34 CTNNB1 CTNNB1 CTNNB1 7197 0.035 0.42 NO
35 HSP90B1 HSP90B1 HSP90B1 7562 0.029 0.4 NO
36 IKBKG IKBKG IKBKG 7640 0.028 0.4 NO
37 EGF EGF EGF 7701 0.026 0.4 NO
38 PIK3R1 PIK3R1 PIK3R1 7820 0.024 0.39 NO
39 CDK2 CDK2 CDK2 7831 0.024 0.4 NO
40 ATF4 ATF4 ATF4 8126 0.02 0.38 NO
41 CHUK CHUK CHUK 8167 0.019 0.38 NO
42 NFKB1 NFKB1 NFKB1 8209 0.018 0.38 NO
43 MAP2K2 MAP2K2 MAP2K2 8259 0.018 0.38 NO
44 CCNE1 CCNE1 CCNE1 8536 0.014 0.36 NO
45 PIK3R3 PIK3R3 PIK3R3 8553 0.014 0.36 NO
46 AKT2 AKT2 AKT2 8686 0.012 0.36 NO
47 PIK3CA PIK3CA PIK3CA 8689 0.012 0.36 NO
48 MAP2K1 MAP2K1 MAP2K1 9023 0.0074 0.34 NO
49 AR AR AR 9054 0.007 0.34 NO
50 PIK3CB PIK3CB PIK3CB 9188 0.0054 0.33 NO
51 RELA RELA RELA 9209 0.0052 0.33 NO
52 MAPK1 MAPK1 MAPK1 9367 0.0035 0.32 NO
53 NFKBIA NFKBIA NFKBIA 9532 0.0019 0.32 NO
54 KLK3 KLK3 KLK3 9970 -0.003 0.29 NO
55 NRAS NRAS NRAS 10018 -0.0035 0.29 NO
56 AKT1 AKT1 AKT1 10046 -0.0038 0.29 NO
57 CREBBP CREBBP CREBBP 10060 -0.004 0.29 NO
58 RAF1 RAF1 RAF1 10280 -0.0068 0.28 NO
59 CREB1 CREB1 CREB1 10647 -0.011 0.26 NO
60 MTOR MTOR MTOR 10706 -0.012 0.26 NO
61 IGF1R IGF1R IGF1R 11044 -0.016 0.24 NO
62 HSP90AA1 HSP90AA1 HSP90AA1 11170 -0.017 0.23 NO
63 SOS2 SOS2 SOS2 11197 -0.018 0.23 NO
64 CCNE2 CCNE2 CCNE2 11323 -0.019 0.23 NO
65 SOS1 SOS1 SOS1 12020 -0.027 0.19 NO
66 RB1 RB1 RB1 12198 -0.029 0.18 NO
67 KRAS KRAS KRAS 12296 -0.03 0.18 NO
68 GSK3B GSK3B GSK3B 12321 -0.031 0.18 NO
69 CDKN1A CDKN1A CDKN1A 12459 -0.032 0.18 NO
70 PDPK1 PDPK1 PDPK1 13384 -0.045 0.13 NO
71 MDM2 MDM2 MDM2 13524 -0.047 0.13 NO
72 EGFR EGFR EGFR 13569 -0.048 0.13 NO
73 TCF7L2 TCF7L2 TCF7L2 13803 -0.051 0.12 NO
74 EP300 EP300 EP300 13957 -0.053 0.12 NO
75 PIK3R2 PIK3R2 PIK3R2 14062 -0.055 0.12 NO
76 CASP9 CASP9 CASP9 14345 -0.061 0.11 NO
77 FGFR2 FGFR2 FGFR2 14470 -0.064 0.1 NO
78 CREB3L4 CREB3L4 CREB3L4 14908 -0.072 0.086 NO
79 IKBKB IKBKB IKBKB 14924 -0.073 0.092 NO
80 CCND1 CCND1 CCND1 15241 -0.08 0.082 NO
81 E2F3 E2F3 E2F3 15555 -0.09 0.072 NO
82 HRAS HRAS HRAS 15575 -0.09 0.079 NO
83 ERBB2 ERBB2 ERBB2 16020 -0.11 0.064 NO
84 GSTP1 GSTP1 GSTP1 16147 -0.11 0.067 NO
85 TGFA TGFA TGFA 16792 -0.15 0.044 NO
86 BRAF BRAF BRAF 17100 -0.18 0.043 NO
87 SRD5A2 SRD5A2 SRD5A2 17343 -0.2 0.047 NO

Figure S1.  Get High-res Image This plot shows mRNAseq_cNMF expression data heatmap (on the left) a RunningEnrichmentScore(RES) plot (on the top right) and a Signal2Noise(S2N) plot (on the bottom right) of genes in the pathway: BIOCARTA NO1 PATHWAY.

Figure S2.  Get High-res Image For the top 5 core enriched genes in the pathway: BIOCARTA NO1 PATHWAY, this volcano plot shows how much they are up/down-regulated and significant. The significance was calculated by empirical bayesian fit

genes ES table in pathway: BIOCARTA ALK PATHWAY

Table S2.  Get Full Table This table shows a Running Enrichment Score (RES) of each gene in this pathway, that is, the enrichment score at this point in the ranked list of genes. All genes are ranked by Signal-to-Noise (S2N), a measure of similarity as default and are used to obtain ES matrix of all genes. In this way, GSEA tool uses expression pattern of not only overlapped genes but also not-overlapped genes to produce ES matrix.

Rank GENE SYMBOL DESC LIST.LOC S2N RES CORE_ENRICHMENT
1 RUNX1T1 RUNX1T1 RUNX1T1 107 0.71 0.085 YES
2 PIK3R5 PIK3R5 PIK3R5 353 0.61 0.15 YES
3 SPI1 SPI1 SPI1 570 0.55 0.21 YES
4 AKT3 AKT3 AKT3 775 0.51 0.26 YES
5 FLT3 FLT3 FLT3 855 0.5 0.32 YES
6 LEF1 LEF1 LEF1 1081 0.46 0.37 YES
7 ZBTB16 ZBTB16 ZBTB16 1198 0.44 0.42 YES
8 PIK3CG PIK3CG PIK3CG 1254 0.44 0.47 YES
9 PIK3CD PIK3CD PIK3CD 1387 0.42 0.52 YES
10 TCF7L1 TCF7L1 TCF7L1 1770 0.37 0.55 YES
11 TCF7 TCF7 TCF7 2429 0.28 0.55 YES
12 PIM2 PIM2 PIM2 2515 0.27 0.58 YES
13 STAT5A STAT5A STAT5A 3869 0.16 0.52 NO
14 KIT KIT KIT 3976 0.15 0.54 NO
15 CCNA1 CCNA1 CCNA1 4945 0.099 0.5 NO
16 RARA RARA RARA 5561 0.076 0.47 NO
17 MAPK3 MAPK3 MAPK3 5782 0.068 0.47 NO
18 GRB2 GRB2 GRB2 6063 0.06 0.46 NO
19 STAT5B STAT5B STAT5B 6262 0.055 0.46 NO
20 ARAF ARAF ARAF 6619 0.047 0.44 NO
21 STAT3 STAT3 STAT3 6830 0.043 0.44 NO
22 BAD BAD BAD 7053 0.038 0.43 NO
23 RUNX1 RUNX1 RUNX1 7148 0.036 0.43 NO
24 PML PML PML 7627 0.028 0.41 NO
25 IKBKG IKBKG IKBKG 7640 0.028 0.41 NO
26 PIK3R1 PIK3R1 PIK3R1 7820 0.024 0.4 NO
27 CHUK CHUK CHUK 8167 0.019 0.39 NO
28 NFKB1 NFKB1 NFKB1 8209 0.018 0.39 NO
29 MYC MYC MYC 8243 0.018 0.39 NO
30 MAP2K2 MAP2K2 MAP2K2 8259 0.018 0.39 NO
31 PIK3R3 PIK3R3 PIK3R3 8553 0.014 0.37 NO
32 AKT2 AKT2 AKT2 8686 0.012 0.37 NO
33 PIK3CA PIK3CA PIK3CA 8689 0.012 0.37 NO
34 MAP2K1 MAP2K1 MAP2K1 9023 0.0074 0.35 NO
35 PIK3CB PIK3CB PIK3CB 9188 0.0054 0.34 NO
36 RELA RELA RELA 9209 0.0052 0.34 NO
37 MAPK1 MAPK1 MAPK1 9367 0.0035 0.34 NO
38 NRAS NRAS NRAS 10018 -0.0035 0.3 NO
39 AKT1 AKT1 AKT1 10046 -0.0038 0.3 NO
40 RAF1 RAF1 RAF1 10280 -0.0068 0.29 NO
41 MTOR MTOR MTOR 10706 -0.012 0.26 NO
42 SOS2 SOS2 SOS2 11197 -0.018 0.24 NO
43 RPS6KB2 RPS6KB2 RPS6KB2 11579 -0.022 0.22 NO
44 EIF4EBP1 EIF4EBP1 EIF4EBP1 11811 -0.025 0.21 NO
45 SOS1 SOS1 SOS1 12020 -0.027 0.2 NO
46 PIM1 PIM1 PIM1 12144 -0.028 0.2 NO
47 KRAS KRAS KRAS 12296 -0.03 0.2 NO
48 RPS6KB1 RPS6KB1 RPS6KB1 13625 -0.048 0.13 NO
49 TCF7L2 TCF7L2 TCF7L2 13803 -0.051 0.13 NO
50 PIK3R2 PIK3R2 PIK3R2 14062 -0.055 0.12 NO
51 IKBKB IKBKB IKBKB 14924 -0.073 0.082 NO
52 CCND1 CCND1 CCND1 15241 -0.08 0.075 NO
53 HRAS HRAS HRAS 15575 -0.09 0.068 NO
54 BRAF BRAF BRAF 17100 -0.18 0.0072 NO
55 JUP JUP JUP 17334 -0.2 0.02 NO
56 CEBPA CEBPA CEBPA 17464 -0.21 0.04 NO

Figure S3.  Get High-res Image This plot shows mRNAseq_cNMF expression data heatmap (on the left) a RunningEnrichmentScore(RES) plot (on the top right) and a Signal2Noise(S2N) plot (on the bottom right) of genes in the pathway: BIOCARTA ALK PATHWAY.

Figure S4.  Get High-res Image For the top 5 core enriched genes in the pathway: BIOCARTA ALK PATHWAY, this volcano plot shows how much they are up/down-regulated and significant. The significance was calculated by empirical bayesian fit

genes ES table in pathway: BIOCARTA AT1R PATHWAY

Table S3.  Get Full Table This table shows a Running Enrichment Score (RES) of each gene in this pathway, that is, the enrichment score at this point in the ranked list of genes. All genes are ranked by Signal-to-Noise (S2N), a measure of similarity as default and are used to obtain ES matrix of all genes. In this way, GSEA tool uses expression pattern of not only overlapped genes but also not-overlapped genes to produce ES matrix.

Rank GENE SYMBOL DESC LIST.LOC S2N RES CORE_ENRICHMENT
1 IGF1 IGF1 IGF1 4 0.88 0.066 YES
2 FGF7 FGF7 FGF7 37 0.77 0.12 YES
3 FGF2 FGF2 FGF2 161 0.67 0.17 YES
4 HGF HGF HGF 186 0.66 0.22 YES
5 FGFR1 FGFR1 FGFR1 249 0.64 0.26 YES
6 FGF14 FGF14 FGF14 328 0.61 0.3 YES
7 PIK3R5 PIK3R5 PIK3R5 353 0.61 0.35 YES
8 FGF1 FGF1 FGF1 580 0.55 0.38 YES
9 PDGFRA PDGFRA PDGFRA 691 0.53 0.41 YES
10 AKT3 AKT3 AKT3 775 0.51 0.44 YES
11 PDGFC PDGFC PDGFC 862 0.5 0.48 YES
12 MITF MITF MITF 1021 0.47 0.5 YES
13 FGF10 FGF10 FGF10 1125 0.46 0.53 YES
14 PDGFRB PDGFRB PDGFRB 1207 0.44 0.56 YES
15 PIK3CG PIK3CG PIK3CG 1254 0.44 0.59 YES
16 FGF18 FGF18 FGF18 1296 0.43 0.62 YES
17 PIK3CD PIK3CD PIK3CD 1387 0.42 0.65 YES
18 FGF13 FGF13 FGF13 1829 0.36 0.65 YES
19 FGF5 FGF5 FGF5 1848 0.36 0.68 YES
20 FGF9 FGF9 FGF9 2071 0.33 0.69 YES
21 PDGFB PDGFB PDGFB 2464 0.28 0.69 NO
22 PDGFD PDGFD PDGFD 2879 0.24 0.68 NO
23 CDK6 CDK6 CDK6 4112 0.14 0.62 NO
24 CDKN2A CDKN2A CDKN2A 4248 0.14 0.63 NO
25 PDGFA PDGFA PDGFA 4589 0.12 0.62 NO
26 MAPK3 MAPK3 MAPK3 5782 0.068 0.56 NO
27 E2F2 E2F2 E2F2 5902 0.064 0.56 NO
28 FGF22 FGF22 FGF22 6456 0.05 0.53 NO
29 ARAF ARAF ARAF 6619 0.047 0.52 NO
30 PTEN PTEN PTEN 6762 0.044 0.52 NO
31 BAD BAD BAD 7053 0.038 0.51 NO
32 TP53 TP53 TP53 7102 0.037 0.51 NO
33 CDK4 CDK4 CDK4 7258 0.034 0.5 NO
34 FGF8 FGF8 FGF8 7343 0.033 0.5 NO
35 MET MET MET 7535 0.029 0.49 NO
36 EGF EGF EGF 7701 0.026 0.48 NO
37 PIK3R1 PIK3R1 PIK3R1 7820 0.024 0.48 NO
38 MAP2K2 MAP2K2 MAP2K2 8259 0.018 0.46 NO
39 PIK3R3 PIK3R3 PIK3R3 8553 0.014 0.44 NO
40 AKT2 AKT2 AKT2 8686 0.012 0.43 NO
41 PIK3CA PIK3CA PIK3CA 8689 0.012 0.43 NO
42 MAP2K1 MAP2K1 MAP2K1 9023 0.0074 0.42 NO
43 PIK3CB PIK3CB PIK3CB 9188 0.0054 0.41 NO
44 MAPK1 MAPK1 MAPK1 9367 0.0035 0.4 NO
45 NRAS NRAS NRAS 10018 -0.0035 0.36 NO
46 AKT1 AKT1 AKT1 10046 -0.0038 0.36 NO
47 FGF19 FGF19 FGF19 10087 -0.0042 0.36 NO
48 RAF1 RAF1 RAF1 10280 -0.0068 0.35 NO
49 FGF12 FGF12 FGF12 10961 -0.015 0.31 NO
50 IGF1R IGF1R IGF1R 11044 -0.016 0.31 NO
51 RB1 RB1 RB1 12198 -0.029 0.25 NO
52 KRAS KRAS KRAS 12296 -0.03 0.24 NO
53 CDKN1A CDKN1A CDKN1A 12459 -0.032 0.24 NO
54 FGF17 FGF17 FGF17 13442 -0.046 0.19 NO
55 MDM2 MDM2 MDM2 13524 -0.047 0.19 NO
56 EGFR EGFR EGFR 13569 -0.048 0.19 NO
57 PIK3R2 PIK3R2 PIK3R2 14062 -0.055 0.16 NO
58 CCND1 CCND1 CCND1 15241 -0.08 0.11 NO
59 E2F3 E2F3 E2F3 15555 -0.09 0.096 NO
60 HRAS HRAS HRAS 15575 -0.09 0.1 NO
61 FGF11 FGF11 FGF11 16996 -0.17 0.036 NO
62 BRAF BRAF BRAF 17100 -0.18 0.044 NO
63 CDH1 CDH1 CDH1 17510 -0.22 0.038 NO

Figure S5.  Get High-res Image This plot shows mRNAseq_cNMF expression data heatmap (on the left) a RunningEnrichmentScore(RES) plot (on the top right) and a Signal2Noise(S2N) plot (on the bottom right) of genes in the pathway: BIOCARTA AT1R PATHWAY.

Figure S6.  Get High-res Image For the top 5 core enriched genes in the pathway: BIOCARTA AT1R PATHWAY, this volcano plot shows how much they are up/down-regulated and significant. The significance was calculated by empirical bayesian fit

genes ES table in pathway: BIOCARTA BCR PATHWAY

Table S4.  Get Full Table This table shows a Running Enrichment Score (RES) of each gene in this pathway, that is, the enrichment score at this point in the ranked list of genes. All genes are ranked by Signal-to-Noise (S2N), a measure of similarity as default and are used to obtain ES matrix of all genes. In this way, GSEA tool uses expression pattern of not only overlapped genes but also not-overlapped genes to produce ES matrix.

Rank GENE SYMBOL DESC LIST.LOC S2N RES CORE_ENRICHMENT
1 IGF1 IGF1 IGF1 4 0.88 0.16 YES
2 PIK3R5 PIK3R5 PIK3R5 353 0.61 0.25 YES
3 AKT3 AKT3 AKT3 775 0.51 0.31 YES
4 PIK3CG PIK3CG PIK3CG 1254 0.44 0.36 YES
5 PIK3CD PIK3CD PIK3CD 1387 0.42 0.43 YES
6 VEGFC VEGFC VEGFC 2409 0.28 0.43 YES
7 PRKAA2 PRKAA2 PRKAA2 2710 0.25 0.46 YES
8 RPS6KA2 RPS6KA2 RPS6KA2 3562 0.18 0.44 YES
9 VEGFB VEGFB VEGFB 3781 0.17 0.46 YES
10 FIGF FIGF FIGF 4016 0.15 0.47 YES
11 ULK2 ULK2 ULK2 4838 0.1 0.44 NO
12 MAPK3 MAPK3 MAPK3 5782 0.068 0.41 NO
13 EIF4E2 EIF4E2 EIF4E2 6733 0.044 0.36 NO
14 RHEB RHEB RHEB 7311 0.033 0.34 NO
15 HIF1A HIF1A HIF1A 7589 0.029 0.32 NO
16 PIK3R1 PIK3R1 PIK3R1 7820 0.024 0.32 NO
17 CAB39 CAB39 CAB39 8406 0.016 0.29 NO
18 PIK3R3 PIK3R3 PIK3R3 8553 0.014 0.28 NO
19 AKT2 AKT2 AKT2 8686 0.012 0.28 NO
20 PIK3CA PIK3CA PIK3CA 8689 0.012 0.28 NO
21 RPTOR RPTOR RPTOR 8696 0.012 0.28 NO
22 PIK3CB PIK3CB PIK3CB 9188 0.0054 0.25 NO
23 MAPK1 MAPK1 MAPK1 9367 0.0035 0.24 NO
24 MLST8 MLST8 MLST8 9877 -0.002 0.22 NO
25 AKT1 AKT1 AKT1 10046 -0.0038 0.21 NO
26 RPS6KA3 RPS6KA3 RPS6KA3 10062 -0.004 0.21 NO
27 STRADA STRADA STRADA 10503 -0.0095 0.19 NO
28 EIF4B EIF4B EIF4B 10578 -0.01 0.18 NO
29 MTOR MTOR MTOR 10706 -0.012 0.18 NO
30 TSC2 TSC2 TSC2 10790 -0.013 0.18 NO
31 ULK1 ULK1 ULK1 10841 -0.014 0.18 NO
32 STK11 STK11 STK11 10987 -0.015 0.17 NO
33 DDIT4 DDIT4 DDIT4 11160 -0.017 0.16 NO
34 RPS6KB2 RPS6KB2 RPS6KB2 11579 -0.022 0.15 NO
35 EIF4EBP1 EIF4EBP1 EIF4EBP1 11811 -0.025 0.14 NO
36 TSC1 TSC1 TSC1 12363 -0.031 0.11 NO
37 PDPK1 PDPK1 PDPK1 13384 -0.045 0.064 NO
38 RPS6KB1 RPS6KB1 RPS6KB1 13625 -0.048 0.06 NO
39 EIF4E EIF4E EIF4E 13898 -0.052 0.054 NO
40 PIK3R2 PIK3R2 PIK3R2 14062 -0.055 0.055 NO
41 RPS6 RPS6 RPS6 14206 -0.058 0.058 NO
42 RPS6KA1 RPS6KA1 RPS6KA1 14514 -0.064 0.052 NO
43 PRKAA1 PRKAA1 PRKAA1 14529 -0.065 0.063 NO
44 RICTOR RICTOR RICTOR 14547 -0.065 0.074 NO
45 ULK3 ULK3 ULK3 14919 -0.073 0.066 NO
46 RPS6KA6 RPS6KA6 RPS6KA6 16129 -0.11 0.02 NO
47 CAB39L CAB39L CAB39L 16420 -0.13 0.026 NO
48 BRAF BRAF BRAF 17100 -0.18 0.021 NO
49 VEGFA VEGFA VEGFA 17530 -0.22 0.037 NO

Figure S7.  Get High-res Image This plot shows mRNAseq_cNMF expression data heatmap (on the left) a RunningEnrichmentScore(RES) plot (on the top right) and a Signal2Noise(S2N) plot (on the bottom right) of genes in the pathway: BIOCARTA BCR PATHWAY.

Figure S8.  Get High-res Image For the top 5 core enriched genes in the pathway: BIOCARTA BCR PATHWAY, this volcano plot shows how much they are up/down-regulated and significant. The significance was calculated by empirical bayesian fit

genes ES table in pathway: BIOCARTA BIOPEPTIDES PATHWAY

Table S5.  Get Full Table This table shows a Running Enrichment Score (RES) of each gene in this pathway, that is, the enrichment score at this point in the ranked list of genes. All genes are ranked by Signal-to-Noise (S2N), a measure of similarity as default and are used to obtain ES matrix of all genes. In this way, GSEA tool uses expression pattern of not only overlapped genes but also not-overlapped genes to produce ES matrix.

Rank GENE SYMBOL DESC LIST.LOC S2N RES CORE_ENRICHMENT
1 IGF1 IGF1 IGF1 4 0.88 0.11 YES
2 FGF2 FGF2 FGF2 161 0.67 0.18 YES
3 HAND2 HAND2 HAND2 303 0.62 0.25 YES
4 HAND1 HAND1 HAND1 571 0.55 0.31 YES
5 NFATC1 NFATC1 NFATC1 1043 0.47 0.34 YES
6 PIK3CG PIK3CG PIK3CG 1254 0.44 0.38 YES
7 CAMK1G CAMK1G CAMK1G 1377 0.42 0.43 YES
8 PRKAR2B PRKAR2B PRKAR2B 1959 0.34 0.44 YES
9 CAMK4 CAMK4 CAMK4 1981 0.34 0.48 YES
10 CAMK1 CAMK1 CAMK1 2299 0.3 0.5 YES
11 NFATC4 NFATC4 NFATC4 2389 0.29 0.53 YES
12 NFATC2 NFATC2 NFATC2 2457 0.28 0.56 YES
13 LIF LIF LIF 2467 0.28 0.6 YES
14 AGT AGT AGT 2569 0.27 0.62 YES
15 ACTA1 ACTA1 ACTA1 3401 0.2 0.6 YES
16 GATA4 GATA4 GATA4 3672 0.18 0.61 YES
17 PPP3CC PPP3CC PPP3CC 3721 0.17 0.63 YES
18 EDN1 EDN1 EDN1 3823 0.16 0.64 YES
19 NKX2-5 NKX2-5 NKX2-5 4777 0.11 0.6 NO
20 PRKAR2A PRKAR2A PRKAR2A 5121 0.091 0.59 NO
21 PPP3CB PPP3CB PPP3CB 5203 0.088 0.6 NO
22 CALM2 CALM2 CALM2 5414 0.08 0.6 NO
23 MAPK3 MAPK3 MAPK3 5782 0.068 0.59 NO
24 PRKACB PRKACB PRKACB 6671 0.046 0.54 NO
25 MAPK14 MAPK14 MAPK14 6794 0.043 0.54 NO
26 NFATC3 NFATC3 NFATC3 6862 0.042 0.54 NO
27 PPP3CA PPP3CA PPP3CA 6911 0.041 0.55 NO
28 CALM3 CALM3 CALM3 6917 0.041 0.55 NO
29 FKBP1A FKBP1A FKBP1A 7093 0.037 0.55 NO
30 CALR CALR CALR 7481 0.03 0.53 NO
31 CALM1 CALM1 CALM1 7534 0.03 0.53 NO
32 PIK3R1 PIK3R1 PIK3R1 7820 0.024 0.52 NO
33 PRKAR1A PRKAR1A PRKAR1A 8430 0.015 0.49 NO
34 PIK3CA PIK3CA PIK3CA 8689 0.012 0.47 NO
35 PRKAR1B PRKAR1B PRKAR1B 8843 0.0099 0.47 NO
36 MAP2K1 MAP2K1 MAP2K1 9023 0.0074 0.46 NO
37 MAPK1 MAPK1 MAPK1 9367 0.0035 0.44 NO
38 HBEGF HBEGF HBEGF 9502 0.0021 0.43 NO
39 AKT1 AKT1 AKT1 10046 -0.0038 0.4 NO
40 CREBBP CREBBP CREBBP 10060 -0.004 0.4 NO
41 CTF1 CTF1 CTF1 10162 -0.0053 0.4 NO
42 RAF1 RAF1 RAF1 10280 -0.0068 0.39 NO
43 MAPK8 MAPK8 MAPK8 11676 -0.023 0.32 NO
44 GSK3B GSK3B GSK3B 12321 -0.031 0.28 NO
45 F2 F2 F2 13010 -0.04 0.25 NO
46 RPS6KB1 RPS6KB1 RPS6KB1 13625 -0.048 0.22 NO
47 NPPA NPPA NPPA 14243 -0.059 0.2 NO
48 CSNK1A1 CSNK1A1 CSNK1A1 14779 -0.07 0.18 NO
49 HRAS HRAS HRAS 15575 -0.09 0.14 NO

Figure S9.  Get High-res Image This plot shows mRNAseq_cNMF expression data heatmap (on the left) a RunningEnrichmentScore(RES) plot (on the top right) and a Signal2Noise(S2N) plot (on the bottom right) of genes in the pathway: BIOCARTA BIOPEPTIDES PATHWAY.

Figure S10.  Get High-res Image For the top 5 core enriched genes in the pathway: BIOCARTA BIOPEPTIDES PATHWAY, this volcano plot shows how much they are up/down-regulated and significant. The significance was calculated by empirical bayesian fit

genes ES table in pathway: BIOCARTA HDAC PATHWAY

Table S6.  Get Full Table This table shows a Running Enrichment Score (RES) of each gene in this pathway, that is, the enrichment score at this point in the ranked list of genes. All genes are ranked by Signal-to-Noise (S2N), a measure of similarity as default and are used to obtain ES matrix of all genes. In this way, GSEA tool uses expression pattern of not only overlapped genes but also not-overlapped genes to produce ES matrix.

Rank GENE SYMBOL DESC LIST.LOC S2N RES CORE_ENRICHMENT
1 FPR1 FPR1 FPR1 141 0.68 0.14 YES
2 NCF1C NCF1C NCF1C 382 0.6 0.25 YES
3 NFATC1 NFATC1 NFATC1 1043 0.47 0.31 YES
4 NCF2 NCF2 NCF2 1154 0.45 0.4 YES
5 CAMK1G CAMK1G CAMK1G 1377 0.42 0.47 YES
6 CAMK1 CAMK1 CAMK1 2299 0.3 0.48 YES
7 NFATC4 NFATC4 NFATC4 2389 0.29 0.54 YES
8 NFATC2 NFATC2 NFATC2 2457 0.28 0.59 YES
9 PPP3CC PPP3CC PPP3CC 3721 0.17 0.56 NO
10 PPP3CB PPP3CB PPP3CB 5203 0.088 0.5 NO
11 CALM2 CALM2 CALM2 5414 0.08 0.5 NO
12 MAPK3 MAPK3 MAPK3 5782 0.068 0.5 NO
13 MAPK14 MAPK14 MAPK14 6794 0.043 0.45 NO
14 NFATC3 NFATC3 NFATC3 6862 0.042 0.46 NO
15 ELK1 ELK1 ELK1 6879 0.042 0.46 NO
16 PPP3CA PPP3CA PPP3CA 6911 0.041 0.47 NO
17 CALM3 CALM3 CALM3 6917 0.041 0.48 NO
18 CALM1 CALM1 CALM1 7534 0.03 0.45 NO
19 GNB1 GNB1 GNB1 7543 0.029 0.46 NO
20 NFKB1 NFKB1 NFKB1 8209 0.018 0.42 NO
21 MAP2K2 MAP2K2 MAP2K2 8259 0.018 0.42 NO
22 MAP2K3 MAP2K3 MAP2K3 8324 0.017 0.42 NO
23 MAP3K1 MAP3K1 MAP3K1 8370 0.016 0.42 NO
24 MAP2K1 MAP2K1 MAP2K1 9023 0.0074 0.39 NO
25 RELA RELA RELA 9209 0.0052 0.38 NO
26 MAPK1 MAPK1 MAPK1 9367 0.0035 0.37 NO
27 NFKBIA NFKBIA NFKBIA 9532 0.0019 0.36 NO
28 RAF1 RAF1 RAF1 10280 -0.0068 0.32 NO
29 RAC1 RAC1 RAC1 11993 -0.027 0.24 NO
30 PLCB1 PLCB1 PLCB1 12386 -0.032 0.22 NO
31 MAP2K6 MAP2K6 MAP2K6 12653 -0.035 0.21 NO
32 PIK3C2G PIK3C2G PIK3C2G 14757 -0.069 0.11 NO
33 PAK1 PAK1 PAK1 14825 -0.071 0.12 NO
34 HRAS HRAS HRAS 15575 -0.09 0.1 NO
35 GNGT1 GNGT1 GNGT1 17369 -0.2 0.046 NO

Figure S11.  Get High-res Image This plot shows mRNAseq_cNMF expression data heatmap (on the left) a RunningEnrichmentScore(RES) plot (on the top right) and a Signal2Noise(S2N) plot (on the bottom right) of genes in the pathway: BIOCARTA HDAC PATHWAY.

Figure S12.  Get High-res Image For the top 5 core enriched genes in the pathway: BIOCARTA HDAC PATHWAY, this volcano plot shows how much they are up/down-regulated and significant. The significance was calculated by empirical bayesian fit

genes ES table in pathway: BIOCARTA EGF PATHWAY

Table S7.  Get Full Table This table shows a Running Enrichment Score (RES) of each gene in this pathway, that is, the enrichment score at this point in the ranked list of genes. All genes are ranked by Signal-to-Noise (S2N), a measure of similarity as default and are used to obtain ES matrix of all genes. In this way, GSEA tool uses expression pattern of not only overlapped genes but also not-overlapped genes to produce ES matrix.

Rank GENE SYMBOL DESC LIST.LOC S2N RES CORE_ENRICHMENT
1 ENPP1 ENPP1 ENPP1 43 0.76 0.038 YES
2 PDE1A PDE1A PDE1A 103 0.71 0.072 YES
3 PDE4B PDE4B PDE4B 434 0.59 0.084 YES
4 NPR1 NPR1 NPR1 615 0.54 0.1 YES
5 ADCY5 ADCY5 ADCY5 695 0.53 0.13 YES
6 PDE1B PDE1B PDE1B 728 0.52 0.15 YES
7 PDE2A PDE2A PDE2A 987 0.47 0.16 YES
8 ADCY2 ADCY2 ADCY2 1009 0.47 0.19 YES
9 ENPP3 ENPP3 ENPP3 1055 0.46 0.21 YES
10 PAPSS2 PAPSS2 PAPSS2 1268 0.44 0.22 YES
11 PDE6G PDE6G PDE6G 1313 0.43 0.24 YES
12 GUCY1B3 GUCY1B3 GUCY1B3 1372 0.42 0.26 YES
13 GUCY1A3 GUCY1A3 GUCY1A3 1382 0.42 0.28 YES
14 ADCY4 ADCY4 ADCY4 1678 0.38 0.28 YES
15 NT5M NT5M NT5M 1710 0.38 0.3 YES
16 PDE5A PDE5A PDE5A 1760 0.37 0.32 YES
17 PDE3A PDE3A PDE3A 1784 0.37 0.34 YES
18 AMPD1 AMPD1 AMPD1 1809 0.36 0.35 YES
19 NPR2 NPR2 NPR2 1827 0.36 0.37 YES
20 GMPR GMPR GMPR 2046 0.33 0.38 YES
21 NT5E NT5E NT5E 2060 0.33 0.39 YES
22 PDE1C PDE1C PDE1C 2137 0.32 0.4 YES
23 PDE6B PDE6B PDE6B 2169 0.31 0.42 YES
24 AK5 AK5 AK5 2428 0.28 0.42 YES
25 GUCY1A2 GUCY1A2 GUCY1A2 2530 0.27 0.43 YES
26 ADCY7 ADCY7 ADCY7 2761 0.25 0.43 YES
27 ENTPD1 ENTPD1 ENTPD1 2782 0.25 0.44 YES
28 PDE11A PDE11A PDE11A 2833 0.24 0.45 YES
29 ADCY9 ADCY9 ADCY9 3050 0.22 0.45 YES
30 NME5 NME5 NME5 3229 0.21 0.45 YES
31 PDE3B PDE3B PDE3B 3391 0.2 0.45 YES
32 PDE4A PDE4A PDE4A 3486 0.19 0.46 YES
33 ADA ADA ADA 3637 0.18 0.46 YES
34 AK1 AK1 AK1 4001 0.15 0.45 NO
35 POLR3GL POLR3GL POLR3GL 4069 0.15 0.45 NO
36 PDE4D PDE4D PDE4D 4652 0.11 0.42 NO
37 PDE9A PDE9A PDE9A 4698 0.11 0.43 NO
38 NME7 NME7 NME7 4725 0.11 0.43 NO
39 IMPDH1 IMPDH1 IMPDH1 4742 0.11 0.44 NO
40 AK7 AK7 AK7 4831 0.1 0.44 NO
41 PRIM1 PRIM1 PRIM1 5018 0.096 0.43 NO
42 AK3L1 AK3L1 AK3L1 5553 0.076 0.41 NO
43 POLR1E POLR1E POLR1E 5595 0.075 0.41 NO
44 ENTPD8 ENTPD8 ENTPD8 5624 0.074 0.41 NO
45 PDE7B PDE7B PDE7B 5645 0.073 0.41 NO
46 PRPS1 PRPS1 PRPS1 5646 0.073 0.42 NO
47 AMPD3 AMPD3 AMPD3 5696 0.071 0.42 NO
48 POLR3C POLR3C POLR3C 5901 0.064 0.41 NO
49 POLR3D POLR3D POLR3D 5909 0.064 0.41 NO
50 PRPS1L1 PRPS1L1 PRPS1L1 6037 0.061 0.41 NO
51 POLD4 POLD4 POLD4 6553 0.048 0.38 NO
52 POLA2 POLA2 POLA2 6555 0.048 0.39 NO
53 AMPD2 AMPD2 AMPD2 6605 0.047 0.39 NO
54 POLE4 POLE4 POLE4 7013 0.039 0.37 NO
55 GUK1 GUK1 GUK1 7066 0.038 0.36 NO
56 PDE6D PDE6D PDE6D 7069 0.038 0.37 NO
57 CANT1 CANT1 CANT1 7126 0.036 0.37 NO
58 GUCY2C GUCY2C GUCY2C 7147 0.036 0.37 NO
59 POLR3G POLR3G POLR3G 7209 0.035 0.36 NO
60 POLR2L POLR2L POLR2L 7286 0.034 0.36 NO
61 ADSL ADSL ADSL 7291 0.034 0.36 NO
62 ATIC ATIC ATIC 7626 0.028 0.35 NO
63 POLD1 POLD1 POLD1 7733 0.026 0.34 NO
64 POLD3 POLD3 POLD3 7851 0.024 0.34 NO
65 DCK DCK DCK 7877 0.023 0.34 NO
66 GUCY2D GUCY2D GUCY2D 7997 0.022 0.33 NO
67 PRIM2 PRIM2 PRIM2 8011 0.021 0.33 NO
68 PAPSS1 PAPSS1 PAPSS1 8022 0.021 0.33 NO
69 ADCY6 ADCY6 ADCY6 8046 0.021 0.33 NO
70 POLR2I POLR2I POLR2I 8072 0.02 0.33 NO
71 NME4 NME4 NME4 8188 0.019 0.33 NO
72 PDE6A PDE6A PDE6A 8207 0.018 0.33 NO
73 NME6 NME6 NME6 8237 0.018 0.33 NO
74 RRM1 RRM1 RRM1 8293 0.017 0.32 NO
75 POLR2D POLR2D POLR2D 8305 0.017 0.32 NO
76 POLA1 POLA1 POLA1 8312 0.017 0.32 NO
77 POLR2E POLR2E POLR2E 8321 0.017 0.32 NO
78 PDE8B PDE8B PDE8B 8322 0.017 0.33 NO
79 PNP PNP PNP 8393 0.016 0.32 NO
80 NUDT5 NUDT5 NUDT5 8521 0.014 0.32 NO
81 GMPS GMPS GMPS 8579 0.013 0.31 NO
82 POLR2G POLR2G POLR2G 8932 0.0085 0.3 NO
83 POLE3 POLE3 POLE3 8937 0.0085 0.3 NO
84 POLR3F POLR3F POLR3F 9095 0.0064 0.29 NO
85 NME3 NME3 NME3 9319 0.004 0.28 NO
86 POLR2C POLR2C POLR2C 9430 0.0029 0.27 NO
87 NUDT2 NUDT2 NUDT2 9639 0.00063 0.26 NO
88 ITPA ITPA ITPA 9778 -0.00096 0.25 NO
89 ADCY1 ADCY1 ADCY1 9854 -0.0018 0.25 NO
90 RRM2 RRM2 RRM2 9915 -0.0024 0.24 NO
91 RRM2B RRM2B RRM2B 10032 -0.0036 0.24 NO
92 POLD2 POLD2 POLD2 10141 -0.0051 0.23 NO
93 ADCY10 ADCY10 ADCY10 10344 -0.0076 0.22 NO
94 POLR3A POLR3A POLR3A 10468 -0.0092 0.21 NO
95 PKM2 PKM2 PKM2 10677 -0.011 0.2 NO
96 IMPDH2 IMPDH2 IMPDH2 10725 -0.012 0.2 NO
97 POLR1A POLR1A POLR1A 10772 -0.012 0.2 NO
98 GMPR2 GMPR2 GMPR2 10958 -0.015 0.19 NO
99 POLR2J2 POLR2J2 POLR2J2 10978 -0.015 0.19 NO
100 PFAS PFAS PFAS 11141 -0.017 0.18 NO
101 NME1-NME2 NME1-NME2 NME1-NME2 11161 -0.017 0.18 NO
102 GART GART GART 11193 -0.018 0.18 NO
103 AK2 AK2 AK2 11218 -0.018 0.18 NO
104 ADK ADK ADK 11240 -0.018 0.18 NO
105 POLE2 POLE2 POLE2 11422 -0.02 0.17 NO
106 POLR2F POLR2F POLR2F 11531 -0.021 0.16 NO
107 ENTPD2 ENTPD2 ENTPD2 12019 -0.027 0.14 NO
108 DGUOK DGUOK DGUOK 12063 -0.028 0.14 NO
109 POLR2A POLR2A POLR2A 12172 -0.029 0.13 NO
110 POLR3H POLR3H POLR3H 12180 -0.029 0.14 NO
111 POLE POLE POLE 12219 -0.03 0.14 NO
112 PRUNE PRUNE PRUNE 12234 -0.03 0.14 NO
113 POLR2B POLR2B POLR2B 12346 -0.031 0.13 NO
114 FHIT FHIT FHIT 12375 -0.031 0.13 NO
115 POLR3K POLR3K POLR3K 12449 -0.032 0.13 NO
116 APRT APRT APRT 12729 -0.036 0.12 NO
117 POLR2J POLR2J POLR2J 12987 -0.04 0.1 NO
118 PNPT1 PNPT1 PNPT1 13154 -0.042 0.096 NO
119 ENTPD6 ENTPD6 ENTPD6 13316 -0.044 0.09 NO
120 HPRT1 HPRT1 HPRT1 13544 -0.047 0.08 NO
121 ADSS ADSS ADSS 13554 -0.048 0.082 NO
122 PDE7A PDE7A PDE7A 13584 -0.048 0.082 NO
123 PKLR PKLR PKLR 13620 -0.048 0.083 NO
124 NUDT9 NUDT9 NUDT9 13749 -0.05 0.079 NO
125 PRPS2 PRPS2 PRPS2 13785 -0.051 0.079 NO
126 PPAT PPAT PPAT 13875 -0.052 0.077 NO
127 POLR2K POLR2K POLR2K 14014 -0.054 0.072 NO
128 POLR1D POLR1D POLR1D 14024 -0.055 0.075 NO
129 POLR2H POLR2H POLR2H 14026 -0.055 0.078 NO
130 NME2 NME2 NME2 14047 -0.055 0.079 NO
131 ENTPD4 ENTPD4 ENTPD4 14130 -0.057 0.078 NO
132 NME1 NME1 NME1 14191 -0.058 0.078 NO
133 POLR3B POLR3B POLR3B 14204 -0.058 0.08 NO
134 ZNRD1 ZNRD1 ZNRD1 14394 -0.062 0.073 NO
135 PDE4C PDE4C PDE4C 14554 -0.065 0.067 NO
136 PAICS PAICS PAICS 14699 -0.068 0.063 NO
137 NT5C3 NT5C3 NT5C3 14743 -0.069 0.064 NO
138 NT5C NT5C NT5C 14928 -0.073 0.058 NO
139 PDE8A PDE8A PDE8A 15449 -0.086 0.034 NO
140 NT5C2 NT5C2 NT5C2 15469 -0.087 0.037 NO
141 POLR1B POLR1B POLR1B 15512 -0.088 0.039 NO
142 POLR1C POLR1C POLR1C 15740 -0.096 0.032 NO
143 POLR2J3 POLR2J3 POLR2J3 16501 -0.13 -0.0032 NO
144 ENTPD5 ENTPD5 ENTPD5 16647 -0.14 -0.0038 NO
145 PDE10A PDE10A PDE10A 17355 -0.2 -0.032 NO
146 ADSSL1 ADSSL1 ADSSL1 17536 -0.22 -0.031 NO
147 GDA GDA GDA 17826 -0.27 -0.032 NO
148 XDH XDH XDH 17988 -0.32 -0.024 NO
149 ENTPD3 ENTPD3 ENTPD3 18016 -0.32 -0.009 NO
150 NT5C1B NT5C1B NT5C1B 18087 -0.36 0.0061 NO

Figure S13.  Get High-res Image This plot shows mRNAseq_cNMF expression data heatmap (on the left) a RunningEnrichmentScore(RES) plot (on the top right) and a Signal2Noise(S2N) plot (on the bottom right) of genes in the pathway: BIOCARTA EGF PATHWAY.

Figure S14.  Get High-res Image For the top 5 core enriched genes in the pathway: BIOCARTA EGF PATHWAY, this volcano plot shows how much they are up/down-regulated and significant. The significance was calculated by empirical bayesian fit

genes ES table in pathway: BIOCARTA ERK PATHWAY

Table S8.  Get Full Table This table shows a Running Enrichment Score (RES) of each gene in this pathway, that is, the enrichment score at this point in the ranked list of genes. All genes are ranked by Signal-to-Noise (S2N), a measure of similarity as default and are used to obtain ES matrix of all genes. In this way, GSEA tool uses expression pattern of not only overlapped genes but also not-overlapped genes to produce ES matrix.

Rank GENE SYMBOL DESC LIST.LOC S2N RES CORE_ENRICHMENT
1 FGF7 FGF7 FGF7 37 0.77 0.02 YES
2 FGF2 FGF2 FGF2 161 0.67 0.032 YES
3 ITGAM ITGAM ITGAM 171 0.67 0.05 YES
4 ITGA11 ITGA11 ITGA11 188 0.66 0.068 YES
5 NCKAP1L NCKAP1L NCKAP1L 210 0.65 0.085 YES
6 FGFR1 FGFR1 FGFR1 249 0.64 0.1 YES
7 ITGA7 ITGA7 ITGA7 267 0.63 0.12 YES
8 FGF14 FGF14 FGF14 328 0.61 0.13 YES
9 PIK3R5 PIK3R5 PIK3R5 353 0.61 0.15 YES
10 WAS WAS WAS 449 0.58 0.16 YES
11 IQGAP2 IQGAP2 IQGAP2 462 0.58 0.18 YES
12 ITGB2 ITGB2 ITGB2 551 0.56 0.19 YES
13 FGF1 FGF1 FGF1 580 0.55 0.2 YES
14 ITGB3 ITGB3 ITGB3 600 0.54 0.21 YES
15 MYLK MYLK MYLK 612 0.54 0.23 YES
16 PDGFRA PDGFRA PDGFRA 691 0.53 0.24 YES
17 ITGAX ITGAX ITGAX 756 0.52 0.25 YES
18 CD14 CD14 CD14 763 0.51 0.26 YES
19 ACTN2 ACTN2 ACTN2 805 0.51 0.28 YES
20 PDGFC PDGFC PDGFC 862 0.5 0.29 YES
21 ITGAL ITGAL ITGAL 884 0.49 0.3 YES
22 FN1 FN1 FN1 965 0.48 0.31 YES
23 MYL9 MYL9 MYL9 989 0.47 0.32 YES
24 ITGA4 ITGA4 ITGA4 994 0.47 0.33 YES
25 TIAM2 TIAM2 TIAM2 1007 0.47 0.35 YES
26 VAV1 VAV1 VAV1 1049 0.47 0.36 YES
27 MRAS MRAS MRAS 1116 0.46 0.37 YES
28 FGF10 FGF10 FGF10 1125 0.46 0.38 YES
29 CHRM2 CHRM2 CHRM2 1143 0.45 0.39 YES
30 PDGFRB PDGFRB PDGFRB 1207 0.44 0.4 YES
31 ITGA9 ITGA9 ITGA9 1237 0.44 0.41 YES
32 PIK3CG PIK3CG PIK3CG 1254 0.44 0.42 YES
33 INSRR INSRR INSRR 1284 0.43 0.43 YES
34 ITGAD ITGAD ITGAD 1286 0.43 0.44 YES
35 FGF18 FGF18 FGF18 1296 0.43 0.46 YES
36 PIK3CD PIK3CD PIK3CD 1387 0.42 0.46 YES
37 CFL2 CFL2 CFL2 1413 0.41 0.47 YES
38 CHRM4 CHRM4 CHRM4 1591 0.39 0.48 YES
39 ITGA5 ITGA5 ITGA5 1780 0.37 0.48 YES
40 FGF13 FGF13 FGF13 1829 0.36 0.48 YES
41 FGF5 FGF5 FGF5 1848 0.36 0.49 YES
42 ACTN3 ACTN3 ACTN3 1928 0.34 0.5 YES
43 ITGA10 ITGA10 ITGA10 1961 0.34 0.5 YES
44 FGF9 FGF9 FGF9 2071 0.33 0.51 YES
45 ITGA1 ITGA1 ITGA1 2136 0.32 0.51 YES
46 PIP4K2A PIP4K2A PIP4K2A 2327 0.3 0.51 YES
47 F2R F2R F2R 2412 0.28 0.52 YES
48 PDGFB PDGFB PDGFB 2464 0.28 0.52 YES
49 PIP5K1B PIP5K1B PIP5K1B 2480 0.28 0.53 YES
50 PAK3 PAK3 PAK3 2503 0.27 0.53 YES
51 BDKRB1 BDKRB1 BDKRB1 2845 0.24 0.52 YES
52 PDGFD PDGFD PDGFD 2879 0.24 0.53 YES
53 ARHGEF6 ARHGEF6 ARHGEF6 3020 0.22 0.52 YES
54 ACTN1 ACTN1 ACTN1 3152 0.21 0.52 YES
55 ITGA8 ITGA8 ITGA8 3241 0.21 0.52 YES
56 RRAS RRAS RRAS 3256 0.21 0.53 YES
57 MYH10 MYH10 MYH10 3377 0.2 0.53 YES
58 MSN MSN MSN 3431 0.19 0.53 YES
59 GSN GSN GSN 3441 0.19 0.54 YES
60 CHRM5 CHRM5 CHRM5 3485 0.19 0.54 YES
61 ITGB5 ITGB5 ITGB5 3553 0.18 0.54 YES
62 BDKRB2 BDKRB2 BDKRB2 3647 0.18 0.54 NO
63 RAC2 RAC2 RAC2 3743 0.17 0.54 NO
64 GNA12 GNA12 GNA12 3883 0.16 0.54 NO
65 DIAPH3 DIAPH3 DIAPH3 3967 0.15 0.54 NO
66 PFN4 PFN4 PFN4 4042 0.15 0.54 NO
67 RDX RDX RDX 4229 0.14 0.53 NO
68 FGD1 FGD1 FGD1 4232 0.14 0.53 NO
69 ITGB7 ITGB7 ITGB7 4298 0.13 0.53 NO
70 RAC3 RAC3 RAC3 4332 0.13 0.54 NO
71 TMSB4Y TMSB4Y TMSB4Y 4426 0.12 0.53 NO
72 CHRM3 CHRM3 CHRM3 4481 0.12 0.53 NO
73 CYFIP2 CYFIP2 CYFIP2 4567 0.12 0.53 NO
74 ITGAV ITGAV ITGAV 4587 0.12 0.54 NO
75 PDGFA PDGFA PDGFA 4589 0.12 0.54 NO
76 ARPC1B ARPC1B ARPC1B 4712 0.11 0.54 NO
77 CHRM1 CHRM1 CHRM1 4781 0.11 0.53 NO
78 VCL VCL VCL 4999 0.097 0.52 NO
79 ITGB1 ITGB1 ITGB1 5148 0.09 0.52 NO
80 ENAH ENAH ENAH 5185 0.088 0.52 NO
81 LIMK1 LIMK1 LIMK1 5280 0.085 0.52 NO
82 ACTB ACTB ACTB 5294 0.084 0.52 NO
83 ITGAE ITGAE ITGAE 5363 0.082 0.52 NO
84 ITGA2B ITGA2B ITGA2B 5389 0.081 0.52 NO
85 RHOA RHOA RHOA 5572 0.075 0.51 NO
86 MYLK3 MYLK3 MYLK3 5619 0.074 0.51 NO
87 MAPK3 MAPK3 MAPK3 5782 0.068 0.5 NO
88 PIP5K1C PIP5K1C PIP5K1C 5798 0.068 0.5 NO
89 MYL12A MYL12A MYL12A 5923 0.064 0.5 NO
90 ARHGEF1 ARHGEF1 ARHGEF1 5972 0.063 0.5 NO
91 BCAR1 BCAR1 BCAR1 5984 0.062 0.5 NO
92 ABI2 ABI2 ABI2 5998 0.062 0.5 NO
93 TMSL3 TMSL3 TMSL3 6074 0.06 0.5 NO
94 FGD3 FGD3 FGD3 6115 0.059 0.5 NO
95 PFN1 PFN1 PFN1 6212 0.056 0.49 NO
96 ROCK1 ROCK1 ROCK1 6236 0.055 0.49 NO
97 MYH9 MYH9 MYH9 6251 0.055 0.49 NO
98 ROCK2 ROCK2 ROCK2 6446 0.05 0.48 NO
99 FGF22 FGF22 FGF22 6456 0.05 0.48 NO
100 PPP1R12A PPP1R12A PPP1R12A 6469 0.05 0.49 NO
101 GNG12 GNG12 GNG12 6571 0.048 0.48 NO
102 ARAF ARAF ARAF 6619 0.047 0.48 NO
103 ARPC4 ARPC4 ARPC4 6687 0.045 0.48 NO
104 DIAPH2 DIAPH2 DIAPH2 7022 0.039 0.46 NO
105 SSH1 SSH1 SSH1 7076 0.037 0.46 NO
106 RRAS2 RRAS2 RRAS2 7290 0.034 0.45 NO
107 FGF8 FGF8 FGF8 7343 0.033 0.45 NO
108 DOCK1 DOCK1 DOCK1 7376 0.032 0.44 NO
109 GNA13 GNA13 GNA13 7397 0.032 0.44 NO
110 SSH2 SSH2 SSH2 7412 0.032 0.44 NO
111 IQGAP1 IQGAP1 IQGAP1 7438 0.031 0.44 NO
112 VAV2 VAV2 VAV2 7477 0.031 0.44 NO
113 WASF1 WASF1 WASF1 7499 0.03 0.44 NO
114 CSK CSK CSK 7561 0.029 0.44 NO
115 ARPC5 ARPC5 ARPC5 7572 0.029 0.44 NO
116 CFL1 CFL1 CFL1 7694 0.027 0.44 NO
117 EGF EGF EGF 7701 0.026 0.44 NO
118 PIK3R1 PIK3R1 PIK3R1 7820 0.024 0.43 NO
119 ACTN4 ACTN4 ACTN4 7857 0.024 0.43 NO
120 PIP5K1A PIP5K1A PIP5K1A 8073 0.02 0.42 NO
121 PIP4K2B PIP4K2B PIP4K2B 8186 0.019 0.41 NO
122 MAP2K2 MAP2K2 MAP2K2 8259 0.018 0.41 NO
123 ARPC5L ARPC5L ARPC5L 8288 0.017 0.41 NO
124 PIK3R3 PIK3R3 PIK3R3 8553 0.014 0.39 NO
125 PIK3CA PIK3CA PIK3CA 8689 0.012 0.38 NO
126 MAP2K1 MAP2K1 MAP2K1 9023 0.0074 0.37 NO
127 BAIAP2 BAIAP2 BAIAP2 9089 0.0065 0.36 NO
128 CYFIP1 CYFIP1 CYFIP1 9145 0.0058 0.36 NO
129 PIK3CB PIK3CB PIK3CB 9188 0.0054 0.36 NO
130 ARPC2 ARPC2 ARPC2 9212 0.0052 0.36 NO
131 MAPK1 MAPK1 MAPK1 9367 0.0035 0.35 NO
132 APC2 APC2 APC2 9412 0.0031 0.35 NO
133 WASF2 WASF2 WASF2 9413 0.003 0.35 NO
134 PAK2 PAK2 PAK2 9472 0.0025 0.34 NO
135 PPP1CB PPP1CB PPP1CB 9500 0.0021 0.34 NO
136 GRLF1 GRLF1 GRLF1 9636 0.00072 0.33 NO
137 NRAS NRAS NRAS 10018 -0.0035 0.31 NO
138 ACTG1 ACTG1 ACTG1 10082 -0.0042 0.31 NO
139 FGF19 FGF19 FGF19 10087 -0.0042 0.31 NO
140 CRK CRK CRK 10227 -0.0061 0.3 NO
141 PPP1CC PPP1CC PPP1CC 10256 -0.0066 0.3 NO
142 RAF1 RAF1 RAF1 10280 -0.0068 0.3 NO
143 PXN PXN PXN 10763 -0.012 0.27 NO
144 PPP1CA PPP1CA PPP1CA 10765 -0.012 0.27 NO
145 CDC42 CDC42 CDC42 10923 -0.015 0.26 NO
146 FGF12 FGF12 FGF12 10961 -0.015 0.26 NO
147 GIT1 GIT1 GIT1 10967 -0.015 0.26 NO
148 DIAPH1 DIAPH1 DIAPH1 10988 -0.015 0.26 NO
149 ARHGEF7 ARHGEF7 ARHGEF7 11142 -0.017 0.26 NO
150 PIKFYVE PIKFYVE PIKFYVE 11172 -0.017 0.25 NO
151 SOS2 SOS2 SOS2 11197 -0.018 0.25 NO
152 MYL12B MYL12B MYL12B 11621 -0.022 0.23 NO
153 APC APC APC 11907 -0.026 0.22 NO
154 RAC1 RAC1 RAC1 11993 -0.027 0.21 NO
155 SOS1 SOS1 SOS1 12020 -0.027 0.21 NO
156 KRAS KRAS KRAS 12296 -0.03 0.2 NO
157 LIMK2 LIMK2 LIMK2 12585 -0.034 0.18 NO
158 ARPC3 ARPC3 ARPC3 12616 -0.034 0.18 NO
159 F2 F2 F2 13010 -0.04 0.16 NO
160 NCKAP1 NCKAP1 NCKAP1 13096 -0.041 0.16 NO
161 ITGA2 ITGA2 ITGA2 13114 -0.041 0.16 NO
162 FGF17 FGF17 FGF17 13442 -0.046 0.14 NO
163 PAK4 PAK4 PAK4 13464 -0.046 0.14 NO
164 EGFR EGFR EGFR 13569 -0.048 0.14 NO
165 ARHGEF12 ARHGEF12 ARHGEF12 13672 -0.049 0.13 NO
166 EZR EZR EZR 13769 -0.05 0.13 NO
167 ARPC1A ARPC1A ARPC1A 13784 -0.051 0.13 NO
168 MYLPF MYLPF MYLPF 13867 -0.052 0.12 NO
169 PIP4K2C PIP4K2C PIP4K2C 13873 -0.052 0.12 NO
170 PIK3R2 PIK3R2 PIK3R2 14062 -0.055 0.12 NO
171 ARHGEF4 ARHGEF4 ARHGEF4 14121 -0.057 0.12 NO
172 CRKL CRKL CRKL 14128 -0.057 0.12 NO
173 FGFR2 FGFR2 FGFR2 14470 -0.064 0.099 NO
174 IQGAP3 IQGAP3 IQGAP3 14478 -0.064 0.1 NO
175 FGFR4 FGFR4 FGFR4 14602 -0.066 0.096 NO
176 ITGB8 ITGB8 ITGB8 14759 -0.069 0.089 NO
177 PAK1 PAK1 PAK1 14825 -0.071 0.087 NO
178 PFN2 PFN2 PFN2 14932 -0.073 0.083 NO
179 WASL WASL WASL 15303 -0.082 0.065 NO
180 PTK2 PTK2 PTK2 15586 -0.091 0.052 NO
181 SLC9A1 SLC9A1 SLC9A1 15777 -0.098 0.044 NO
182 MYLK2 MYLK2 MYLK2 16024 -0.11 0.034 NO
183 MYL5 MYL5 MYL5 16071 -0.11 0.034 NO
184 TIAM1 TIAM1 TIAM1 16257 -0.12 0.027 NO
185 ITGA3 ITGA3 ITGA3 16325 -0.12 0.027 NO
186 ITGA6 ITGA6 ITGA6 16326 -0.12 0.03 NO
187 PAK7 PAK7 PAK7 16857 -0.16 0.0056 NO
188 ITGB4 ITGB4 ITGB4 16978 -0.17 0.0036 NO
189 FGF11 FGF11 FGF11 16996 -0.17 0.0074 NO
190 SCIN SCIN SCIN 17015 -0.17 0.011 NO
191 BRAF BRAF BRAF 17100 -0.18 0.012 NO
192 MYH14 MYH14 MYH14 17159 -0.18 0.014 NO
193 ITGB6 ITGB6 ITGB6 17349 -0.2 0.0088 NO
194 SSH3 SSH3 SSH3 17700 -0.25 -0.0036 NO
195 PAK6 PAK6 PAK6 17935 -0.3 -0.0082 NO
196 VAV3 VAV3 VAV3 18026 -0.33 -0.0039 NO
197 FGFR3 FGFR3 FGFR3 18190 -0.47 0.00039 NO

Figure S15.  Get High-res Image This plot shows mRNAseq_cNMF expression data heatmap (on the left) a RunningEnrichmentScore(RES) plot (on the top right) and a Signal2Noise(S2N) plot (on the bottom right) of genes in the pathway: BIOCARTA ERK PATHWAY.

Figure S16.  Get High-res Image For the top 5 core enriched genes in the pathway: BIOCARTA ERK PATHWAY, this volcano plot shows how much they are up/down-regulated and significant. The significance was calculated by empirical bayesian fit

genes ES table in pathway: BIOCARTA FCER1 PATHWAY

Table S9.  Get Full Table This table shows a Running Enrichment Score (RES) of each gene in this pathway, that is, the enrichment score at this point in the ranked list of genes. All genes are ranked by Signal-to-Noise (S2N), a measure of similarity as default and are used to obtain ES matrix of all genes. In this way, GSEA tool uses expression pattern of not only overlapped genes but also not-overlapped genes to produce ES matrix.

Rank GENE SYMBOL DESC LIST.LOC S2N RES CORE_ENRICHMENT
1 LY96 LY96 LY96 158 0.67 0.18 YES
2 CD14 CD14 CD14 763 0.51 0.3 YES
3 LEF1 LEF1 LEF1 1081 0.46 0.41 YES
4 LBP LBP LBP 1791 0.37 0.48 YES
5 TLR4 TLR4 TLR4 2272 0.3 0.54 YES
6 WNT1 WNT1 WNT1 2623 0.26 0.59 YES
7 FZD1 FZD1 FZD1 2980 0.23 0.64 YES
8 GJA1 GJA1 GJA1 7024 0.038 0.43 NO
9 IRAK1 IRAK1 IRAK1 7058 0.038 0.44 NO
10 CTNNB1 CTNNB1 CTNNB1 7197 0.035 0.44 NO
11 PIK3R1 PIK3R1 PIK3R1 7820 0.024 0.41 NO
12 EIF2AK2 EIF2AK2 EIF2AK2 8017 0.021 0.41 NO
13 NFKB1 NFKB1 NFKB1 8209 0.018 0.4 NO
14 PIK3CA PIK3CA PIK3CA 8689 0.012 0.38 NO
15 RELA RELA RELA 9209 0.0052 0.35 NO
16 AKT1 AKT1 AKT1 10046 -0.0038 0.31 NO
17 TIRAP TIRAP TIRAP 10495 -0.0095 0.28 NO
18 MYD88 MYD88 MYD88 11236 -0.018 0.25 NO
19 APC APC APC 11907 -0.026 0.22 NO
20 PPP2CA PPP2CA PPP2CA 12290 -0.03 0.21 NO
21 GSK3B GSK3B GSK3B 12321 -0.031 0.21 NO
22 AXIN1 AXIN1 AXIN1 12813 -0.037 0.2 NO
23 PDPK1 PDPK1 PDPK1 13384 -0.045 0.18 NO
24 DVL1 DVL1 DVL1 14040 -0.055 0.16 NO
25 CCND1 CCND1 CCND1 15241 -0.08 0.12 NO
26 GNAI1 GNAI1 GNAI1 16917 -0.16 0.07 NO

Figure S17.  Get High-res Image This plot shows mRNAseq_cNMF expression data heatmap (on the left) a RunningEnrichmentScore(RES) plot (on the top right) and a Signal2Noise(S2N) plot (on the bottom right) of genes in the pathway: BIOCARTA FCER1 PATHWAY.

Figure S18.  Get High-res Image For the top 5 core enriched genes in the pathway: BIOCARTA FCER1 PATHWAY, this volcano plot shows how much they are up/down-regulated and significant. The significance was calculated by empirical bayesian fit

genes ES table in pathway: BIOCARTA FMLP PATHWAY

Table S10.  Get Full Table This table shows a Running Enrichment Score (RES) of each gene in this pathway, that is, the enrichment score at this point in the ranked list of genes. All genes are ranked by Signal-to-Noise (S2N), a measure of similarity as default and are used to obtain ES matrix of all genes. In this way, GSEA tool uses expression pattern of not only overlapped genes but also not-overlapped genes to produce ES matrix.

Rank GENE SYMBOL DESC LIST.LOC S2N RES CORE_ENRICHMENT
1 PTPN7 PTPN7 PTPN7 752 0.52 0.03 YES
2 ZAP70 ZAP70 ZAP70 1001 0.47 0.081 YES
3 NFATC1 NFATC1 NFATC1 1043 0.47 0.14 YES
4 VAV1 VAV1 VAV1 1049 0.47 0.21 YES
5 CD3E CD3E CD3E 1118 0.46 0.26 YES
6 PIK3CG PIK3CG PIK3CG 1254 0.44 0.32 YES
7 CD247 CD247 CD247 1275 0.43 0.38 YES
8 LCK LCK LCK 1304 0.43 0.43 YES
9 PRKCB PRKCB PRKCB 1308 0.43 0.49 YES
10 CD3D CD3D CD3D 1487 0.4 0.54 YES
11 CD3G CD3G CD3G 1630 0.39 0.58 YES
12 FYN FYN FYN 1685 0.38 0.63 YES
13 LAT LAT LAT 2375 0.29 0.63 YES
14 NFATC4 NFATC4 NFATC4 2389 0.29 0.67 YES
15 NFATC2 NFATC2 NFATC2 2457 0.28 0.71 YES
16 PPP3CC PPP3CC PPP3CC 3721 0.17 0.66 NO
17 PPP3CB PPP3CB PPP3CB 5203 0.088 0.59 NO
18 CALM2 CALM2 CALM2 5414 0.08 0.59 NO
19 JUN JUN JUN 5425 0.08 0.6 NO
20 MAPK3 MAPK3 MAPK3 5782 0.068 0.59 NO
21 PRKCA PRKCA PRKCA 5833 0.067 0.6 NO
22 GRB2 GRB2 GRB2 6063 0.06 0.59 NO
23 SHC1 SHC1 SHC1 6708 0.045 0.56 NO
24 NFATC3 NFATC3 NFATC3 6862 0.042 0.56 NO
25 ELK1 ELK1 ELK1 6879 0.042 0.57 NO
26 PPP3CA PPP3CA PPP3CA 6911 0.041 0.57 NO
27 CALM3 CALM3 CALM3 6917 0.041 0.58 NO
28 RASA1 RASA1 RASA1 7028 0.038 0.57 NO
29 CALM1 CALM1 CALM1 7534 0.03 0.55 NO
30 PIK3R1 PIK3R1 PIK3R1 7820 0.024 0.54 NO
31 NFKB1 NFKB1 NFKB1 8209 0.018 0.52 NO
32 PLCG1 PLCG1 PLCG1 8217 0.018 0.52 NO
33 MAP3K1 MAP3K1 MAP3K1 8370 0.016 0.52 NO
34 PIK3CA PIK3CA PIK3CA 8689 0.012 0.5 NO
35 MAP2K1 MAP2K1 MAP2K1 9023 0.0074 0.48 NO
36 RELA RELA RELA 9209 0.0052 0.47 NO
37 NFKBIA NFKBIA NFKBIA 9532 0.0019 0.46 NO
38 RAF1 RAF1 RAF1 10280 -0.0068 0.42 NO
39 MAPK8 MAPK8 MAPK8 11676 -0.023 0.34 NO
40 RAC1 RAC1 RAC1 11993 -0.027 0.33 NO
41 SOS1 SOS1 SOS1 12020 -0.027 0.33 NO
42 FOS FOS FOS 12182 -0.029 0.32 NO
43 MAP2K4 MAP2K4 MAP2K4 13229 -0.043 0.27 NO

Figure S19.  Get High-res Image This plot shows mRNAseq_cNMF expression data heatmap (on the left) a RunningEnrichmentScore(RES) plot (on the top right) and a Signal2Noise(S2N) plot (on the bottom right) of genes in the pathway: BIOCARTA FMLP PATHWAY.

Figure S20.  Get High-res Image For the top 5 core enriched genes in the pathway: BIOCARTA FMLP PATHWAY, this volcano plot shows how much they are up/down-regulated and significant. The significance was calculated by empirical bayesian fit

Fold change

For the top enriched genes, if you want to check whether they are

Expression level

For the top enriched genes, if you want to check whether they are

An expression pattern of top(30%)/middle(30%)/low(30%) in this subtype against other subtypes is available in a heatmap

Significant gene list

For the top enriched genes, if you want to check whether they are

Subtype clus2 enriched pathways

Table 4.  Get Full Table This table shows top 10 pathways which are significantly enriched in cluster clus2. It displays only significant gene sets satisfying nom.p.val.threshold (-1), fwer.p.val.threshold (-1) , fdr.q.val.threshold (0.25) and the default table is sorted by Normalized Enrichment Score (NES). Further details on NES statistics, please visit The Broad GSEA website.

GeneSet(GS) Size(#genes) genes.ES.table ES NES NOM.p.val FDR.q.val FWER.p.val Tag.. Gene.. Signal FDR..median. glob.p.val
KEGG GLYCOLYSIS GLUCONEOGENESIS 59 genes.ES.table 0.3 1 0.46 0.82 1 0.22 0.13 0.19 0.8 0.24
KEGG PENTOSE AND GLUCURONATE INTERCONVERSIONS 26 genes.ES.table 0.79 1.7 0.015 0.29 0.54 0.62 0.12 0.55 0.14 0.068
KEGG FATTY ACID METABOLISM 41 genes.ES.table 0.42 1.3 0.19 0.69 0.99 0.46 0.24 0.35 0.59 0.19
KEGG STEROID HORMONE BIOSYNTHESIS 51 genes.ES.table 0.63 1.5 0.047 0.29 0.85 0.57 0.12 0.5 0.2 0.041
KEGG VALINE LEUCINE AND ISOLEUCINE DEGRADATION 43 genes.ES.table 0.36 1.2 0.23 0.68 0.99 0.42 0.23 0.32 0.59 0.18
KEGG TYROSINE METABOLISM 39 genes.ES.table 0.4 1.1 0.34 0.69 1 0.23 0.11 0.2 0.64 0.16
KEGG GLUTATHIONE METABOLISM 45 genes.ES.table 0.38 1.1 0.32 0.73 1 0.33 0.17 0.28 0.67 0.2
KEGG STARCH AND SUCROSE METABOLISM 46 genes.ES.table 0.55 1.4 0.061 0.42 0.93 0.44 0.13 0.38 0.32 0.086
KEGG GLYCEROPHOSPHOLIPID METABOLISM 70 genes.ES.table 0.27 1 0.41 0.8 1 0.51 0.3 0.36 0.77 0.24
KEGG ETHER LIPID METABOLISM 28 genes.ES.table 0.4 1.2 0.23 0.67 1 0.39 0.15 0.33 0.6 0.17
genes ES table in pathway: KEGG GLYCOLYSIS GLUCONEOGENESIS

Table S11.  Get Full Table This table shows a Running Enrichment Score (RES) of each gene in this pathway, that is, the enrichment score at this point in the ranked list of genes. All genes are ranked by Signal-to-Noise (S2N), a measure of similarity as default and are used to obtain ES matrix of all genes. In this way, GSEA tool uses expression pattern of not only overlapped genes but also not-overlapped genes to produce ES matrix.

Rank GENE SYMBOL DESC LIST.LOC S2N RES CORE_ENRICHMENT
1 UGT1A1 UGT1A1 UGT1A1 63 0.69 0.086 YES
2 UGT2B28 UGT2B28 UGT2B28 101 0.62 0.16 YES
3 UGT1A9 UGT1A9 UGT1A9 228 0.53 0.23 YES
4 UGT2B15 UGT2B15 UGT2B15 292 0.49 0.29 YES
5 UGT1A6 UGT1A6 UGT1A6 328 0.47 0.34 YES
6 UGT2B11 UGT2B11 UGT2B11 386 0.45 0.4 YES
7 UGT1A3 UGT1A3 UGT1A3 484 0.42 0.45 YES
8 UGT2B7 UGT2B7 UGT2B7 650 0.38 0.49 YES
9 UGT1A4 UGT1A4 UGT1A4 871 0.34 0.52 YES
10 UGT2A3 UGT2A3 UGT2A3 899 0.33 0.56 YES
11 UGT2B10 UGT2B10 UGT2B10 923 0.33 0.6 YES
12 UGT1A5 UGT1A5 UGT1A5 1105 0.3 0.63 YES
13 UGT1A10 UGT1A10 UGT1A10 1438 0.26 0.65 YES
14 UGT2B4 UGT2B4 UGT2B4 1597 0.24 0.67 YES
15 ALAS1 ALAS1 ALAS1 1634 0.24 0.7 YES
16 UGT1A8 UGT1A8 UGT1A8 1917 0.21 0.71 YES
17 PPOX PPOX PPOX 2828 0.15 0.68 NO
18 MMAB MMAB MMAB 6242 0.045 0.5 NO
19 EARS2 EARS2 EARS2 6533 0.04 0.49 NO
20 UGT1A7 UGT1A7 UGT1A7 6763 0.035 0.48 NO
21 UGT2A1 UGT2A1 UGT2A1 7310 0.025 0.45 NO
22 COX15 COX15 COX15 8174 0.0087 0.41 NO
23 GUSB GUSB GUSB 8231 0.0079 0.4 NO
24 HMOX2 HMOX2 HMOX2 8492 0.0031 0.39 NO
25 ALAD ALAD ALAD 8684 -0.00044 0.38 NO
26 COX10 COX10 COX10 9744 -0.018 0.32 NO
27 ALAS2 ALAS2 ALAS2 9880 -0.021 0.32 NO
28 FTH1 FTH1 FTH1 10848 -0.04 0.27 NO
29 HMBS HMBS HMBS 11034 -0.045 0.27 NO
30 UROD UROD UROD 11281 -0.05 0.26 NO
31 CP CP CP 11534 -0.055 0.25 NO
32 CPOX CPOX CPOX 11837 -0.063 0.24 NO
33 EPRS EPRS EPRS 12718 -0.087 0.21 NO
34 BLVRB BLVRB BLVRB 12739 -0.088 0.22 NO
35 FECH FECH FECH 12936 -0.095 0.22 NO
36 HMOX1 HMOX1 HMOX1 13858 -0.13 0.19 NO
37 UROS UROS UROS 13937 -0.14 0.2 NO
38 BLVRA BLVRA BLVRA 15856 -0.27 0.13 NO

Figure S21.  Get High-res Image This plot shows mRNAseq_cNMF expression data heatmap (on the left) a RunningEnrichmentScore(RES) plot (on the top right) and a Signal2Noise(S2N) plot (on the bottom right) of genes in the pathway: KEGG GLYCOLYSIS GLUCONEOGENESIS.

Figure S22.  Get High-res Image For the top 5 core enriched genes in the pathway: KEGG GLYCOLYSIS GLUCONEOGENESIS, this volcano plot shows how much they are up/down-regulated and significant. The significance was calculated by empirical bayesian fit

genes ES table in pathway: KEGG PENTOSE AND GLUCURONATE INTERCONVERSIONS

Table S12.  Get Full Table This table shows a Running Enrichment Score (RES) of each gene in this pathway, that is, the enrichment score at this point in the ranked list of genes. All genes are ranked by Signal-to-Noise (S2N), a measure of similarity as default and are used to obtain ES matrix of all genes. In this way, GSEA tool uses expression pattern of not only overlapped genes but also not-overlapped genes to produce ES matrix.

Rank GENE SYMBOL DESC LIST.LOC S2N RES CORE_ENRICHMENT
1 UGT1A1 UGT1A1 UGT1A1 63 0.69 0.096 YES
2 UGT2B28 UGT2B28 UGT2B28 101 0.62 0.18 YES
3 UGT1A9 UGT1A9 UGT1A9 228 0.53 0.25 YES
4 UGT2B15 UGT2B15 UGT2B15 292 0.49 0.32 YES
5 UGT1A6 UGT1A6 UGT1A6 328 0.47 0.38 YES
6 UGT2B11 UGT2B11 UGT2B11 386 0.45 0.45 YES
7 UGT1A3 UGT1A3 UGT1A3 484 0.42 0.5 YES
8 UGT2B7 UGT2B7 UGT2B7 650 0.38 0.55 YES
9 UGT1A4 UGT1A4 UGT1A4 871 0.34 0.58 YES
10 UGT2A3 UGT2A3 UGT2A3 899 0.33 0.63 YES
11 UGT2B10 UGT2B10 UGT2B10 923 0.33 0.68 YES
12 UGT1A5 UGT1A5 UGT1A5 1105 0.3 0.71 YES
13 UGT1A10 UGT1A10 UGT1A10 1438 0.26 0.73 YES
14 UGT2B4 UGT2B4 UGT2B4 1597 0.24 0.75 YES
15 UGT1A8 UGT1A8 UGT1A8 1917 0.21 0.77 YES
16 XYLB XYLB XYLB 2104 0.2 0.79 YES
17 DCXR DCXR DCXR 3334 0.13 0.74 NO
18 CRYL1 CRYL1 CRYL1 3353 0.13 0.75 NO
19 UGT1A7 UGT1A7 UGT1A7 6763 0.035 0.57 NO
20 UGT2A1 UGT2A1 UGT2A1 7310 0.025 0.55 NO
21 GUSB GUSB GUSB 8231 0.0079 0.5 NO
22 DHDH DHDH DHDH 8241 0.0078 0.5 NO
23 AKR1B1 AKR1B1 AKR1B1 9340 -0.012 0.44 NO
24 RPE RPE RPE 11689 -0.059 0.32 NO
25 UGP2 UGP2 UGP2 12190 -0.072 0.3 NO
26 LOC729020 LOC729020 LOC729020 15183 -0.22 0.17 NO

Figure S23.  Get High-res Image This plot shows mRNAseq_cNMF expression data heatmap (on the left) a RunningEnrichmentScore(RES) plot (on the top right) and a Signal2Noise(S2N) plot (on the bottom right) of genes in the pathway: KEGG PENTOSE AND GLUCURONATE INTERCONVERSIONS.

Figure S24.  Get High-res Image For the top 5 core enriched genes in the pathway: KEGG PENTOSE AND GLUCURONATE INTERCONVERSIONS, this volcano plot shows how much they are up/down-regulated and significant. The significance was calculated by empirical bayesian fit

genes ES table in pathway: KEGG FATTY ACID METABOLISM

Table S13.  Get Full Table This table shows a Running Enrichment Score (RES) of each gene in this pathway, that is, the enrichment score at this point in the ranked list of genes. All genes are ranked by Signal-to-Noise (S2N), a measure of similarity as default and are used to obtain ES matrix of all genes. In this way, GSEA tool uses expression pattern of not only overlapped genes but also not-overlapped genes to produce ES matrix.

Rank GENE SYMBOL DESC LIST.LOC S2N RES CORE_ENRICHMENT
1 UGT1A1 UGT1A1 UGT1A1 63 0.69 0.04 YES
2 UGT2B28 UGT2B28 UGT2B28 101 0.62 0.077 YES
3 CYP3A5 CYP3A5 CYP3A5 103 0.62 0.12 YES
4 CYP2C8 CYP2C8 CYP2C8 215 0.54 0.14 YES
5 ADH6 ADH6 ADH6 216 0.54 0.18 YES
6 UGT1A9 UGT1A9 UGT1A9 228 0.53 0.21 YES
7 UGT2B15 UGT2B15 UGT2B15 292 0.49 0.24 YES
8 UGT1A6 UGT1A6 UGT1A6 328 0.47 0.26 YES
9 UGT2B11 UGT2B11 UGT2B11 386 0.45 0.29 YES
10 UGT1A3 UGT1A3 UGT1A3 484 0.42 0.31 YES
11 CYP2C9 CYP2C9 CYP2C9 485 0.42 0.34 YES
12 AKR1C2 AKR1C2 AKR1C2 514 0.41 0.36 YES
13 UGT2B7 UGT2B7 UGT2B7 650 0.38 0.38 YES
14 CYP3A7 CYP3A7 CYP3A7 732 0.36 0.4 YES
15 GSTM4 GSTM4 GSTM4 767 0.36 0.42 YES
16 AKR1C3 AKR1C3 AKR1C3 780 0.35 0.44 YES
17 CYP1A1 CYP1A1 CYP1A1 844 0.34 0.45 YES
18 UGT1A4 UGT1A4 UGT1A4 871 0.34 0.47 YES
19 GSTM2 GSTM2 GSTM2 894 0.33 0.49 YES
20 UGT2A3 UGT2A3 UGT2A3 899 0.33 0.51 YES
21 UGT2B10 UGT2B10 UGT2B10 923 0.33 0.53 YES
22 UGT1A5 UGT1A5 UGT1A5 1105 0.3 0.54 YES
23 GSTA1 GSTA1 GSTA1 1108 0.3 0.56 YES
24 CYP3A43 CYP3A43 CYP3A43 1123 0.3 0.58 YES
25 ADH1C ADH1C ADH1C 1174 0.29 0.59 YES
26 CYP2C19 CYP2C19 CYP2C19 1245 0.28 0.61 YES
27 CYP1A2 CYP1A2 CYP1A2 1252 0.28 0.62 YES
28 GSTM3 GSTM3 GSTM3 1268 0.28 0.64 YES
29 UGT1A10 UGT1A10 UGT1A10 1438 0.26 0.65 YES
30 AKR1C1 AKR1C1 AKR1C1 1475 0.26 0.66 YES
31 MGST2 MGST2 MGST2 1549 0.25 0.67 YES
32 CYP2C18 CYP2C18 CYP2C18 1564 0.25 0.69 YES
33 GSTA2 GSTA2 GSTA2 1592 0.24 0.7 YES
34 UGT2B4 UGT2B4 UGT2B4 1597 0.24 0.72 YES
35 ADH4 ADH4 ADH4 1713 0.23 0.72 YES
36 UGT1A8 UGT1A8 UGT1A8 1917 0.21 0.73 YES
37 ALDH3B2 ALDH3B2 ALDH3B2 1995 0.21 0.74 YES
38 MGST1 MGST1 MGST1 2409 0.18 0.72 NO
39 AKR1C4 AKR1C4 AKR1C4 2512 0.17 0.73 NO
40 GSTM1 GSTM1 GSTM1 2894 0.15 0.72 NO
41 GSTO2 GSTO2 GSTO2 3026 0.14 0.72 NO
42 ADH1A ADH1A ADH1A 3706 0.11 0.69 NO
43 CYP2B6 CYP2B6 CYP2B6 4695 0.082 0.64 NO
44 GSTK1 GSTK1 GSTK1 5580 0.06 0.59 NO
45 GSTZ1 GSTZ1 GSTZ1 5772 0.056 0.59 NO
46 GSTT1 GSTT1 GSTT1 6385 0.043 0.56 NO
47 ADH7 ADH7 ADH7 6742 0.036 0.54 NO
48 UGT1A7 UGT1A7 UGT1A7 6763 0.035 0.54 NO
49 MGST3 MGST3 MGST3 6837 0.034 0.54 NO
50 UGT2A1 UGT2A1 UGT2A1 7310 0.025 0.51 NO
51 CYP2E1 CYP2E1 CYP2E1 7502 0.021 0.5 NO
52 ADH5 ADH5 ADH5 7534 0.021 0.5 NO
53 DHDH DHDH DHDH 8241 0.0078 0.46 NO
54 ADH1B ADH1B ADH1B 8596 0.0015 0.44 NO
55 GSTT2 GSTT2 GSTT2 9094 -0.0074 0.42 NO
56 CYP2F1 CYP2F1 CYP2F1 9228 -0.0098 0.41 NO
57 GSTP1 GSTP1 GSTP1 9623 -0.017 0.39 NO
58 ALDH3A1 ALDH3A1 ALDH3A1 10050 -0.024 0.37 NO
59 EPHX1 EPHX1 EPHX1 11774 -0.061 0.28 NO
60 GSTO1 GSTO1 GSTO1 12133 -0.071 0.26 NO
61 ALDH3B1 ALDH3B1 ALDH3B1 12363 -0.077 0.26 NO
62 GSTA4 GSTA4 GSTA4 13952 -0.14 0.18 NO
63 ALDH1A3 ALDH1A3 ALDH1A3 14609 -0.17 0.15 NO
64 GSTM5 GSTM5 GSTM5 14772 -0.18 0.15 NO
65 CYP2S1 CYP2S1 CYP2S1 15434 -0.24 0.13 NO
66 CYP1B1 CYP1B1 CYP1B1 16545 -0.34 0.091 NO

Figure S25.  Get High-res Image This plot shows mRNAseq_cNMF expression data heatmap (on the left) a RunningEnrichmentScore(RES) plot (on the top right) and a Signal2Noise(S2N) plot (on the bottom right) of genes in the pathway: KEGG FATTY ACID METABOLISM.

Figure S26.  Get High-res Image For the top 5 core enriched genes in the pathway: KEGG FATTY ACID METABOLISM, this volcano plot shows how much they are up/down-regulated and significant. The significance was calculated by empirical bayesian fit

genes ES table in pathway: KEGG STEROID HORMONE BIOSYNTHESIS

Table S14.  Get Full Table This table shows a Running Enrichment Score (RES) of each gene in this pathway, that is, the enrichment score at this point in the ranked list of genes. All genes are ranked by Signal-to-Noise (S2N), a measure of similarity as default and are used to obtain ES matrix of all genes. In this way, GSEA tool uses expression pattern of not only overlapped genes but also not-overlapped genes to produce ES matrix.

Rank GENE SYMBOL DESC LIST.LOC S2N RES CORE_ENRICHMENT
1 UGT1A1 UGT1A1 UGT1A1 63 0.69 0.042 YES
2 UGT2B28 UGT2B28 UGT2B28 101 0.62 0.081 YES
3 CYP3A5 CYP3A5 CYP3A5 103 0.62 0.12 YES
4 CYP2C8 CYP2C8 CYP2C8 215 0.54 0.15 YES
5 ADH6 ADH6 ADH6 216 0.54 0.19 YES
6 UGT1A9 UGT1A9 UGT1A9 228 0.53 0.22 YES
7 UGT2B15 UGT2B15 UGT2B15 292 0.49 0.25 YES
8 UGT1A6 UGT1A6 UGT1A6 328 0.47 0.28 YES
9 UGT2B11 UGT2B11 UGT2B11 386 0.45 0.3 YES
10 DGAT2 DGAT2 DGAT2 461 0.43 0.33 YES
11 UGT1A3 UGT1A3 UGT1A3 484 0.42 0.36 YES
12 CYP2C9 CYP2C9 CYP2C9 485 0.42 0.38 YES
13 UGT2B7 UGT2B7 UGT2B7 650 0.38 0.4 YES
14 CYP3A7 CYP3A7 CYP3A7 732 0.36 0.42 YES
15 CYP4A11 CYP4A11 CYP4A11 816 0.35 0.44 YES
16 CYP1A1 CYP1A1 CYP1A1 844 0.34 0.46 YES
17 UGT1A4 UGT1A4 UGT1A4 871 0.34 0.48 YES
18 UGT2A3 UGT2A3 UGT2A3 899 0.33 0.5 YES
19 UGT2B10 UGT2B10 UGT2B10 923 0.33 0.52 YES
20 ALDH1A2 ALDH1A2 ALDH1A2 937 0.33 0.54 YES
21 UGT1A5 UGT1A5 UGT1A5 1105 0.3 0.55 YES
22 CYP3A43 CYP3A43 CYP3A43 1123 0.3 0.57 YES
23 ADH1C ADH1C ADH1C 1174 0.29 0.58 YES
24 CYP2C19 CYP2C19 CYP2C19 1245 0.28 0.6 YES
25 CYP1A2 CYP1A2 CYP1A2 1252 0.28 0.62 YES
26 UGT1A10 UGT1A10 UGT1A10 1438 0.26 0.62 YES
27 BCMO1 BCMO1 BCMO1 1546 0.25 0.64 YES
28 CYP2C18 CYP2C18 CYP2C18 1564 0.25 0.65 YES
29 UGT2B4 UGT2B4 UGT2B4 1597 0.24 0.66 YES
30 CYP4A22 CYP4A22 CYP4A22 1602 0.24 0.68 YES
31 ADH4 ADH4 ADH4 1713 0.23 0.69 YES
32 UGT1A8 UGT1A8 UGT1A8 1917 0.21 0.69 YES
33 DHRS3 DHRS3 DHRS3 2931 0.15 0.65 NO
34 DGAT1 DGAT1 DGAT1 3007 0.14 0.65 NO
35 ADH1A ADH1A ADH1A 3706 0.11 0.62 NO
36 CYP2B6 CYP2B6 CYP2B6 4695 0.082 0.57 NO
37 LRAT LRAT LRAT 5094 0.072 0.55 NO
38 RDH16 RDH16 RDH16 5929 0.052 0.51 NO
39 RDH10 RDH10 RDH10 6057 0.049 0.51 NO
40 RDH12 RDH12 RDH12 6532 0.04 0.48 NO
41 ADH7 ADH7 ADH7 6742 0.036 0.48 NO
42 UGT1A7 UGT1A7 UGT1A7 6763 0.035 0.48 NO
43 RDH11 RDH11 RDH11 6767 0.035 0.48 NO
44 UGT2A1 UGT2A1 UGT2A1 7310 0.025 0.45 NO
45 ADH5 ADH5 ADH5 7534 0.021 0.44 NO
46 ADH1B ADH1B ADH1B 8596 0.0015 0.38 NO
47 CYP2A6 CYP2A6 CYP2A6 8619 0.00096 0.38 NO
48 CYP26A1 CYP26A1 CYP26A1 8698 -0.0006 0.38 NO
49 PNPLA4 PNPLA4 PNPLA4 9793 -0.019 0.32 NO
50 RDH5 RDH5 RDH5 10060 -0.024 0.3 NO
51 DHRS4 DHRS4 DHRS4 10413 -0.031 0.29 NO
52 DHRS4L2 DHRS4L2 DHRS4L2 10705 -0.037 0.27 NO
53 RETSAT RETSAT RETSAT 10816 -0.039 0.27 NO
54 CYP26C1 CYP26C1 CYP26C1 10985 -0.044 0.26 NO
55 AWAT2 AWAT2 AWAT2 12807 -0.09 0.17 NO
56 RPE65 RPE65 RPE65 15256 -0.22 0.048 NO
57 RDH8 RDH8 RDH8 15595 -0.25 0.046 NO
58 ALDH1A1 ALDH1A1 ALDH1A1 16757 -0.37 0.0063 NO
59 DHRS9 DHRS9 DHRS9 17382 -0.47 0.0027 NO
60 CYP26B1 CYP26B1 CYP26B1 17962 -0.64 0.013 NO

Figure S27.  Get High-res Image This plot shows mRNAseq_cNMF expression data heatmap (on the left) a RunningEnrichmentScore(RES) plot (on the top right) and a Signal2Noise(S2N) plot (on the bottom right) of genes in the pathway: KEGG STEROID HORMONE BIOSYNTHESIS.

Figure S28.  Get High-res Image For the top 5 core enriched genes in the pathway: KEGG STEROID HORMONE BIOSYNTHESIS, this volcano plot shows how much they are up/down-regulated and significant. The significance was calculated by empirical bayesian fit

genes ES table in pathway: KEGG VALINE LEUCINE AND ISOLEUCINE DEGRADATION

Table S15.  Get Full Table This table shows a Running Enrichment Score (RES) of each gene in this pathway, that is, the enrichment score at this point in the ranked list of genes. All genes are ranked by Signal-to-Noise (S2N), a measure of similarity as default and are used to obtain ES matrix of all genes. In this way, GSEA tool uses expression pattern of not only overlapped genes but also not-overlapped genes to produce ES matrix.

Rank GENE SYMBOL DESC LIST.LOC S2N RES CORE_ENRICHMENT
1 UGT1A1 UGT1A1 UGT1A1 63 0.69 0.036 YES
2 UGT2B28 UGT2B28 UGT2B28 101 0.62 0.068 YES
3 CYP3A5 CYP3A5 CYP3A5 103 0.62 0.1 YES
4 FMO5 FMO5 FMO5 188 0.55 0.13 YES
5 CYP2C8 CYP2C8 CYP2C8 215 0.54 0.16 YES
6 ADH6 ADH6 ADH6 216 0.54 0.19 YES
7 UGT1A9 UGT1A9 UGT1A9 228 0.53 0.22 YES
8 UGT2B15 UGT2B15 UGT2B15 292 0.49 0.24 YES
9 MAOA MAOA MAOA 311 0.48 0.27 YES
10 UGT1A6 UGT1A6 UGT1A6 328 0.47 0.29 YES
11 UGT2B11 UGT2B11 UGT2B11 386 0.45 0.32 YES
12 UGT1A3 UGT1A3 UGT1A3 484 0.42 0.33 YES
13 CYP2C9 CYP2C9 CYP2C9 485 0.42 0.36 YES
14 UGT2B7 UGT2B7 UGT2B7 650 0.38 0.37 YES
15 CYP3A7 CYP3A7 CYP3A7 732 0.36 0.39 YES
16 GSTM4 GSTM4 GSTM4 767 0.36 0.4 YES
17 CYP2D6 CYP2D6 CYP2D6 788 0.35 0.42 YES
18 UGT1A4 UGT1A4 UGT1A4 871 0.34 0.44 YES
19 GSTM2 GSTM2 GSTM2 894 0.33 0.46 YES
20 UGT2A3 UGT2A3 UGT2A3 899 0.33 0.47 YES
21 UGT2B10 UGT2B10 UGT2B10 923 0.33 0.49 YES
22 UGT1A5 UGT1A5 UGT1A5 1105 0.3 0.5 YES
23 GSTA1 GSTA1 GSTA1 1108 0.3 0.51 YES
24 CYP3A43 CYP3A43 CYP3A43 1123 0.3 0.53 YES
25 ADH1C ADH1C ADH1C 1174 0.29 0.54 YES
26 CYP2C19 CYP2C19 CYP2C19 1245 0.28 0.56 YES
27 CYP1A2 CYP1A2 CYP1A2 1252 0.28 0.57 YES
28 GSTM3 GSTM3 GSTM3 1268 0.28 0.58 YES
29 UGT1A10 UGT1A10 UGT1A10 1438 0.26 0.59 YES
30 MGST2 MGST2 MGST2 1549 0.25 0.6 YES
31 CYP2C18 CYP2C18 CYP2C18 1564 0.25 0.61 YES
32 GSTA2 GSTA2 GSTA2 1592 0.24 0.62 YES
33 UGT2B4 UGT2B4 UGT2B4 1597 0.24 0.64 YES
34 ADH4 ADH4 ADH4 1713 0.23 0.64 YES
35 UGT1A8 UGT1A8 UGT1A8 1917 0.21 0.64 YES
36 ALDH3B2 ALDH3B2 ALDH3B2 1995 0.21 0.65 YES
37 MGST1 MGST1 MGST1 2409 0.18 0.64 NO
38 GSTM1 GSTM1 GSTM1 2894 0.15 0.62 NO
39 GSTO2 GSTO2 GSTO2 3026 0.14 0.62 NO
40 ADH1A ADH1A ADH1A 3706 0.11 0.59 NO
41 CYP2B6 CYP2B6 CYP2B6 4695 0.082 0.54 NO
42 GSTK1 GSTK1 GSTK1 5580 0.06 0.5 NO
43 GSTZ1 GSTZ1 GSTZ1 5772 0.056 0.49 NO
44 GSTT1 GSTT1 GSTT1 6385 0.043 0.46 NO
45 ADH7 ADH7 ADH7 6742 0.036 0.44 NO
46 UGT1A7 UGT1A7 UGT1A7 6763 0.035 0.44 NO
47 MGST3 MGST3 MGST3 6837 0.034 0.44 NO
48 UGT2A1 UGT2A1 UGT2A1 7310 0.025 0.41 NO
49 CYP2E1 CYP2E1 CYP2E1 7502 0.021 0.4 NO
50 ADH5 ADH5 ADH5 7534 0.021 0.4 NO
51 FMO4 FMO4 FMO4 8578 0.0018 0.34 NO
52 ADH1B ADH1B ADH1B 8596 0.0015 0.34 NO
53 CYP2A6 CYP2A6 CYP2A6 8619 0.00096 0.34 NO
54 GSTT2 GSTT2 GSTT2 9094 -0.0074 0.32 NO
55 GSTP1 GSTP1 GSTP1 9623 -0.017 0.29 NO
56 ALDH3A1 ALDH3A1 ALDH3A1 10050 -0.024 0.27 NO
57 GSTO1 GSTO1 GSTO1 12133 -0.071 0.16 NO
58 ALDH3B1 ALDH3B1 ALDH3B1 12363 -0.077 0.15 NO
59 GSTA4 GSTA4 GSTA4 13952 -0.14 0.068 NO
60 ALDH1A3 ALDH1A3 ALDH1A3 14609 -0.17 0.042 NO
61 GSTM5 GSTM5 GSTM5 14772 -0.18 0.043 NO
62 FMO3 FMO3 FMO3 15097 -0.21 0.037 NO
63 AOX1 AOX1 AOX1 17492 -0.49 -0.067 NO
64 MAOB MAOB MAOB 17604 -0.52 -0.044 NO
65 FMO2 FMO2 FMO2 17868 -0.6 -0.025 NO
66 FMO1 FMO1 FMO1 18153 -0.77 0.0024 NO

Figure S29.  Get High-res Image This plot shows mRNAseq_cNMF expression data heatmap (on the left) a RunningEnrichmentScore(RES) plot (on the top right) and a Signal2Noise(S2N) plot (on the bottom right) of genes in the pathway: KEGG VALINE LEUCINE AND ISOLEUCINE DEGRADATION.

Figure S30.  Get High-res Image For the top 5 core enriched genes in the pathway: KEGG VALINE LEUCINE AND ISOLEUCINE DEGRADATION, this volcano plot shows how much they are up/down-regulated and significant. The significance was calculated by empirical bayesian fit

genes ES table in pathway: KEGG TYROSINE METABOLISM

Table S16.  Get Full Table This table shows a Running Enrichment Score (RES) of each gene in this pathway, that is, the enrichment score at this point in the ranked list of genes. All genes are ranked by Signal-to-Noise (S2N), a measure of similarity as default and are used to obtain ES matrix of all genes. In this way, GSEA tool uses expression pattern of not only overlapped genes but also not-overlapped genes to produce ES matrix.

Rank GENE SYMBOL DESC LIST.LOC S2N RES CORE_ENRICHMENT
1 HSD17B2 HSD17B2 HSD17B2 47 0.74 0.048 YES
2 UGT1A1 UGT1A1 UGT1A1 63 0.69 0.095 YES
3 UGT2B28 UGT2B28 UGT2B28 101 0.62 0.14 YES
4 CYP3A5 CYP3A5 CYP3A5 103 0.62 0.18 YES
5 UGT1A9 UGT1A9 UGT1A9 228 0.53 0.21 YES
6 UGT2B15 UGT2B15 UGT2B15 292 0.49 0.24 YES
7 UGT1A6 UGT1A6 UGT1A6 328 0.47 0.27 YES
8 UGT2B11 UGT2B11 UGT2B11 386 0.45 0.3 YES
9 UGT1A3 UGT1A3 UGT1A3 484 0.42 0.32 YES
10 AKR1C2 AKR1C2 AKR1C2 514 0.41 0.35 YES
11 UGT2B7 UGT2B7 UGT2B7 650 0.38 0.37 YES
12 CYP3A7 CYP3A7 CYP3A7 732 0.36 0.39 YES
13 AKR1C3 AKR1C3 AKR1C3 780 0.35 0.41 YES
14 CYP1A1 CYP1A1 CYP1A1 844 0.34 0.43 YES
15 UGT1A4 UGT1A4 UGT1A4 871 0.34 0.45 YES
16 UGT2A3 UGT2A3 UGT2A3 899 0.33 0.48 YES
17 UGT2B10 UGT2B10 UGT2B10 923 0.33 0.5 YES
18 UGT1A5 UGT1A5 UGT1A5 1105 0.3 0.51 YES
19 CYP3A43 CYP3A43 CYP3A43 1123 0.3 0.53 YES
20 HSD11B2 HSD11B2 HSD11B2 1159 0.29 0.54 YES
21 SULT1E1 SULT1E1 SULT1E1 1191 0.29 0.56 YES
22 UGT1A10 UGT1A10 UGT1A10 1438 0.26 0.57 YES
23 AKR1C1 AKR1C1 AKR1C1 1475 0.26 0.58 YES
24 SRD5A2 SRD5A2 SRD5A2 1499 0.25 0.6 YES
25 UGT2B4 UGT2B4 UGT2B4 1597 0.24 0.61 YES
26 UGT1A8 UGT1A8 UGT1A8 1917 0.21 0.61 YES
27 COMT COMT COMT 2052 0.2 0.61 YES
28 HSD3B1 HSD3B1 HSD3B1 2163 0.2 0.62 YES
29 AKR1D1 AKR1D1 AKR1D1 2249 0.19 0.63 YES
30 AKR1C4 AKR1C4 AKR1C4 2512 0.17 0.63 NO
31 HSD17B7 HSD17B7 HSD17B7 2801 0.16 0.62 NO
32 STS STS STS 3160 0.14 0.61 NO
33 HSD3B2 HSD3B2 HSD3B2 4411 0.091 0.55 NO
34 SRD5A3 SRD5A3 SRD5A3 5544 0.061 0.49 NO
35 HSD17B8 HSD17B8 HSD17B8 6153 0.047 0.46 NO
36 UGT1A7 UGT1A7 UGT1A7 6763 0.035 0.43 NO
37 UGT2A1 UGT2A1 UGT2A1 7310 0.025 0.4 NO
38 HSD17B1 HSD17B1 HSD17B1 7396 0.023 0.4 NO
39 CYP11A1 CYP11A1 CYP11A1 8956 -0.0049 0.31 NO
40 CYP7A1 CYP7A1 CYP7A1 9287 -0.011 0.3 NO
41 CYP17A1 CYP17A1 CYP17A1 12075 -0.069 0.15 NO
42 HSD17B12 HSD17B12 HSD17B12 12735 -0.088 0.12 NO
43 HSD17B3 HSD17B3 HSD17B3 14109 -0.15 0.051 NO
44 CYP21A2 CYP21A2 CYP21A2 15696 -0.26 -0.019 NO
45 SRD5A1 SRD5A1 SRD5A1 15753 -0.26 -0.0039 NO
46 SULT2B1 SULT2B1 SULT2B1 15873 -0.27 0.0085 NO
47 CYP7B1 CYP7B1 CYP7B1 16154 -0.3 0.014 NO
48 CYP19A1 CYP19A1 CYP19A1 16281 -0.31 0.029 NO
49 CYP1B1 CYP1B1 CYP1B1 16545 -0.34 0.038 NO
50 HSD11B1 HSD11B1 HSD11B1 16812 -0.38 0.05 NO
51 HSD17B6 HSD17B6 HSD17B6 16847 -0.38 0.074 NO

Figure S31.  Get High-res Image This plot shows mRNAseq_cNMF expression data heatmap (on the left) a RunningEnrichmentScore(RES) plot (on the top right) and a Signal2Noise(S2N) plot (on the bottom right) of genes in the pathway: KEGG TYROSINE METABOLISM.

Figure S32.  Get High-res Image For the top 5 core enriched genes in the pathway: KEGG TYROSINE METABOLISM, this volcano plot shows how much they are up/down-regulated and significant. The significance was calculated by empirical bayesian fit

genes ES table in pathway: KEGG GLUTATHIONE METABOLISM

Table S17.  Get Full Table This table shows a Running Enrichment Score (RES) of each gene in this pathway, that is, the enrichment score at this point in the ranked list of genes. All genes are ranked by Signal-to-Noise (S2N), a measure of similarity as default and are used to obtain ES matrix of all genes. In this way, GSEA tool uses expression pattern of not only overlapped genes but also not-overlapped genes to produce ES matrix.

Rank GENE SYMBOL DESC LIST.LOC S2N RES CORE_ENRICHMENT
1 UGT1A1 UGT1A1 UGT1A1 63 0.69 0.061 YES
2 UGT2B28 UGT2B28 UGT2B28 101 0.62 0.12 YES
3 UGT1A9 UGT1A9 UGT1A9 228 0.53 0.16 YES
4 UGT2B15 UGT2B15 UGT2B15 292 0.49 0.2 YES
5 UGT1A6 UGT1A6 UGT1A6 328 0.47 0.24 YES
6 UGT2B11 UGT2B11 UGT2B11 386 0.45 0.28 YES
7 UGT1A3 UGT1A3 UGT1A3 484 0.42 0.32 YES
8 UGT2B7 UGT2B7 UGT2B7 650 0.38 0.34 YES
9 AMY2B AMY2B AMY2B 832 0.34 0.36 YES
10 UGT1A4 UGT1A4 UGT1A4 871 0.34 0.39 YES
11 UGT2A3 UGT2A3 UGT2A3 899 0.33 0.42 YES
12 UGT2B10 UGT2B10 UGT2B10 923 0.33 0.45 YES
13 UGT1A5 UGT1A5 UGT1A5 1105 0.3 0.47 YES
14 G6PC G6PC G6PC 1218 0.28 0.49 YES
15 TREH TREH TREH 1226 0.28 0.52 YES
16 UGT1A10 UGT1A10 UGT1A10 1438 0.26 0.53 YES
17 UGT2B4 UGT2B4 UGT2B4 1597 0.24 0.54 YES
18 UGT1A8 UGT1A8 UGT1A8 1917 0.21 0.54 YES
19 AMY2A AMY2A AMY2A 2327 0.18 0.54 YES
20 GYS2 GYS2 GYS2 2400 0.18 0.55 YES
21 AGL AGL AGL 5292 0.067 0.4 NO
22 PGM2 PGM2 PGM2 6183 0.046 0.35 NO
23 GYS1 GYS1 GYS1 6347 0.043 0.35 NO
24 UGT1A7 UGT1A7 UGT1A7 6763 0.035 0.33 NO
25 HK2 HK2 HK2 6836 0.034 0.33 NO
26 GBA3 GBA3 GBA3 6838 0.034 0.33 NO
27 UGT2A1 UGT2A1 UGT2A1 7310 0.025 0.31 NO
28 UGDH UGDH UGDH 8023 0.012 0.27 NO
29 GUSB GUSB GUSB 8231 0.0079 0.26 NO
30 GAA GAA GAA 9685 -0.018 0.18 NO
31 GPI GPI GPI 10095 -0.025 0.16 NO
32 GCK GCK GCK 10971 -0.043 0.12 NO
33 AMY1A AMY1A AMY1A 11269 -0.05 0.1 NO
34 HK1 HK1 HK1 11431 -0.053 0.1 NO
35 UGP2 UGP2 UGP2 12190 -0.072 0.065 NO
36 GANC GANC GANC 12690 -0.086 0.046 NO
37 MGAM MGAM MGAM 13566 -0.12 0.0084 NO
38 PYGL PYGL PYGL 13898 -0.13 0.0026 NO
39 PYGM PYGM PYGM 14055 -0.14 0.0072 NO
40 GBE1 GBE1 GBE1 14131 -0.15 0.017 NO
41 PYGB PYGB PYGB 14462 -0.16 0.014 NO
42 PGM1 PGM1 PGM1 15840 -0.27 -0.037 NO
43 ENPP3 ENPP3 ENPP3 16187 -0.3 -0.028 NO
44 PGM2L1 PGM2L1 PGM2L1 16333 -0.32 -0.006 NO
45 ENPP1 ENPP1 ENPP1 16945 -0.4 -0.0028 NO
46 HK3 HK3 HK3 18159 -0.77 0.0021 NO

Figure S33.  Get High-res Image This plot shows mRNAseq_cNMF expression data heatmap (on the left) a RunningEnrichmentScore(RES) plot (on the top right) and a Signal2Noise(S2N) plot (on the bottom right) of genes in the pathway: KEGG GLUTATHIONE METABOLISM.

Figure S34.  Get High-res Image For the top 5 core enriched genes in the pathway: KEGG GLUTATHIONE METABOLISM, this volcano plot shows how much they are up/down-regulated and significant. The significance was calculated by empirical bayesian fit

genes ES table in pathway: KEGG STARCH AND SUCROSE METABOLISM

Table S18.  Get Full Table This table shows a Running Enrichment Score (RES) of each gene in this pathway, that is, the enrichment score at this point in the ranked list of genes. All genes are ranked by Signal-to-Noise (S2N), a measure of similarity as default and are used to obtain ES matrix of all genes. In this way, GSEA tool uses expression pattern of not only overlapped genes but also not-overlapped genes to produce ES matrix.

Rank GENE SYMBOL DESC LIST.LOC S2N RES CORE_ENRICHMENT
1 UGT1A1 UGT1A1 UGT1A1 63 0.69 0.057 YES
2 UGT2B28 UGT2B28 UGT2B28 101 0.62 0.11 YES
3 CYP3A5 CYP3A5 CYP3A5 103 0.62 0.16 YES
4 UGT1A9 UGT1A9 UGT1A9 228 0.53 0.2 YES
5 UGT2B15 UGT2B15 UGT2B15 292 0.49 0.24 YES
6 UGT1A6 UGT1A6 UGT1A6 328 0.47 0.28 YES
7 UGT2B11 UGT2B11 UGT2B11 386 0.45 0.32 YES
8 UGT1A3 UGT1A3 UGT1A3 484 0.42 0.35 YES
9 UGT2B7 UGT2B7 UGT2B7 650 0.38 0.38 YES
10 CYP3A7 CYP3A7 CYP3A7 732 0.36 0.4 YES
11 UGT1A4 UGT1A4 UGT1A4 871 0.34 0.42 YES
12 UGT2A3 UGT2A3 UGT2A3 899 0.33 0.45 YES
13 UGT2B10 UGT2B10 UGT2B10 923 0.33 0.48 YES
14 UGT1A5 UGT1A5 UGT1A5 1105 0.3 0.5 YES
15 CYP3A43 CYP3A43 CYP3A43 1123 0.3 0.52 YES
16 UGT1A10 UGT1A10 UGT1A10 1438 0.26 0.53 YES
17 UGT2B4 UGT2B4 UGT2B4 1597 0.24 0.54 YES
18 UGT1A8 UGT1A8 UGT1A8 1917 0.21 0.54 YES
19 NAT1 NAT1 NAT1 2347 0.18 0.53 NO
20 UPP2 UPP2 UPP2 4408 0.091 0.43 NO
21 UCKL1 UCKL1 UCKL1 5095 0.072 0.39 NO
22 NAT2 NAT2 NAT2 6093 0.048 0.34 NO
23 UGT1A7 UGT1A7 UGT1A7 6763 0.035 0.31 NO
24 UGT2A1 UGT2A1 UGT2A1 7310 0.025 0.28 NO
25 IMPDH2 IMPDH2 IMPDH2 7598 0.02 0.27 NO
26 ITPA ITPA ITPA 8157 0.0092 0.24 NO
27 GUSB GUSB GUSB 8231 0.0079 0.24 NO
28 CYP2A6 CYP2A6 CYP2A6 8619 0.00096 0.21 NO
29 TK2 TK2 TK2 9381 -0.012 0.17 NO
30 UMPS UMPS UMPS 9409 -0.013 0.17 NO
31 TPMT TPMT TPMT 10558 -0.034 0.11 NO
32 UCK1 UCK1 UCK1 11295 -0.05 0.076 NO
33 UPB1 UPB1 UPB1 11850 -0.063 0.051 NO
34 CES2 CES2 CES2 11870 -0.064 0.055 NO
35 HPRT1 HPRT1 HPRT1 12298 -0.075 0.038 NO
36 UCK2 UCK2 UCK2 12446 -0.079 0.037 NO
37 XDH XDH XDH 13344 -0.11 -0.0026 NO
38 UPP1 UPP1 UPP1 13809 -0.13 -0.017 NO
39 GMPS GMPS GMPS 13959 -0.14 -0.013 NO
40 TK1 TK1 TK1 14077 -0.14 -0.0068 NO
41 IMPDH1 IMPDH1 IMPDH1 15010 -0.2 -0.041 NO
42 DPYS DPYS DPYS 15760 -0.26 -0.059 NO
43 CES1 CES1 CES1 16818 -0.38 -0.084 NO
44 TYMP TYMP TYMP 17638 -0.53 -0.083 NO
45 CDA CDA CDA 17903 -0.61 -0.043 NO
46 DPYD DPYD DPYD 18053 -0.68 0.0079 NO

Figure S35.  Get High-res Image This plot shows mRNAseq_cNMF expression data heatmap (on the left) a RunningEnrichmentScore(RES) plot (on the top right) and a Signal2Noise(S2N) plot (on the bottom right) of genes in the pathway: KEGG STARCH AND SUCROSE METABOLISM.

Figure S36.  Get High-res Image For the top 5 core enriched genes in the pathway: KEGG STARCH AND SUCROSE METABOLISM, this volcano plot shows how much they are up/down-regulated and significant. The significance was calculated by empirical bayesian fit

genes ES table in pathway: KEGG GLYCEROPHOSPHOLIPID METABOLISM

Table S19.  Get Full Table This table shows a Running Enrichment Score (RES) of each gene in this pathway, that is, the enrichment score at this point in the ranked list of genes. All genes are ranked by Signal-to-Noise (S2N), a measure of similarity as default and are used to obtain ES matrix of all genes. In this way, GSEA tool uses expression pattern of not only overlapped genes but also not-overlapped genes to produce ES matrix.

Rank GENE SYMBOL DESC LIST.LOC S2N RES CORE_ENRICHMENT
1 SLC27A2 SLC27A2 SLC27A2 419 0.44 0.023 YES
2 ACSL5 ACSL5 ACSL5 682 0.37 0.047 YES
3 CROT CROT CROT 783 0.35 0.078 YES
4 PEX11G PEX11G PEX11G 946 0.32 0.1 YES
5 AMACR AMACR AMACR 1101 0.3 0.13 YES
6 IDH1 IDH1 IDH1 1156 0.29 0.15 YES
7 PEX11A PEX11A PEX11A 1310 0.27 0.17 YES
8 ACOX1 ACOX1 ACOX1 1316 0.27 0.2 YES
9 ABCD3 ABCD3 ABCD3 1588 0.24 0.21 YES
10 BAAT BAAT BAAT 1614 0.24 0.24 YES
11 ACAA1 ACAA1 ACAA1 1659 0.24 0.26 YES
12 NUDT12 NUDT12 NUDT12 2068 0.2 0.26 YES
13 DECR2 DECR2 DECR2 2641 0.16 0.24 YES
14 FAR2 FAR2 FAR2 2689 0.16 0.26 YES
15 PHYH PHYH PHYH 2854 0.15 0.26 YES
16 ACOX3 ACOX3 ACOX3 2917 0.15 0.27 YES
17 AGXT AGXT AGXT 3008 0.14 0.28 YES
18 MVK MVK MVK 3014 0.14 0.3 YES
19 ACSL1 ACSL1 ACSL1 3278 0.13 0.3 YES
20 HSD17B4 HSD17B4 HSD17B4 3424 0.12 0.3 YES
21 HMGCL HMGCL HMGCL 3475 0.12 0.31 YES
22 PEX7 PEX7 PEX7 3559 0.12 0.32 YES
23 CAT CAT CAT 3959 0.11 0.31 YES
24 PEX13 PEX13 PEX13 4175 0.098 0.31 YES
25 PEX19 PEX19 PEX19 4266 0.096 0.31 YES
26 SCP2 SCP2 SCP2 4355 0.092 0.32 YES
27 NUDT19 NUDT19 NUDT19 4416 0.091 0.32 YES
28 PXMP4 PXMP4 PXMP4 4418 0.09 0.33 YES
29 EPHX2 EPHX2 EPHX2 4528 0.087 0.34 YES
30 PEX1 PEX1 PEX1 4599 0.084 0.34 YES
31 PEX2 PEX2 PEX2 4630 0.083 0.35 YES
32 HAO2 HAO2 HAO2 4775 0.08 0.35 YES
33 MLYCD MLYCD MLYCD 4813 0.078 0.35 YES
34 MPV17L MPV17L MPV17L 4874 0.077 0.36 YES
35 PEX14 PEX14 PEX14 4902 0.076 0.36 YES
36 PAOX PAOX PAOX 5031 0.073 0.37 YES
37 PEX10 PEX10 PEX10 5097 0.071 0.37 YES
38 GSTK1 GSTK1 GSTK1 5580 0.06 0.35 NO
39 PEX12 PEX12 PEX12 5615 0.059 0.35 NO
40 ECH1 ECH1 ECH1 5632 0.059 0.36 NO
41 CRAT CRAT CRAT 5727 0.056 0.36 NO
42 FAR1 FAR1 FAR1 5732 0.056 0.36 NO
43 ACOT8 ACOT8 ACOT8 5862 0.053 0.36 NO
44 PRDX5 PRDX5 PRDX5 6018 0.05 0.36 NO
45 PMVK PMVK PMVK 6265 0.045 0.35 NO
46 PEX6 PEX6 PEX6 6295 0.044 0.35 NO
47 MPV17 MPV17 MPV17 6508 0.04 0.35 NO
48 ABCD4 ABCD4 ABCD4 6692 0.037 0.34 NO
49 SOD1 SOD1 SOD1 6786 0.035 0.34 NO
50 EHHADH EHHADH EHHADH 6951 0.032 0.33 NO
51 PEX11B PEX11B PEX11B 7442 0.022 0.31 NO
52 SLC25A17 SLC25A17 SLC25A17 7602 0.019 0.3 NO
53 HACL1 HACL1 HACL1 7957 0.013 0.28 NO
54 PEX16 PEX16 PEX16 8184 0.0086 0.27 NO
55 ABCD1 ABCD1 ABCD1 8405 0.0048 0.26 NO
56 ACSL3 ACSL3 ACSL3 8878 -0.0038 0.24 NO
57 IDH2 IDH2 IDH2 9441 -0.013 0.2 NO
58 GNPAT GNPAT GNPAT 9911 -0.022 0.18 NO
59 ACSL4 ACSL4 ACSL4 10149 -0.026 0.17 NO
60 DHRS4 DHRS4 DHRS4 10413 -0.031 0.16 NO
61 PEX5 PEX5 PEX5 10483 -0.032 0.16 NO
62 PRDX1 PRDX1 PRDX1 10614 -0.035 0.16 NO
63 PEX26 PEX26 PEX26 11622 -0.057 0.11 NO
64 DAO DAO DAO 12330 -0.076 0.075 NO
65 PEX3 PEX3 PEX3 12596 -0.084 0.069 NO
66 DDO DDO DDO 12774 -0.089 0.069 NO
67 NOS2 NOS2 NOS2 12880 -0.093 0.072 NO
68 AGPS AGPS AGPS 13268 -0.11 0.062 NO
69 XDH XDH XDH 13344 -0.11 0.069 NO
70 PXMP2 PXMP2 PXMP2 14636 -0.18 0.016 NO
71 PECI PECI PECI 14986 -0.2 0.018 NO
72 PECR PECR PECR 15278 -0.22 0.025 NO
73 ACSL6 ACSL6 ACSL6 15437 -0.24 0.041 NO
74 SOD2 SOD2 SOD2 15714 -0.26 0.052 NO
75 PIPOX PIPOX PIPOX 16654 -0.36 0.038 NO
76 ABCD2 ABCD2 ABCD2 17292 -0.46 0.05 NO

Figure S37.  Get High-res Image This plot shows mRNAseq_cNMF expression data heatmap (on the left) a RunningEnrichmentScore(RES) plot (on the top right) and a Signal2Noise(S2N) plot (on the bottom right) of genes in the pathway: KEGG GLYCEROPHOSPHOLIPID METABOLISM.

Figure S38.  Get High-res Image For the top 5 core enriched genes in the pathway: KEGG GLYCEROPHOSPHOLIPID METABOLISM, this volcano plot shows how much they are up/down-regulated and significant. The significance was calculated by empirical bayesian fit

genes ES table in pathway: KEGG ETHER LIPID METABOLISM

Table S20.  Get Full Table This table shows a Running Enrichment Score (RES) of each gene in this pathway, that is, the enrichment score at this point in the ranked list of genes. All genes are ranked by Signal-to-Noise (S2N), a measure of similarity as default and are used to obtain ES matrix of all genes. In this way, GSEA tool uses expression pattern of not only overlapped genes but also not-overlapped genes to produce ES matrix.

Rank GENE SYMBOL DESC LIST.LOC S2N RES CORE_ENRICHMENT
1 ADH6 ADH6 ADH6 216 0.54 0.077 YES
2 ACSL5 ACSL5 ACSL5 682 0.37 0.11 YES
3 CYP4A11 CYP4A11 CYP4A11 816 0.35 0.16 YES
4 ACADSB ACADSB ACADSB 1086 0.3 0.2 YES
5 ADH1C ADH1C ADH1C 1174 0.29 0.24 YES
6 CYP4A22 CYP4A22 CYP4A22 1602 0.24 0.26 YES
7 ACAA1 ACAA1 ACAA1 1659 0.24 0.29 YES
8 CPT1B CPT1B CPT1B 1712 0.23 0.33 YES
9 ADH4 ADH4 ADH4 1713 0.23 0.37 YES
10 ACADL ACADL ACADL 2376 0.18 0.36 YES
11 ACOX3 ACOX3 ACOX3 2917 0.15 0.36 YES
12 HADH HADH HADH 2978 0.15 0.38 YES
13 ACSL1 ACSL1 ACSL1 3278 0.13 0.38 YES
14 DCI DCI DCI 3641 0.12 0.38 YES
15 ADH1A ADH1A ADH1A 3706 0.11 0.4 YES
16 ACADVL ACADVL ACADVL 3850 0.11 0.41 YES
17 ACADS ACADS ACADS 3968 0.1 0.42 YES
18 ECHS1 ECHS1 ECHS1 4174 0.098 0.42 YES
19 HADHB HADHB HADHB 4409 0.091 0.42 YES
20 GCDH GCDH GCDH 5406 0.064 0.38 NO
21 CPT2 CPT2 CPT2 5657 0.058 0.38 NO
22 ACADM ACADM ACADM 6011 0.05 0.36 NO
23 ADH7 ADH7 ADH7 6742 0.036 0.33 NO
24 EHHADH EHHADH EHHADH 6951 0.032 0.32 NO
25 ADH5 ADH5 ADH5 7534 0.021 0.3 NO
26 ACAT2 ACAT2 ACAT2 7612 0.019 0.3 NO
27 HADHA HADHA HADHA 8445 0.0041 0.25 NO
28 ALDH9A1 ALDH9A1 ALDH9A1 8452 0.0038 0.25 NO
29 ADH1B ADH1B ADH1B 8596 0.0015 0.24 NO
30 ACSL3 ACSL3 ACSL3 8878 -0.0038 0.23 NO
31 CPT1A CPT1A CPT1A 9865 -0.02 0.18 NO
32 ACSL4 ACSL4 ACSL4 10149 -0.026 0.16 NO
33 ACAA2 ACAA2 ACAA2 12662 -0.086 0.041 NO
34 ALDH7A1 ALDH7A1 ALDH7A1 13256 -0.11 0.026 NO
35 ALDH3A2 ALDH3A2 ALDH3A2 13591 -0.12 0.027 NO
36 CPT1C CPT1C CPT1C 14087 -0.14 0.024 NO
37 PECI PECI PECI 14986 -0.2 0.0075 NO
38 ALDH1B1 ALDH1B1 ALDH1B1 15220 -0.22 0.031 NO
39 ACAT1 ACAT1 ACAT1 15414 -0.23 0.059 NO
40 ACSL6 ACSL6 ACSL6 15437 -0.24 0.097 NO
41 ALDH2 ALDH2 ALDH2 16477 -0.34 0.095 NO

Figure S39.  Get High-res Image This plot shows mRNAseq_cNMF expression data heatmap (on the left) a RunningEnrichmentScore(RES) plot (on the top right) and a Signal2Noise(S2N) plot (on the bottom right) of genes in the pathway: KEGG ETHER LIPID METABOLISM.

Figure S40.  Get High-res Image For the top 5 core enriched genes in the pathway: KEGG ETHER LIPID METABOLISM, this volcano plot shows how much they are up/down-regulated and significant. The significance was calculated by empirical bayesian fit

Fold change

For the top enriched genes, if you want to check whether they are

Expression level

For the top enriched genes, if you want to check whether they are

An expression pattern of top(30%)/middle(30%)/low(30%) in this subtype against other subtypes is available in a heatmap

Significant gene list

For the top enriched genes, if you want to check whether they are

Subtype clus3 enriched pathways

Table 5.  Get Full Table This table shows top 10 pathways which are significantly enriched in cluster clus3. It displays only significant gene sets satisfying nom.p.val.threshold (-1), fwer.p.val.threshold (-1) , fdr.q.val.threshold (0.25) and the default table is sorted by Normalized Enrichment Score (NES). Further details on NES statistics, please visit The Broad GSEA website.

GeneSet(GS) Size(#genes) genes.ES.table ES NES NOM.p.val FDR.q.val FWER.p.val Tag.. Gene.. Signal FDR..median. glob.p.val
BIOCARTA G1 PATHWAY 27 genes.ES.table 0.58 1.7 0.0096 0.17 0.44 0.41 0.19 0.33 0 0.031
BIOCARTA EGF PATHWAY 30 genes.ES.table 0.49 1.5 0.084 0.29 0.85 0.3 0.16 0.25 0.19 0.037
BIOCARTA FAS PATHWAY 29 genes.ES.table 0.49 1.6 0.062 0.23 0.68 0.45 0.21 0.36 0.13 0.035
BIOCARTA RACCYCD PATHWAY 25 genes.ES.table 0.49 1.8 0.019 0.52 0.25 0.32 0.2 0.26 0 0.17
BIOCARTA MAPK PATHWAY 86 genes.ES.table 0.35 1.6 0.046 0.23 0.76 0.37 0.23 0.29 0.14 0.029
BIOCARTA P38MAPK PATHWAY 39 genes.ES.table 0.47 1.6 0.029 0.22 0.69 0.64 0.33 0.43 0.13 0.029
BIOCARTA IL1R PATHWAY 32 genes.ES.table 0.57 1.6 0.045 0.24 0.76 0.53 0.2 0.43 0.15 0.034
BIOCARTA TNFR1 PATHWAY 28 genes.ES.table 0.47 1.7 0.026 0.15 0.46 0.43 0.21 0.34 0 0.022
KEGG PYRIMIDINE METABOLISM 96 genes.ES.table 0.4 1.8 0.0057 0.17 0.35 0.3 0.2 0.24 0 0.036
KEGG AMINOACYL TRNA BIOSYNTHESIS 40 genes.ES.table 0.45 1.8 0.039 0.15 0.36 0.57 0.35 0.38 0 0.032
genes ES table in pathway: BIOCARTA G1 PATHWAY

Table S21.  Get Full Table This table shows a Running Enrichment Score (RES) of each gene in this pathway, that is, the enrichment score at this point in the ranked list of genes. All genes are ranked by Signal-to-Noise (S2N), a measure of similarity as default and are used to obtain ES matrix of all genes. In this way, GSEA tool uses expression pattern of not only overlapped genes but also not-overlapped genes to produce ES matrix.

Rank GENE SYMBOL DESC LIST.LOC S2N RES CORE_ENRICHMENT
1 CDK6 CDK6 CDK6 104 0.59 0.3 YES
2 TFDP1 TFDP1 TFDP1 2831 0.11 0.21 YES
3 HRAS HRAS HRAS 2833 0.11 0.27 YES
4 PIK3CA PIK3CA PIK3CA 2896 0.11 0.32 YES
5 PAK1 PAK1 PAK1 3075 0.1 0.36 YES
6 CDKN1A CDKN1A CDKN1A 3142 0.1 0.41 YES
7 NFKB1 NFKB1 NFKB1 3262 0.096 0.46 YES
8 CHUK CHUK CHUK 3546 0.087 0.49 YES
9 MAPK1 MAPK1 MAPK1 4964 0.053 0.44 NO
10 IKBKG IKBKG IKBKG 5015 0.052 0.46 NO
11 RAC1 RAC1 RAC1 5759 0.038 0.44 NO
12 RB1 RB1 RB1 6335 0.027 0.42 NO
13 CDK4 CDK4 CDK4 6378 0.026 0.43 NO
14 CCND1 CCND1 CCND1 7008 0.016 0.41 NO
15 AKT1 AKT1 AKT1 7737 0.0045 0.37 NO
16 CDK2 CDK2 CDK2 8228 -0.0032 0.34 NO
17 RHOA RHOA RHOA 8234 -0.0033 0.35 NO
18 NFKBIA NFKBIA NFKBIA 8271 -0.004 0.35 NO
19 RELA RELA RELA 8584 -0.009 0.33 NO
20 MAPK3 MAPK3 MAPK3 8962 -0.015 0.32 NO
21 CDKN1B CDKN1B CDKN1B 10608 -0.044 0.25 NO
22 CCNE1 CCNE1 CCNE1 10902 -0.05 0.26 NO
23 PIK3R1 PIK3R1 PIK3R1 11962 -0.073 0.24 NO
24 RAF1 RAF1 RAF1 11996 -0.074 0.28 NO
25 IKBKB IKBKB IKBKB 13436 -0.12 0.26 NO

Figure S41.  Get High-res Image This plot shows mRNAseq_cNMF expression data heatmap (on the left) a RunningEnrichmentScore(RES) plot (on the top right) and a Signal2Noise(S2N) plot (on the bottom right) of genes in the pathway: BIOCARTA G1 PATHWAY.

Figure S42.  Get High-res Image For the top 5 core enriched genes in the pathway: BIOCARTA G1 PATHWAY, this volcano plot shows how much they are up/down-regulated and significant. The significance was calculated by empirical bayesian fit

genes ES table in pathway: BIOCARTA EGF PATHWAY

Table S22.  Get Full Table This table shows a Running Enrichment Score (RES) of each gene in this pathway, that is, the enrichment score at this point in the ranked list of genes. All genes are ranked by Signal-to-Noise (S2N), a measure of similarity as default and are used to obtain ES matrix of all genes. In this way, GSEA tool uses expression pattern of not only overlapped genes but also not-overlapped genes to produce ES matrix.

Rank GENE SYMBOL DESC LIST.LOC S2N RES CORE_ENRICHMENT
1 CDK6 CDK6 CDK6 104 0.59 0.041 YES
2 MYC MYC MYC 327 0.4 0.061 YES
3 SFN SFN SFN 377 0.38 0.088 YES
4 ORC1L ORC1L ORC1L 539 0.33 0.11 YES
5 CCNA1 CCNA1 CCNA1 558 0.32 0.13 YES
6 CDC25B CDC25B CDC25B 674 0.3 0.15 YES
7 CCNE2 CCNE2 CCNE2 713 0.29 0.17 YES
8 PTTG1 PTTG1 PTTG1 927 0.25 0.18 YES
9 TGFB2 TGFB2 TGFB2 931 0.25 0.2 YES
10 PKMYT1 PKMYT1 PKMYT1 945 0.25 0.22 YES
11 CCNA2 CCNA2 CCNA2 995 0.24 0.23 YES
12 PLK1 PLK1 PLK1 1041 0.24 0.25 YES
13 E2F2 E2F2 E2F2 1139 0.23 0.26 YES
14 CCNB1 CCNB1 CCNB1 1216 0.22 0.28 YES
15 MAD2L1 MAD2L1 MAD2L1 1231 0.22 0.29 YES
16 CDC20 CDC20 CDC20 1260 0.21 0.31 YES
17 TTK TTK TTK 1379 0.2 0.32 YES
18 CCNB2 CCNB2 CCNB2 1393 0.2 0.33 YES
19 BUB1B BUB1B BUB1B 1482 0.19 0.34 YES
20 RBL1 RBL1 RBL1 1556 0.18 0.35 YES
21 CDC45 CDC45 CDC45 1775 0.17 0.35 YES
22 MCM4 MCM4 MCM4 1997 0.15 0.35 YES
23 CDK1 CDK1 CDK1 2000 0.15 0.37 YES
24 BUB1 BUB1 BUB1 2134 0.15 0.37 YES
25 CHEK1 CHEK1 CHEK1 2170 0.14 0.38 YES
26 MCM2 MCM2 MCM2 2295 0.14 0.38 YES
27 CDC25C CDC25C CDC25C 2297 0.14 0.4 YES
28 YWHAQ YWHAQ YWHAQ 2538 0.12 0.39 YES
29 PRKDC PRKDC PRKDC 2587 0.12 0.4 YES
30 TGFB1 TGFB1 TGFB1 2610 0.12 0.41 YES
31 STAG1 STAG1 STAG1 2740 0.12 0.41 YES
32 MCM6 MCM6 MCM6 2777 0.12 0.42 YES
33 TFDP1 TFDP1 TFDP1 2831 0.11 0.42 YES
34 ESPL1 ESPL1 ESPL1 3005 0.11 0.42 YES
35 CDC7 CDC7 CDC7 3054 0.1 0.43 YES
36 YWHAG YWHAG YWHAG 3140 0.1 0.43 YES
37 CDKN1A CDKN1A CDKN1A 3142 0.1 0.44 YES
38 TGFB3 TGFB3 TGFB3 3207 0.098 0.44 YES
39 SMC3 SMC3 SMC3 3208 0.098 0.45 YES
40 CDC25A CDC25A CDC25A 3216 0.098 0.46 YES
41 SMC1A SMC1A SMC1A 3275 0.096 0.46 YES
42 CDKN2B CDKN2B CDKN2B 3341 0.093 0.47 YES
43 GADD45A GADD45A GADD45A 3364 0.092 0.47 YES
44 SKP2 SKP2 SKP2 3391 0.092 0.48 YES
45 ANAPC10 ANAPC10 ANAPC10 3575 0.086 0.48 YES
46 CDK7 CDK7 CDK7 3585 0.086 0.48 YES
47 CDC6 CDC6 CDC6 3604 0.085 0.49 YES
48 ORC5L ORC5L ORC5L 3636 0.084 0.49 YES
49 MAD2L2 MAD2L2 MAD2L2 3670 0.083 0.5 YES
50 ORC6L ORC6L ORC6L 3732 0.082 0.5 YES
51 ANAPC1 ANAPC1 ANAPC1 3980 0.075 0.49 YES
52 PCNA PCNA PCNA 4013 0.074 0.5 YES
53 CDC27 CDC27 CDC27 4091 0.072 0.5 YES
54 YWHAH YWHAH YWHAH 4152 0.071 0.5 YES
55 STAG2 STAG2 STAG2 4272 0.068 0.5 YES
56 CDKN2A CDKN2A CDKN2A 4414 0.064 0.5 YES
57 ORC2L ORC2L ORC2L 4497 0.062 0.5 YES
58 CDC23 CDC23 CDC23 4606 0.06 0.5 YES
59 MCM5 MCM5 MCM5 4627 0.059 0.5 YES
60 TFDP2 TFDP2 TFDP2 4650 0.059 0.5 YES
61 YWHAZ YWHAZ YWHAZ 4990 0.052 0.49 NO
62 RAD21 RAD21 RAD21 5239 0.047 0.48 NO
63 MCM7 MCM7 MCM7 5264 0.046 0.48 NO
64 ATR ATR ATR 5524 0.042 0.47 NO
65 ORC3L ORC3L ORC3L 5796 0.037 0.46 NO
66 BUB3 BUB3 BUB3 5843 0.036 0.46 NO
67 CDKN2D CDKN2D CDKN2D 5861 0.035 0.46 NO
68 GSK3B GSK3B GSK3B 5885 0.035 0.46 NO
69 E2F1 E2F1 E2F1 5923 0.034 0.46 NO
70 CUL1 CUL1 CUL1 5958 0.034 0.46 NO
71 CDC26 CDC26 CDC26 6044 0.032 0.46 NO
72 CDKN2C CDKN2C CDKN2C 6086 0.032 0.46 NO
73 CCND3 CCND3 CCND3 6179 0.03 0.46 NO
74 RB1 RB1 RB1 6335 0.027 0.45 NO
75 CDK4 CDK4 CDK4 6378 0.026 0.45 NO
76 ORC4L ORC4L ORC4L 6380 0.026 0.45 NO
77 SMAD2 SMAD2 SMAD2 6912 0.018 0.42 NO
78 ABL1 ABL1 ABL1 6917 0.017 0.43 NO
79 CCND1 CCND1 CCND1 7008 0.016 0.42 NO
80 E2F4 E2F4 E2F4 7080 0.015 0.42 NO
81 YWHAE YWHAE YWHAE 7193 0.013 0.42 NO
82 FZR1 FZR1 FZR1 7236 0.012 0.41 NO
83 CCNH CCNH CCNH 7412 0.0094 0.4 NO
84 HDAC2 HDAC2 HDAC2 7480 0.0084 0.4 NO
85 SMAD3 SMAD3 SMAD3 7593 0.0067 0.4 NO
86 HDAC1 HDAC1 HDAC1 7625 0.0063 0.4 NO
87 WEE2 WEE2 WEE2 7657 0.0058 0.39 NO
88 ANAPC5 ANAPC5 ANAPC5 7684 0.0054 0.39 NO
89 CCND2 CCND2 CCND2 7792 0.0038 0.39 NO
90 SKP1 SKP1 SKP1 7803 0.0036 0.39 NO
91 MAD1L1 MAD1L1 MAD1L1 7827 0.0032 0.39 NO
92 YWHAB YWHAB YWHAB 7858 0.0027 0.38 NO
93 WEE1 WEE1 WEE1 8036 -0.000071 0.37 NO
94 ANAPC7 ANAPC7 ANAPC7 8077 -0.001 0.37 NO
95 CREBBP CREBBP CREBBP 8147 -0.002 0.37 NO
96 CDK2 CDK2 CDK2 8228 -0.0032 0.36 NO
97 MCM3 MCM3 MCM3 8246 -0.0035 0.36 NO
98 E2F3 E2F3 E2F3 8638 -0.0097 0.34 NO
99 CHEK2 CHEK2 CHEK2 8658 -0.01 0.34 NO
100 ANAPC2 ANAPC2 ANAPC2 8802 -0.012 0.34 NO
101 ANAPC13 ANAPC13 ANAPC13 8869 -0.013 0.33 NO
102 RBX1 RBX1 RBX1 9083 -0.017 0.32 NO
103 SMAD4 SMAD4 SMAD4 9756 -0.028 0.29 NO
104 SMC1B SMC1B SMC1B 10153 -0.035 0.27 NO
105 ANAPC11 ANAPC11 ANAPC11 10240 -0.037 0.27 NO
106 CDKN1B CDKN1B CDKN1B 10608 -0.044 0.25 NO
107 ZBTB17 ZBTB17 ZBTB17 10612 -0.044 0.25 NO
108 RBL2 RBL2 RBL2 10760 -0.048 0.25 NO
109 MDM2 MDM2 MDM2 10836 -0.049 0.25 NO
110 CCNE1 CCNE1 CCNE1 10902 -0.05 0.25 NO
111 CDC16 CDC16 CDC16 11061 -0.054 0.24 NO
112 EP300 EP300 EP300 11112 -0.055 0.25 NO
113 GADD45B GADD45B GADD45B 11725 -0.068 0.22 NO
114 ATM ATM ATM 12614 -0.09 0.18 NO
115 TP53 TP53 TP53 12743 -0.094 0.18 NO
116 ANAPC4 ANAPC4 ANAPC4 12977 -0.1 0.17 NO
117 CDC14B CDC14B CDC14B 13469 -0.12 0.15 NO
118 CCNB3 CCNB3 CCNB3 14531 -0.16 0.11 NO
119 GADD45G GADD45G GADD45G 14920 -0.17 0.1 NO
120 CDKN1C CDKN1C CDKN1C 16085 -0.24 0.055 NO
121 PTTG2 PTTG2 PTTG2 16244 -0.25 0.066 NO
122 E2F5 E2F5 E2F5 16284 -0.26 0.084 NO
123 CDC14A CDC14A CDC14A 16413 -0.27 0.099 NO

Figure S43.  Get High-res Image This plot shows mRNAseq_cNMF expression data heatmap (on the left) a RunningEnrichmentScore(RES) plot (on the top right) and a Signal2Noise(S2N) plot (on the bottom right) of genes in the pathway: BIOCARTA EGF PATHWAY.

Figure S44.  Get High-res Image For the top 5 core enriched genes in the pathway: BIOCARTA EGF PATHWAY, this volcano plot shows how much they are up/down-regulated and significant. The significance was calculated by empirical bayesian fit

genes ES table in pathway: BIOCARTA FAS PATHWAY

Table S23.  Get Full Table This table shows a Running Enrichment Score (RES) of each gene in this pathway, that is, the enrichment score at this point in the ranked list of genes. All genes are ranked by Signal-to-Noise (S2N), a measure of similarity as default and are used to obtain ES matrix of all genes. In this way, GSEA tool uses expression pattern of not only overlapped genes but also not-overlapped genes to produce ES matrix.

Rank GENE SYMBOL DESC LIST.LOC S2N RES CORE_ENRICHMENT
1 POLE2 POLE2 POLE2 723 0.28 0.055 YES
2 GTF2H3 GTF2H3 GTF2H3 1050 0.24 0.12 YES
3 RFC4 RFC4 RFC4 1942 0.16 0.12 YES
4 POLE3 POLE3 POLE3 2195 0.14 0.15 YES
5 MNAT1 MNAT1 MNAT1 2300 0.14 0.19 YES
6 POLD2 POLD2 POLD2 2305 0.14 0.24 YES
7 RFC3 RFC3 RFC3 2496 0.13 0.27 YES
8 GTF2H1 GTF2H1 GTF2H1 2876 0.11 0.29 YES
9 POLD1 POLD1 POLD1 3007 0.1 0.32 YES
10 ERCC6 ERCC6 ERCC6 3012 0.1 0.35 YES
11 RPA3 RPA3 RPA3 3167 0.1 0.37 YES
12 ERCC8 ERCC8 ERCC8 3393 0.092 0.39 YES
13 CDK7 CDK7 CDK7 3585 0.086 0.41 YES
14 ERCC4 ERCC4 ERCC4 3852 0.079 0.42 YES
15 PCNA PCNA PCNA 4013 0.074 0.44 YES
16 POLD3 POLD3 POLD3 4025 0.074 0.46 YES
17 RFC2 RFC2 RFC2 4193 0.07 0.48 YES
18 RPA1 RPA1 RPA1 4567 0.061 0.48 YES
19 RFC1 RFC1 RFC1 4659 0.058 0.49 YES
20 ERCC1 ERCC1 ERCC1 4705 0.058 0.51 YES
21 CUL4A CUL4A CUL4A 5666 0.039 0.47 NO
22 GTF2H4 GTF2H4 GTF2H4 5751 0.038 0.48 NO
23 RPA4 RPA4 RPA4 5752 0.038 0.49 NO
24 RFC5 RFC5 RFC5 5777 0.037 0.5 NO
25 POLE POLE POLE 6313 0.028 0.48 NO
26 DDB2 DDB2 DDB2 6336 0.027 0.49 NO
27 ERCC3 ERCC3 ERCC3 6564 0.023 0.48 NO
28 CUL4B CUL4B CUL4B 6595 0.023 0.49 NO
29 XPA XPA XPA 6671 0.021 0.49 NO
30 RAD23A RAD23A RAD23A 6691 0.021 0.5 NO
31 POLE4 POLE4 POLE4 6828 0.019 0.5 NO
32 CETN2 CETN2 CETN2 7315 0.011 0.47 NO
33 CCNH CCNH CCNH 7412 0.0094 0.47 NO
34 DDB1 DDB1 DDB1 7536 0.0075 0.46 NO
35 POLD4 POLD4 POLD4 8245 -0.0035 0.43 NO
36 LIG1 LIG1 LIG1 8452 -0.0066 0.42 NO
37 RPA2 RPA2 RPA2 8468 -0.0069 0.42 NO
38 RBX1 RBX1 RBX1 9083 -0.017 0.39 NO
39 GTF2H2 GTF2H2 GTF2H2 9190 -0.019 0.39 NO
40 GTF2H5 GTF2H5 GTF2H5 10761 -0.048 0.32 NO
41 ERCC2 ERCC2 ERCC2 11033 -0.053 0.32 NO
42 ERCC5 ERCC5 ERCC5 11783 -0.069 0.3 NO
43 XPC XPC XPC 14215 -0.14 0.22 NO

Figure S45.  Get High-res Image This plot shows mRNAseq_cNMF expression data heatmap (on the left) a RunningEnrichmentScore(RES) plot (on the top right) and a Signal2Noise(S2N) plot (on the bottom right) of genes in the pathway: BIOCARTA FAS PATHWAY.

Figure S46.  Get High-res Image For the top 5 core enriched genes in the pathway: BIOCARTA FAS PATHWAY, this volcano plot shows how much they are up/down-regulated and significant. The significance was calculated by empirical bayesian fit

genes ES table in pathway: BIOCARTA RACCYCD PATHWAY

Table S24.  Get Full Table This table shows a Running Enrichment Score (RES) of each gene in this pathway, that is, the enrichment score at this point in the ranked list of genes. All genes are ranked by Signal-to-Noise (S2N), a measure of similarity as default and are used to obtain ES matrix of all genes. In this way, GSEA tool uses expression pattern of not only overlapped genes but also not-overlapped genes to produce ES matrix.

Rank GENE SYMBOL DESC LIST.LOC S2N RES CORE_ENRICHMENT
1 PSMB9 PSMB9 PSMB9 535 0.33 0.085 YES
2 IFNG IFNG IFNG 751 0.28 0.17 YES
3 PSMB8 PSMB8 PSMB8 2401 0.13 0.13 YES
4 PSMD1 PSMD1 PSMD1 2955 0.11 0.13 YES
5 PSMD2 PSMD2 PSMD2 2958 0.11 0.17 YES
6 PSMD12 PSMD12 PSMD12 3076 0.1 0.2 YES
7 PSMD14 PSMD14 PSMD14 3096 0.1 0.24 YES
8 PSMB7 PSMB7 PSMB7 3231 0.097 0.26 YES
9 PSMD11 PSMD11 PSMD11 3233 0.097 0.3 YES
10 PSMA6 PSMA6 PSMA6 3302 0.094 0.32 YES
11 PSMB2 PSMB2 PSMB2 3428 0.09 0.35 YES
12 PSME2 PSME2 PSME2 3542 0.087 0.37 YES
13 PSMA1 PSMA1 PSMA1 3826 0.079 0.38 YES
14 PSMA2 PSMA2 PSMA2 3941 0.076 0.41 YES
15 PSMC3 PSMC3 PSMC3 4129 0.071 0.42 YES
16 PSMA3 PSMA3 PSMA3 4212 0.07 0.44 YES
17 PSMA5 PSMA5 PSMA5 4283 0.068 0.46 YES
18 PSMB5 PSMB5 PSMB5 4416 0.064 0.48 YES
19 PSMC2 PSMC2 PSMC2 4454 0.063 0.5 YES
20 PSME3 PSME3 PSME3 4613 0.059 0.51 YES
21 POMP POMP POMP 4667 0.058 0.52 YES
22 PSMB1 PSMB1 PSMB1 4744 0.057 0.54 YES
23 PSMC1 PSMC1 PSMC1 4883 0.054 0.55 YES
24 PSMA7 PSMA7 PSMA7 4918 0.054 0.57 YES
25 PSMD13 PSMD13 PSMD13 5023 0.052 0.58 YES
26 PSMA4 PSMA4 PSMA4 5256 0.047 0.58 YES
27 PSMB6 PSMB6 PSMB6 5494 0.042 0.59 YES
28 PSME4 PSME4 PSME4 5546 0.041 0.6 YES
29 PSME1 PSME1 PSME1 5862 0.035 0.59 YES
30 PSMC6 PSMC6 PSMC6 5913 0.034 0.6 YES
31 PSMD7 PSMD7 PSMD7 6374 0.026 0.59 NO
32 PSMF1 PSMF1 PSMF1 6402 0.026 0.59 NO
33 PSMD8 PSMD8 PSMD8 6478 0.025 0.6 NO
34 PSMB3 PSMB3 PSMB3 6867 0.018 0.58 NO
35 PSMD3 PSMD3 PSMD3 7045 0.015 0.58 NO
36 PSMC5 PSMC5 PSMC5 7178 0.013 0.57 NO
37 PSMD6 PSMD6 PSMD6 8058 -0.00049 0.53 NO
38 PSMB4 PSMB4 PSMB4 8470 -0.0069 0.51 NO
39 SHFM1 SHFM1 SHFM1 8770 -0.012 0.5 NO
40 PSMD4 PSMD4 PSMD4 8857 -0.013 0.49 NO
41 PSMC4 PSMC4 PSMC4 9693 -0.027 0.46 NO
42 PSMA8 PSMA8 PSMA8 9903 -0.03 0.46 NO

Figure S47.  Get High-res Image This plot shows mRNAseq_cNMF expression data heatmap (on the left) a RunningEnrichmentScore(RES) plot (on the top right) and a Signal2Noise(S2N) plot (on the bottom right) of genes in the pathway: BIOCARTA RACCYCD PATHWAY.

Figure S48.  Get High-res Image For the top 5 core enriched genes in the pathway: BIOCARTA RACCYCD PATHWAY, this volcano plot shows how much they are up/down-regulated and significant. The significance was calculated by empirical bayesian fit

genes ES table in pathway: BIOCARTA MAPK PATHWAY

Table S25.  Get Full Table This table shows a Running Enrichment Score (RES) of each gene in this pathway, that is, the enrichment score at this point in the ranked list of genes. All genes are ranked by Signal-to-Noise (S2N), a measure of similarity as default and are used to obtain ES matrix of all genes. In this way, GSEA tool uses expression pattern of not only overlapped genes but also not-overlapped genes to produce ES matrix.

Rank GENE SYMBOL DESC LIST.LOC S2N RES CORE_ENRICHMENT
1 POLR3G POLR3G POLR3G 88 0.61 0.062 YES
2 DPYD DPYD DPYD 145 0.52 0.12 YES
3 TYMP TYMP TYMP 298 0.41 0.15 YES
4 CDA CDA CDA 372 0.38 0.19 YES
5 POLE2 POLE2 POLE2 723 0.28 0.2 YES
6 NT5E NT5E NT5E 872 0.26 0.22 YES
7 RRM2 RRM2 RRM2 1037 0.24 0.24 YES
8 PNP PNP PNP 1622 0.18 0.23 YES
9 RRM1 RRM1 RRM1 1626 0.18 0.25 YES
10 CMPK2 CMPK2 CMPK2 1845 0.16 0.25 YES
11 TXNRD1 TXNRD1 TXNRD1 1881 0.16 0.27 YES
12 TK1 TK1 TK1 2077 0.15 0.27 YES
13 PRIM1 PRIM1 PRIM1 2140 0.15 0.28 YES
14 POLE3 POLE3 POLE3 2195 0.14 0.3 YES
15 POLD2 POLD2 POLD2 2305 0.14 0.31 YES
16 POLR1A POLR1A POLR1A 2386 0.13 0.32 YES
17 NT5M NT5M NT5M 2444 0.13 0.33 YES
18 TYMS TYMS TYMS 2493 0.13 0.34 YES
19 UPP1 UPP1 UPP1 2564 0.12 0.35 YES
20 NT5C1B NT5C1B NT5C1B 2727 0.12 0.35 YES
21 PRIM2 PRIM2 PRIM2 2868 0.11 0.36 YES
22 POLA1 POLA1 POLA1 2889 0.11 0.37 YES
23 POLD1 POLD1 POLD1 3007 0.1 0.37 YES
24 POLR1E POLR1E POLR1E 3238 0.097 0.37 YES
25 CAD CAD CAD 3261 0.096 0.38 YES
26 UCK2 UCK2 UCK2 3264 0.096 0.39 YES
27 POLR2D POLR2D POLR2D 3285 0.095 0.4 YES
28 POLR1B POLR1B POLR1B 3440 0.09 0.4 YES
29 POLR3D POLR3D POLR3D 3582 0.086 0.4 YES
30 POLA2 POLA2 POLA2 3829 0.079 0.4 NO
31 POLD3 POLD3 POLD3 4025 0.074 0.4 NO
32 PNPT1 PNPT1 PNPT1 4228 0.069 0.39 NO
33 UMPS UMPS UMPS 4255 0.068 0.4 NO
34 POLR3A POLR3A POLR3A 4317 0.066 0.4 NO
35 DTYMK DTYMK DTYMK 4769 0.056 0.38 NO
36 POLR3F POLR3F POLR3F 4813 0.056 0.39 NO
37 CANT1 CANT1 CANT1 4856 0.055 0.39 NO
38 DCK DCK DCK 4959 0.053 0.39 NO
39 NT5C3 NT5C3 NT5C3 5190 0.048 0.38 NO
40 CMPK1 CMPK1 CMPK1 5356 0.045 0.38 NO
41 DUT DUT DUT 5534 0.042 0.37 NO
42 NME1 NME1 NME1 5972 0.034 0.35 NO
43 POLR3B POLR3B POLR3B 6032 0.032 0.35 NO
44 NME2 NME2 NME2 6068 0.032 0.35 NO
45 POLE POLE POLE 6313 0.028 0.34 NO
46 POLR2L POLR2L POLR2L 6323 0.027 0.35 NO
47 DCTD DCTD DCTD 6428 0.025 0.34 NO
48 UCK1 UCK1 UCK1 6676 0.021 0.33 NO
49 NME1-NME2 NME1-NME2 NME1-NME2 6755 0.02 0.33 NO
50 POLE4 POLE4 POLE4 6828 0.019 0.33 NO
51 POLR3H POLR3H POLR3H 6872 0.018 0.33 NO
52 POLR2A POLR2A POLR2A 6973 0.016 0.32 NO
53 POLR2B POLR2B POLR2B 7752 0.0043 0.28 NO
54 DHODH DHODH DHODH 7794 0.0037 0.28 NO
55 POLR3C POLR3C POLR3C 7915 0.0016 0.27 NO
56 POLR2C POLR2C POLR2C 7953 0.0011 0.27 NO
57 POLR2G POLR2G POLR2G 7958 0.00099 0.27 NO
58 POLR2H POLR2H POLR2H 8207 -0.0029 0.26 NO
59 POLD4 POLD4 POLD4 8245 -0.0035 0.26 NO
60 AK3 AK3 AK3 8300 -0.0045 0.25 NO
61 NT5C NT5C NT5C 8383 -0.0057 0.25 NO
62 RRM2B RRM2B RRM2B 8429 -0.0063 0.25 NO
63 POLR1D POLR1D POLR1D 8481 -0.0071 0.24 NO
64 ITPA ITPA ITPA 8688 -0.01 0.24 NO
65 POLR3K POLR3K POLR3K 9185 -0.019 0.21 NO
66 POLR2F POLR2F POLR2F 9196 -0.019 0.21 NO
67 POLR2E POLR2E POLR2E 9284 -0.02 0.21 NO
68 NUDT2 NUDT2 NUDT2 9299 -0.021 0.21 NO
69 NME6 NME6 NME6 9430 -0.023 0.2 NO
70 POLR2K POLR2K POLR2K 9559 -0.025 0.2 NO
71 NME7 NME7 NME7 9564 -0.025 0.2 NO
72 TXNRD2 TXNRD2 TXNRD2 9621 -0.026 0.2 NO
73 ENTPD6 ENTPD6 ENTPD6 9860 -0.03 0.19 NO
74 POLR1C POLR1C POLR1C 9956 -0.031 0.19 NO
75 ZNRD1 ZNRD1 ZNRD1 10057 -0.033 0.19 NO
76 POLR3GL POLR3GL POLR3GL 10339 -0.039 0.18 NO
77 UCKL1 UCKL1 UCKL1 10458 -0.041 0.18 NO
78 POLR2I POLR2I POLR2I 10617 -0.045 0.17 NO
79 UPRT UPRT UPRT 10691 -0.046 0.17 NO
80 ENTPD4 ENTPD4 ENTPD4 10966 -0.052 0.16 NO
81 ENTPD1 ENTPD1 ENTPD1 11636 -0.066 0.13 NO
82 POLR2J POLR2J POLR2J 11666 -0.066 0.14 NO
83 ENTPD8 ENTPD8 ENTPD8 11874 -0.071 0.14 NO
84 TK2 TK2 TK2 12382 -0.084 0.12 NO
85 UPP2 UPP2 UPP2 12813 -0.096 0.1 NO
86 UPB1 UPB1 UPB1 13055 -0.1 0.1 NO
87 NME3 NME3 NME3 13189 -0.11 0.11 NO
88 POLR2J3 POLR2J3 POLR2J3 13447 -0.12 0.1 NO
89 CTPS2 CTPS2 CTPS2 13508 -0.12 0.11 NO
90 DPYS DPYS DPYS 13609 -0.12 0.12 NO
91 ENTPD5 ENTPD5 ENTPD5 13970 -0.13 0.12 NO
92 POLR2J2 POLR2J2 POLR2J2 14124 -0.14 0.12 NO
93 NME4 NME4 NME4 14694 -0.16 0.11 NO
94 NT5C2 NT5C2 NT5C2 14713 -0.16 0.13 NO
95 ENTPD3 ENTPD3 ENTPD3 16316 -0.26 0.066 NO
96 NME5 NME5 NME5 17139 -0.34 0.058 NO

Figure S49.  Get High-res Image This plot shows mRNAseq_cNMF expression data heatmap (on the left) a RunningEnrichmentScore(RES) plot (on the top right) and a Signal2Noise(S2N) plot (on the bottom right) of genes in the pathway: BIOCARTA MAPK PATHWAY.

Figure S50.  Get High-res Image For the top 5 core enriched genes in the pathway: BIOCARTA MAPK PATHWAY, this volcano plot shows how much they are up/down-regulated and significant. The significance was calculated by empirical bayesian fit

genes ES table in pathway: BIOCARTA P38MAPK PATHWAY

Table S26.  Get Full Table This table shows a Running Enrichment Score (RES) of each gene in this pathway, that is, the enrichment score at this point in the ranked list of genes. All genes are ranked by Signal-to-Noise (S2N), a measure of similarity as default and are used to obtain ES matrix of all genes. In this way, GSEA tool uses expression pattern of not only overlapped genes but also not-overlapped genes to produce ES matrix.

Rank GENE SYMBOL DESC LIST.LOC S2N RES CORE_ENRICHMENT
1 WARS WARS WARS 565 0.32 0.11 YES
2 TARS TARS TARS 1850 0.16 0.11 YES
3 IARS IARS IARS 2457 0.13 0.13 YES
4 YARS YARS YARS 2850 0.11 0.16 YES
5 FARSB FARSB FARSB 3146 0.1 0.19 YES
6 IARS2 IARS2 IARS2 3306 0.094 0.22 YES
7 DARS DARS DARS 3632 0.084 0.24 YES
8 MARS2 MARS2 MARS2 3864 0.078 0.26 YES
9 EPRS EPRS EPRS 3993 0.075 0.29 YES
10 RARS RARS RARS 4104 0.072 0.31 YES
11 YARS2 YARS2 YARS2 4153 0.071 0.34 YES
12 GARS GARS GARS 4190 0.07 0.37 YES
13 SARS SARS SARS 4354 0.066 0.39 YES
14 TARSL2 TARSL2 TARSL2 4480 0.063 0.41 YES
15 FARS2 FARS2 FARS2 5075 0.051 0.4 YES
16 DARS2 DARS2 DARS2 5285 0.046 0.41 YES
17 KARS KARS KARS 5365 0.045 0.42 YES
18 AARS AARS AARS 5693 0.039 0.42 YES
19 MARS MARS MARS 5886 0.035 0.43 YES
20 CARS CARS CARS 5929 0.034 0.44 YES
21 HARS HARS HARS 6163 0.03 0.44 YES
22 FARSA FARSA FARSA 6209 0.029 0.45 YES
23 VARS VARS VARS 6348 0.027 0.45 YES
24 LARS LARS LARS 7012 0.016 0.42 NO
25 PSTK PSTK PSTK 7148 0.014 0.42 NO
26 WARS2 WARS2 WARS2 7523 0.0076 0.41 NO
27 RARS2 RARS2 RARS2 7621 0.0063 0.4 NO
28 PARS2 PARS2 PARS2 7835 0.0031 0.39 NO
29 HARS2 HARS2 HARS2 8134 -0.0018 0.38 NO
30 LARS2 LARS2 LARS2 8186 -0.0026 0.38 NO
31 EARS2 EARS2 EARS2 8219 -0.0031 0.38 NO
32 NARS NARS NARS 8396 -0.0058 0.37 NO
33 CARS2 CARS2 CARS2 9493 -0.024 0.32 NO
34 MTFMT MTFMT MTFMT 9639 -0.026 0.32 NO
35 NARS2 NARS2 NARS2 9655 -0.026 0.33 NO
36 AARS2 AARS2 AARS2 9947 -0.031 0.33 NO
37 VARS2 VARS2 VARS2 11003 -0.052 0.29 NO
38 SARS2 SARS2 SARS2 11706 -0.067 0.28 NO
39 SEPSECS SEPSECS SEPSECS 12129 -0.077 0.3 NO
40 QARS QARS QARS 12534 -0.088 0.31 NO

Figure S51.  Get High-res Image This plot shows mRNAseq_cNMF expression data heatmap (on the left) a RunningEnrichmentScore(RES) plot (on the top right) and a Signal2Noise(S2N) plot (on the bottom right) of genes in the pathway: BIOCARTA P38MAPK PATHWAY.

Figure S52.  Get High-res Image For the top 5 core enriched genes in the pathway: BIOCARTA P38MAPK PATHWAY, this volcano plot shows how much they are up/down-regulated and significant. The significance was calculated by empirical bayesian fit

genes ES table in pathway: BIOCARTA IL1R PATHWAY

Table S27.  Get Full Table This table shows a Running Enrichment Score (RES) of each gene in this pathway, that is, the enrichment score at this point in the ranked list of genes. All genes are ranked by Signal-to-Noise (S2N), a measure of similarity as default and are used to obtain ES matrix of all genes. In this way, GSEA tool uses expression pattern of not only overlapped genes but also not-overlapped genes to produce ES matrix.

Rank GENE SYMBOL DESC LIST.LOC S2N RES CORE_ENRICHMENT
1 CDK6 CDK6 CDK6 104 0.59 0.22 YES
2 CCNA1 CCNA1 CCNA1 558 0.32 0.31 YES
3 TGFB2 TGFB2 TGFB2 931 0.25 0.39 YES
4 CDK1 CDK1 CDK1 2000 0.15 0.39 YES
5 TGFB1 TGFB1 TGFB1 2610 0.12 0.4 YES
6 TFDP1 TFDP1 TFDP1 2831 0.11 0.43 YES
7 CDKN1A CDKN1A CDKN1A 3142 0.1 0.45 YES
8 TGFB3 TGFB3 TGFB3 3207 0.098 0.49 YES
9 CDC25A CDC25A CDC25A 3216 0.098 0.52 YES
10 CDKN2B CDKN2B CDKN2B 3341 0.093 0.55 YES
11 SKP2 SKP2 SKP2 3391 0.092 0.58 YES
12 CDKN2A CDKN2A CDKN2A 4414 0.064 0.55 NO
13 DHFR DHFR DHFR 4584 0.06 0.56 NO
14 ATR ATR ATR 5524 0.042 0.53 NO
15 GSK3B GSK3B GSK3B 5885 0.035 0.52 NO
16 RB1 RB1 RB1 6335 0.027 0.51 NO
17 CDK4 CDK4 CDK4 6378 0.026 0.52 NO
18 ABL1 ABL1 ABL1 6917 0.017 0.49 NO
19 CCND1 CCND1 CCND1 7008 0.016 0.49 NO
20 SMAD3 SMAD3 SMAD3 7593 0.0067 0.46 NO
21 HDAC1 HDAC1 HDAC1 7625 0.0063 0.46 NO
22 CDK2 CDK2 CDK2 8228 -0.0032 0.43 NO
23 SMAD4 SMAD4 SMAD4 9756 -0.028 0.36 NO
24 CDKN1B CDKN1B CDKN1B 10608 -0.044 0.33 NO
25 CCNE1 CCNE1 CCNE1 10902 -0.05 0.33 NO
26 ATM ATM ATM 12614 -0.09 0.27 NO
27 TP53 TP53 TP53 12743 -0.094 0.3 NO

Figure S53.  Get High-res Image This plot shows mRNAseq_cNMF expression data heatmap (on the left) a RunningEnrichmentScore(RES) plot (on the top right) and a Signal2Noise(S2N) plot (on the bottom right) of genes in the pathway: BIOCARTA IL1R PATHWAY.

Figure S54.  Get High-res Image For the top 5 core enriched genes in the pathway: BIOCARTA IL1R PATHWAY, this volcano plot shows how much they are up/down-regulated and significant. The significance was calculated by empirical bayesian fit

genes ES table in pathway: BIOCARTA TNFR1 PATHWAY

Table S28.  Get Full Table This table shows a Running Enrichment Score (RES) of each gene in this pathway, that is, the enrichment score at this point in the ranked list of genes. All genes are ranked by Signal-to-Noise (S2N), a measure of similarity as default and are used to obtain ES matrix of all genes. In this way, GSEA tool uses expression pattern of not only overlapped genes but also not-overlapped genes to produce ES matrix.

Rank GENE SYMBOL DESC LIST.LOC S2N RES CORE_ENRICHMENT
1 TNF TNF TNF 1145 0.23 0.038 YES
2 BAG4 BAG4 BAG4 2015 0.15 0.058 YES
3 MAPK8 MAPK8 MAPK8 2016 0.15 0.13 YES
4 MAP3K1 MAP3K1 MAP3K1 2186 0.14 0.18 YES
5 LMNB2 LMNB2 LMNB2 2267 0.14 0.24 YES
6 PRKDC PRKDC PRKDC 2587 0.12 0.28 YES
7 LMNB1 LMNB1 LMNB1 2780 0.11 0.32 YES
8 JUN JUN JUN 2824 0.11 0.37 YES
9 PAK1 PAK1 PAK1 3075 0.1 0.4 YES
10 MAP3K7 MAP3K7 MAP3K7 3423 0.09 0.42 YES
11 TNFRSF1A TNFRSF1A TNFRSF1A 3711 0.082 0.44 YES
12 FADD FADD FADD 3781 0.08 0.47 YES
13 PAK2 PAK2 PAK2 5268 0.046 0.41 NO
14 DFFA DFFA DFFA 5953 0.034 0.39 NO
15 LMNA LMNA LMNA 6093 0.031 0.4 NO
16 PARP1 PARP1 PARP1 6118 0.031 0.41 NO
17 CASP8 CASP8 CASP8 6195 0.03 0.42 NO
18 MAP2K4 MAP2K4 MAP2K4 6217 0.029 0.43 NO
19 RB1 RB1 RB1 6335 0.027 0.43 NO
20 SPTAN1 SPTAN1 SPTAN1 6798 0.019 0.42 NO
21 RIPK1 RIPK1 RIPK1 6958 0.017 0.42 NO
22 TRADD TRADD TRADD 7329 0.011 0.4 NO
23 CRADD CRADD CRADD 7790 0.0038 0.38 NO
24 CASP2 CASP2 CASP2 7849 0.0029 0.38 NO
25 CASP3 CASP3 CASP3 10019 -0.033 0.27 NO
26 MADD MADD MADD 12769 -0.094 0.16 NO
27 DFFB DFFB DFFB 14139 -0.14 0.15 NO
28 ARHGDIB ARHGDIB ARHGDIB 14788 -0.17 0.19 NO

Figure S55.  Get High-res Image This plot shows mRNAseq_cNMF expression data heatmap (on the left) a RunningEnrichmentScore(RES) plot (on the top right) and a Signal2Noise(S2N) plot (on the bottom right) of genes in the pathway: BIOCARTA TNFR1 PATHWAY.

Figure S56.  Get High-res Image For the top 5 core enriched genes in the pathway: BIOCARTA TNFR1 PATHWAY, this volcano plot shows how much they are up/down-regulated and significant. The significance was calculated by empirical bayesian fit

genes ES table in pathway: KEGG PYRIMIDINE METABOLISM

Table S29.  Get Full Table This table shows a Running Enrichment Score (RES) of each gene in this pathway, that is, the enrichment score at this point in the ranked list of genes. All genes are ranked by Signal-to-Noise (S2N), a measure of similarity as default and are used to obtain ES matrix of all genes. In this way, GSEA tool uses expression pattern of not only overlapped genes but also not-overlapped genes to produce ES matrix.

Rank GENE SYMBOL DESC LIST.LOC S2N RES CORE_ENRICHMENT
1 POLR3G POLR3G POLR3G 88 0.61 0.097 YES
2 AIM2 AIM2 AIM2 92 0.61 0.2 YES
3 CASP1 CASP1 CASP1 185 0.48 0.27 YES
4 CXCL10 CXCL10 CXCL10 337 0.4 0.33 YES
5 CCL4 CCL4 CCL4 510 0.34 0.38 YES
6 IL18 IL18 IL18 700 0.29 0.42 YES
7 CCL4L2 CCL4L2 CCL4L2 715 0.29 0.46 YES
8 DDX58 DDX58 DDX58 970 0.25 0.49 YES
9 IL1B IL1B IL1B 1086 0.23 0.52 YES
10 IFNA13 IFNA13 IFNA13 1572 0.18 0.53 YES
11 IFNA1 IFNA1 IFNA1 1587 0.18 0.56 YES
12 TMEM173 TMEM173 TMEM173 1671 0.18 0.58 YES
13 ZBP1 ZBP1 ZBP1 2003 0.15 0.59 YES
14 CCL5 CCL5 CCL5 2159 0.14 0.6 YES
15 IRF7 IRF7 IRF7 2318 0.14 0.62 YES
16 IL6 IL6 IL6 2372 0.13 0.64 YES
17 NFKB1 NFKB1 NFKB1 3262 0.096 0.6 NO
18 CHUK CHUK CHUK 3546 0.087 0.6 NO
19 POLR3D POLR3D POLR3D 3582 0.086 0.62 NO
20 PYCARD PYCARD PYCARD 4171 0.07 0.6 NO
21 POLR3A POLR3A POLR3A 4317 0.066 0.6 NO
22 ADAR ADAR ADAR 4510 0.062 0.6 NO
23 IFNB1 IFNB1 IFNB1 4760 0.057 0.6 NO
24 POLR3F POLR3F POLR3F 4813 0.056 0.6 NO
25 IKBKG IKBKG IKBKG 5015 0.052 0.6 NO
26 IL33 IL33 IL33 5064 0.051 0.6 NO
27 POLR3B POLR3B POLR3B 6032 0.032 0.56 NO
28 POLR3H POLR3H POLR3H 6872 0.018 0.51 NO
29 RIPK1 RIPK1 RIPK1 6958 0.017 0.51 NO
30 POLR3C POLR3C POLR3C 7915 0.0016 0.46 NO
31 IKBKE IKBKE IKBKE 7990 0.00064 0.46 NO
32 NFKBIA NFKBIA NFKBIA 8271 -0.004 0.44 NO
33 POLR1D POLR1D POLR1D 8481 -0.0071 0.43 NO
34 RELA RELA RELA 8584 -0.009 0.43 NO
35 TBK1 TBK1 TBK1 8758 -0.012 0.42 NO
36 MAVS MAVS MAVS 9165 -0.018 0.4 NO
37 POLR3K POLR3K POLR3K 9185 -0.019 0.4 NO
38 POLR1C POLR1C POLR1C 9956 -0.031 0.36 NO
39 IRF3 IRF3 IRF3 10095 -0.034 0.36 NO
40 NFKBIB NFKBIB NFKBIB 10286 -0.038 0.36 NO
41 POLR3GL POLR3GL POLR3GL 10339 -0.039 0.36 NO
42 IKBKB IKBKB IKBKB 13436 -0.12 0.21 NO
43 RIPK3 RIPK3 RIPK3 14284 -0.15 0.19 NO
44 TREX1 TREX1 TREX1 14702 -0.16 0.19 NO

Figure S57.  Get High-res Image This plot shows mRNAseq_cNMF expression data heatmap (on the left) a RunningEnrichmentScore(RES) plot (on the top right) and a Signal2Noise(S2N) plot (on the bottom right) of genes in the pathway: KEGG PYRIMIDINE METABOLISM.

Figure S58.  Get High-res Image For the top 5 core enriched genes in the pathway: KEGG PYRIMIDINE METABOLISM, this volcano plot shows how much they are up/down-regulated and significant. The significance was calculated by empirical bayesian fit

genes ES table in pathway: KEGG AMINOACYL TRNA BIOSYNTHESIS

Table S30.  Get Full Table This table shows a Running Enrichment Score (RES) of each gene in this pathway, that is, the enrichment score at this point in the ranked list of genes. All genes are ranked by Signal-to-Noise (S2N), a measure of similarity as default and are used to obtain ES matrix of all genes. In this way, GSEA tool uses expression pattern of not only overlapped genes but also not-overlapped genes to produce ES matrix.

Rank GENE SYMBOL DESC LIST.LOC S2N RES CORE_ENRICHMENT
1 POLE2 POLE2 POLE2 723 0.28 0.059 YES
2 RFC4 RFC4 RFC4 1942 0.16 0.046 YES
3 MCM4 MCM4 MCM4 1997 0.15 0.097 YES
4 PRIM1 PRIM1 PRIM1 2140 0.15 0.14 YES
5 POLE3 POLE3 POLE3 2195 0.14 0.19 YES
6 MCM2 MCM2 MCM2 2295 0.14 0.23 YES
7 POLD2 POLD2 POLD2 2305 0.14 0.28 YES
8 RFC3 RFC3 RFC3 2496 0.13 0.31 YES
9 FEN1 FEN1 FEN1 2688 0.12 0.34 YES
10 RNASEH1 RNASEH1 RNASEH1 2693 0.12 0.38 YES
11 MCM6 MCM6 MCM6 2777 0.12 0.42 YES
12 PRIM2 PRIM2 PRIM2 2868 0.11 0.45 YES
13 POLD1 POLD1 POLD1 3007 0.1 0.48 YES
14 RPA3 RPA3 RPA3 3167 0.1 0.5 YES
15 POLA2 POLA2 POLA2 3829 0.079 0.5 YES
16 DNA2 DNA2 DNA2 3975 0.075 0.51 YES
17 PCNA PCNA PCNA 4013 0.074 0.54 YES
18 POLD3 POLD3 POLD3 4025 0.074 0.56 YES
19 RFC2 RFC2 RFC2 4193 0.07 0.58 YES
20 RPA1 RPA1 RPA1 4567 0.061 0.58 YES
21 MCM5 MCM5 MCM5 4627 0.059 0.6 YES
22 RFC1 RFC1 RFC1 4659 0.058 0.61 YES
23 RNASEH2A RNASEH2A RNASEH2A 5096 0.05 0.61 YES
24 MCM7 MCM7 MCM7 5264 0.046 0.61 YES
25 SSBP1 SSBP1 SSBP1 5501 0.042 0.62 YES
26 RPA4 RPA4 RPA4 5752 0.038 0.62 YES
27 RFC5 RFC5 RFC5 5777 0.037 0.63 YES
28 POLE POLE POLE 6313 0.028 0.61 NO
29 POLE4 POLE4 POLE4 6828 0.019 0.58 NO
30 RNASEH2B RNASEH2B RNASEH2B 8216 -0.0031 0.51 NO
31 POLD4 POLD4 POLD4 8245 -0.0035 0.51 NO
32 MCM3 MCM3 MCM3 8246 -0.0035 0.51 NO
33 LIG1 LIG1 LIG1 8452 -0.0066 0.5 NO
34 RPA2 RPA2 RPA2 8468 -0.0069 0.5 NO
35 RNASEH2C RNASEH2C RNASEH2C 12717 -0.093 0.3 NO

Figure S59.  Get High-res Image This plot shows mRNAseq_cNMF expression data heatmap (on the left) a RunningEnrichmentScore(RES) plot (on the top right) and a Signal2Noise(S2N) plot (on the bottom right) of genes in the pathway: KEGG AMINOACYL TRNA BIOSYNTHESIS.

Figure S60.  Get High-res Image For the top 5 core enriched genes in the pathway: KEGG AMINOACYL TRNA BIOSYNTHESIS, this volcano plot shows how much they are up/down-regulated and significant. The significance was calculated by empirical bayesian fit

Fold change

For the top enriched genes, if you want to check whether they are

Expression level

For the top enriched genes, if you want to check whether they are

An expression pattern of top(30%)/middle(30%)/low(30%) in this subtype against other subtypes is available in a heatmap

Significant gene list

For the top enriched genes, if you want to check whether they are

Methods & Data
Input
  • Gene set database = c2.cp.v3.0-2.symbols.gmt

  • Expression data file = BLCA-TP.uncv2.mRNAseq_RSEM_normalized_log2.txt

  • Phenotype data file = BLCA-TP.mergedcluster.txt

GSEA analysis

For the Gene Set Enrichment Analysis (GSEA), Broad GSEA-P-R.1.0 version is used with class2: canonical pathways geneses from MSigDB. Further details about statistics are available inThe Broad GSEA website.

Download Results

In addition to the links below, the full results of the analysis summarized in this report can also be downloaded programmatically using firehose_get, or interactively from either the Broad GDAC website or TCGA Data Coordination Center Portal.

References
[1] Subramanian, A. et al, Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles., Proc. Natl. Acad. Sci. USA 102(43) (2005)