GSEA Class2: Canonical Pathways enriched in each subtypes of mRNAseq_cNMF in UCS-TP
Uterine Carcinosarcoma (Primary solid tumor)
02 April 2015 | analyses__2015_04_02
Maintainer Information
Citation Information
doi:10.7908/C1B56HW1
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 UCS-TP. Broad Institute of MIT and Harvard. doi:10.7908/C1B56HW1
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 UCS-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: 191
Number of samples: 57
Original number of Gene Sets: 404
Maximum gene set size: 388

Table 2. Get Full Table pheno data info

phenotype info
pheno.type: 1 - 4 :[ clus1 ] 15
pheno.type: 2 - 4 :[ clus2 ] 20
pheno.type: 3 - 4 :[ clus3 ] 12
pheno.type: 4 - 4 :[ clus4 ] 10

For the expression subtypes of 18665 genes in 58 samples, GSEA found enriched gene sets in each cluster using 57 gene sets in MSigDB canonical pathways. Top enriched gene sets are listed as below.

- clus1

- Top enriched gene sets are BIOCARTA NO1 PATHWAY, BIOCARTA AGR PATHWAY, BIOCARTA ALK PATHWAY, BIOCARTA BIOPEPTIDES PATHWAY, BIOCARTA HDAC PATHWAY, BIOCARTA INTEGRIN PATHWAY, BIOCARTA CREB PATHWAY, KEGG PROPANOATE METABOLISM, KEGG RNA DEGRADATION, KEGG MAPK SIGNALING PATHWAY

- And common core enriched genes are ACTA1, ACTN2, ACTN3, ACTC1, ATP1A2, ATP1A3, ATP1A4, ATP1B2, ATP1B4, CACNA1S

- clus2

- Top enriched gene sets are BIOCARTA FAS PATHWAY, BIOCARTA FCER1 PATHWAY, BIOCARTA HIVNEF PATHWAY, BIOCARTA IL2RB PATHWAY, BIOCARTA DEATH PATHWAY, BIOCARTA TNFR1 PATHWAY, BIOCARTA TOLL PATHWAY, KEGG SELENOAMINO ACID METABOLISM, KEGG LYSOSOME, KEGG APOPTOSIS

- And common core enriched genes are CFLAR, FAS, FOS, MAP3K1, NFKBIA, CASP8, FASLG, PIK3CG, PIK3R1, CD14

- clus3

- Top enriched gene sets are BIOCARTA CARM ER PATHWAY, BIOCARTA PYK2 PATHWAY, KEGG TYROSINE METABOLISM, KEGG STARCH AND SUCROSE METABOLISM, KEGG BUTANOATE METABOLISM, KEGG RETINOL METABOLISM, KEGG PORPHYRIN AND CHLOROPHYLL METABOLISM, KEGG METABOLISM OF XENOBIOTICS BY CYTOCHROME P450, KEGG DRUG METABOLISM CYTOCHROME P450, KEGG DRUG METABOLISM OTHER ENZYMES

- And common core enriched genes are UGT1A6, UGT2A3, UGT2B10, UGT2B11, UGT2B15, UGT2B7, ADH1B, ADH1C, ADH6, CYP2B6

- clus4

- Top enriched gene sets are BIOCARTA ALK PATHWAY, BIOCARTA G1 PATHWAY, KEGG CITRATE CYCLE TCA CYCLE, KEGG PYRIMIDINE METABOLISM, KEGG LYSINE DEGRADATION, KEGG AMINOACYL TRNA BIOSYNTHESIS, KEGG RNA DEGRADATION, KEGG RNA POLYMERASE, KEGG BASAL TRANSCRIPTION FACTORS, KEGG DNA REPLICATION

- And common core enriched genes are PCNA, GTF2H1, GTF2H2, GTF2H3, GTF2H4, MCM6, POLD1, POLE, POLE2, RFC1

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 | 28 | genes.ES.table | 0.71 | 1.8 | 0 | 0.11 | 0.27 | 0.21 | 0.042 | 0.21 | 0 | 0.018
BIOCARTA AGR PATHWAY | 35 | genes.ES.table | 0.65 | 1.8 | 0.002 | 0.13 | 0.23 | 0.14 | 0.028 | 0.14 | 0 | 0.028
BIOCARTA ALK PATHWAY | 35 | genes.ES.table | 0.52 | 1.5 | 0.041 | 0.27 | 0.78 | 0.31 | 0.16 | 0.26 | 0.16 | 0.041
BIOCARTA BIOPEPTIDES PATHWAY | 41 | genes.ES.table | 0.51 | 1.6 | 0.027 | 0.23 | 0.65 | 0.22 | 0.14 | 0.19 | 0.12 | 0.036
BIOCARTA HDAC PATHWAY | 27 | genes.ES.table | 0.54 | 1.6 | 0.03 | 0.21 | 0.69 | 0.22 | 0.15 | 0.19 | 0.12 | 0.029
BIOCARTA INTEGRIN PATHWAY | 37 | genes.ES.table | 0.61 | 2.2 | 0 | 0.0029 | 0.002 | 0.081 | 0.0058 | 0.081 | 0 | 0.001
BIOCARTA CREB PATHWAY | 25 | genes.ES.table | 0.48 | 1.5 | 0.034 | 0.25 | 0.79 | 0.24 | 0.15 | 0.2 | 0.15 | 0.037
KEGG PROPANOATE METABOLISM | 31 | genes.ES.table | 0.43 | 1.5 | 0.051 | 0.28 | 0.78 | 0.29 | 0.21 | 0.23 | 0.17 | 0.047
KEGG RNA DEGRADATION | 56 | genes.ES.table | 0.39 | 1.9 | 0.014 | 0.15 | 0.2 | 0.018 | 0.0044 | 0.018 | 0 | 0.045
KEGG MAPK SIGNALING PATHWAY | 256 | genes.ES.table | 0.39 | 1.5 | 0.012 | 0.34 | 0.87 | 0.23 | 0.16 | 0.19 | 0.24 | 0.048

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 | ACTN2 | ACTN2 | ACTN2 | 37 | 1.7 | 0.23 | YES
2 | ACTA1 | ACTA1 | ACTA1 | 52 | 1.6 | 0.44 | YES
3 | ACTN3 | ACTN3 | ACTN3 | 108 | 1.2 | 0.61 | YES
4 | PPP1R12B | PPP1R12B | PPP1R12B | 1662 | 0.27 | 0.56 | NO
5 | FYN | FYN | FYN | 1893 | 0.25 | 0.58 | NO
6 | MAP2K1 | MAP2K1 | MAP2K1 | 2614 | 0.18 | 0.57 | NO
7 | TNS1 | TNS1 | TNS1 | 3092 | 0.14 | 0.56 | NO
8 | PXN | PXN | PXN | 3390 | 0.13 | 0.56 | NO
9 | RAPGEF1 | RAPGEF1 | RAPGEF1 | 3400 | 0.13 | 0.58 | NO
10 | HRAS | HRAS | HRAS | 3905 | 0.11 | 0.57 | NO
11 | MAP2K2 | MAP2K2 | MAP2K2 | 6534 | 0.044 | 0.43 | NO
12 | CRKL | CRKL | CRKL | 6557 | 0.044 | 0.44 | NO
13 | MAPK8 | MAPK8 | MAPK8 | 6650 | 0.042 | 0.44 | NO
14 | RAF1 | RAF1 | RAF1 | 6702 | 0.041 | 0.44 | NO
15 | SHC1 | SHC1 | SHC1 | 6801 | 0.039 | 0.44 | NO
16 | ZYX | ZYX | ZYX | 6813 | 0.039 | 0.45 | NO
17 | CAV1 | CAV1 | CAV1 | 7996 | 0.02 | 0.39 | NO
18 | MAPK1 | MAPK1 | MAPK1 | 8189 | 0.016 | 0.38 | NO
19 | CSK | CSK | CSK | 8293 | 0.014 | 0.37 | NO
20 | RAP1A | RAP1A | RAP1A | 8695 | 0.0082 | 0.35 | NO
21 | SOS1 | SOS1 | SOS1 | 9503 | -0.0053 | 0.31 | NO
22 | RHOA | RHOA | RHOA | 9709 | -0.0086 | 0.3 | NO
23 | GRB2 | GRB2 | GRB2 | 9816 | -0.01 | 0.3 | NO
24 | BCAR1 | BCAR1 | BCAR1 | 10111 | -0.015 | 0.28 | NO
25 | SRC | SRC | SRC | 10349 | -0.019 | 0.27 | NO
26 | CAPNS1 | CAPNS1 | CAPNS1 | 10641 | -0.023 | 0.26 | NO
27 | VCL | VCL | VCL | 11774 | -0.043 | 0.2 | NO
28 | PTK2 | PTK2 | PTK2 | 12010 | -0.048 | 0.2 | NO
29 | JUN | JUN | JUN | 12663 | -0.062 | 0.17 | NO
30 | ROCK1 | ROCK1 | ROCK1 | 12759 | -0.064 | 0.18 | NO
31 | CAPN1 | CAPN1 | CAPN1 | 12852 | -0.066 | 0.18 | NO
32 | MAPK3 | MAPK3 | MAPK3 | 12916 | -0.068 | 0.19 | NO
33 | ITGB1 | ITGB1 | ITGB1 | 12942 | -0.068 | 0.19 | NO
34 | ACTN1 | ACTN1 | ACTN1 | 14784 | -0.12 | 0.11 | NO
35 | ITGA1 | ITGA1 | ITGA1 | 15082 | -0.14 | 0.11 | NO
36 | BCR | BCR | BCR | 15245 | -0.14 | 0.12 | NO
37 | CAPNS2 | CAPNS2 | CAPNS2 | 18037 | -0.42 | 0.033 | 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 AGR 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 | CACNA1S | CACNA1S | CACNA1S | 18 | 1.8 | 0.071 | YES
2 | CACNG1 | CACNG1 | CACNG1 | 36 | 1.7 | 0.14 | YES
3 | ACTC1 | ACTC1 | ACTC1 | 51 | 1.6 | 0.2 | YES
4 | TNNT2 | TNNT2 | TNNT2 | 63 | 1.5 | 0.26 | YES
5 | COX6A2 | COX6A2 | COX6A2 | 79 | 1.4 | 0.31 | YES
6 | MYH7 | MYH7 | MYH7 | 90 | 1.3 | 0.37 | YES
7 | ATP1B4 | ATP1B4 | ATP1B4 | 93 | 1.3 | 0.42 | YES
8 | TNNC1 | TNNC1 | TNNC1 | 94 | 1.3 | 0.47 | YES
9 | MYL3 | MYL3 | MYL3 | 150 | 1.1 | 0.51 | YES
10 | MYH6 | MYH6 | MYH6 | 157 | 1 | 0.55 | YES
11 | MYL2 | MYL2 | MYL2 | 179 | 0.96 | 0.59 | YES
12 | CACNG6 | CACNG6 | CACNG6 | 188 | 0.92 | 0.62 | YES
13 | CACNB1 | CACNB1 | CACNB1 | 465 | 0.61 | 0.63 | YES
14 | RYR2 | RYR2 | RYR2 | 491 | 0.59 | 0.66 | YES
15 | CACNA2D1 | CACNA2D1 | CACNA2D1 | 640 | 0.51 | 0.67 | YES
16 | ATP1B2 | ATP1B2 | ATP1B2 | 643 | 0.51 | 0.69 | YES
17 | CACNA2D4 | CACNA2D4 | CACNA2D4 | 764 | 0.45 | 0.7 | YES
18 | TPM2 | TPM2 | TPM2 | 808 | 0.44 | 0.71 | YES
19 | ATP1A3 | ATP1A3 | ATP1A3 | 1057 | 0.38 | 0.72 | YES
20 | ATP1A2 | ATP1A2 | ATP1A2 | 1207 | 0.35 | 0.72 | YES
21 | ATP1A4 | ATP1A4 | ATP1A4 | 1283 | 0.33 | 0.73 | YES
22 | COX8C | COX8C | COX8C | 1285 | 0.33 | 0.74 | YES
23 | TNNI3 | TNNI3 | TNNI3 | 1348 | 0.32 | 0.75 | YES
24 | ATP2A2 | ATP2A2 | ATP2A2 | 1959 | 0.24 | 0.73 | NO
25 | CACNA2D2 | CACNA2D2 | CACNA2D2 | 2053 | 0.23 | 0.73 | NO
26 | TPM1 | TPM1 | TPM1 | 2088 | 0.22 | 0.74 | NO
27 | CACNG8 | CACNG8 | CACNG8 | 2822 | 0.16 | 0.71 | NO
28 | UQCRFS1 | UQCRFS1 | UQCRFS1 | 2970 | 0.15 | 0.71 | NO
29 | CACNB4 | CACNB4 | CACNB4 | 3232 | 0.14 | 0.7 | NO
30 | COX7A1 | COX7A1 | COX7A1 | 4193 | 0.098 | 0.65 | NO
31 | TPM3 | TPM3 | TPM3 | 4561 | 0.087 | 0.63 | NO
32 | COX5A | COX5A | COX5A | 4888 | 0.078 | 0.62 | NO
33 | COX5B | COX5B | COX5B | 4916 | 0.078 | 0.62 | NO
34 | COX7A2L | COX7A2L | COX7A2L | 5160 | 0.072 | 0.61 | NO
35 | COX6B1 | COX6B1 | COX6B1 | 5439 | 0.065 | 0.6 | NO
36 | CYC1 | CYC1 | CYC1 | 6204 | 0.05 | 0.56 | NO
37 | UQCR11 | UQCR11 | UQCR11 | 6292 | 0.049 | 0.56 | NO
38 | COX6C | COX6C | COX6C | 6695 | 0.041 | 0.54 | NO
39 | CACNB2 | CACNB2 | CACNB2 | 6909 | 0.037 | 0.53 | NO
40 | COX8A | COX8A | COX8A | 7090 | 0.034 | 0.52 | NO
41 | ATP1B3 | ATP1B3 | ATP1B3 | 7224 | 0.032 | 0.51 | NO
42 | COX7B | COX7B | COX7B | 7451 | 0.028 | 0.5 | NO
43 | UQCR10 | UQCR10 | UQCR10 | 7616 | 0.026 | 0.49 | NO
44 | COX7A2 | COX7A2 | COX7A2 | 8210 | 0.016 | 0.46 | NO
45 | COX4I1 | COX4I1 | COX4I1 | 8313 | 0.014 | 0.46 | NO
46 | UQCRB | UQCRB | UQCRB | 8786 | 0.0066 | 0.43 | NO
47 | SLC9A1 | SLC9A1 | SLC9A1 | 9302 | -0.0022 | 0.4 | NO
48 | COX4I2 | COX4I2 | COX4I2 | 10405 | -0.02 | 0.34 | NO
49 | UQCRC1 | UQCRC1 | UQCRC1 | 10547 | -0.022 | 0.34 | NO
50 | COX6A1 | COX6A1 | COX6A1 | 11577 | -0.039 | 0.28 | NO
51 | CACNB3 | CACNB3 | CACNB3 | 11639 | -0.04 | 0.28 | NO
52 | COX7C | COX7C | COX7C | 12228 | -0.052 | 0.25 | NO
53 | CACNG4 | CACNG4 | CACNG4 | 12260 | -0.053 | 0.25 | NO
54 | CACNA1F | CACNA1F | CACNA1F | 12665 | -0.062 | 0.24 | NO
55 | UQCRQ | UQCRQ | UQCRQ | 12991 | -0.069 | 0.22 | NO
56 | ATP1A1 | ATP1A1 | ATP1A1 | 13107 | -0.072 | 0.22 | NO
57 | CACNA1C | CACNA1C | CACNA1C | 13154 | -0.073 | 0.22 | NO
58 | CACNG7 | CACNG7 | CACNG7 | 13331 | -0.077 | 0.21 | NO
59 | TPM4 | TPM4 | TPM4 | 13770 | -0.09 | 0.19 | NO
60 | UQCRHL | UQCRHL | UQCRHL | 14029 | -0.097 | 0.18 | NO
61 | UQCRH | UQCRH | UQCRH | 14678 | -0.12 | 0.15 | NO
62 | SLC9A6 | SLC9A6 | SLC9A6 | 14962 | -0.13 | 0.14 | NO
63 | CACNA2D3 | CACNA2D3 | CACNA2D3 | 15685 | -0.16 | 0.11 | NO
64 | FXYD2 | FXYD2 | FXYD2 | 15733 | -0.17 | 0.11 | NO
65 | CACNG5 | CACNG5 | CACNG5 | 16200 | -0.19 | 0.094 | NO
66 | COX6B2 | COX6B2 | COX6B2 | 16271 | -0.2 | 0.099 | NO
67 | ATP1B1 | ATP1B1 | ATP1B1 | 16482 | -0.21 | 0.096 | NO
68 | CACNA1D | CACNA1D | CACNA1D | 16681 | -0.23 | 0.094 | NO
69 | SLC8A1 | SLC8A1 | SLC8A1 | 17299 | -0.29 | 0.072 | 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 AGR PATHWAY.

Figure S4. Get High-res Image For the top 5 core enriched genes in the pathway: BIOCARTA AGR 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 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 | ENO3 | ENO3 | ENO3 | 83 | 1.4 | 0.39 | YES
2 | XRN1 | XRN1 | XRN1 | 5218 | 0.07 | 0.13 | NO
3 | DCP2 | DCP2 | DCP2 | 5372 | 0.067 | 0.14 | NO
4 | EXOSC3 | EXOSC3 | EXOSC3 | 5381 | 0.067 | 0.16 | NO
5 | EXOSC4 | EXOSC4 | EXOSC4 | 5411 | 0.066 | 0.18 | NO
6 | EDC3 | EDC3 | EDC3 | 5583 | 0.062 | 0.19 | NO
7 | EXOSC8 | EXOSC8 | EXOSC8 | 5943 | 0.055 | 0.18 | NO
8 | SKIV2L2 | SKIV2L2 | SKIV2L2 | 6115 | 0.052 | 0.19 | NO
9 | SKIV2L | SKIV2L | SKIV2L | 6222 | 0.05 | 0.2 | NO
10 | HSPD1 | HSPD1 | HSPD1 | 6303 | 0.049 | 0.21 | NO
11 | EXOSC5 | EXOSC5 | EXOSC5 | 6323 | 0.048 | 0.22 | NO
12 | EDC4 | EDC4 | EDC4 | 6402 | 0.046 | 0.23 | NO
13 | DIS3 | DIS3 | DIS3 | 6432 | 0.046 | 0.24 | NO
14 | LSM4 | LSM4 | LSM4 | 6586 | 0.043 | 0.25 | NO
15 | EXOSC6 | EXOSC6 | EXOSC6 | 6671 | 0.042 | 0.25 | NO
16 | EXOSC1 | EXOSC1 | EXOSC1 | 7098 | 0.034 | 0.24 | NO
17 | EXOSC7 | EXOSC7 | EXOSC7 | 7437 | 0.028 | 0.23 | NO
18 | CNOT6L | CNOT6L | CNOT6L | 7468 | 0.028 | 0.24 | NO
19 | HSPA9 | HSPA9 | HSPA9 | 7718 | 0.024 | 0.23 | NO
20 | PNPT1 | PNPT1 | PNPT1 | 7949 | 0.02 | 0.22 | NO
21 | WDR61 | WDR61 | WDR61 | 7959 | 0.02 | 0.23 | NO
22 | LSM5 | LSM5 | LSM5 | 8025 | 0.019 | 0.23 | NO
23 | C1D | C1D | C1D | 8373 | 0.013 | 0.22 | NO
24 | DDX6 | DDX6 | DDX6 | 8512 | 0.011 | 0.21 | NO
25 | CNOT2 | CNOT2 | CNOT2 | 8636 | 0.0092 | 0.21 | NO
26 | CNOT7 | CNOT7 | CNOT7 | 8692 | 0.0083 | 0.21 | NO
27 | DCPS | DCPS | DCPS | 8741 | 0.0074 | 0.21 | NO
28 | PATL1 | PATL1 | PATL1 | 8792 | 0.0065 | 0.2 | NO
29 | EXOSC10 | EXOSC10 | EXOSC10 | 8810 | 0.0061 | 0.21 | NO
30 | DCP1A | DCP1A | DCP1A | 8896 | 0.0044 | 0.2 | NO
31 | CNOT10 | CNOT10 | CNOT10 | 9001 | 0.0028 | 0.2 | NO
32 | RQCD1 | RQCD1 | RQCD1 | 9018 | 0.0026 | 0.2 | NO
33 | CNOT3 | CNOT3 | CNOT3 | 9057 | 0.002 | 0.2 | NO
34 | PARN | PARN | PARN | 9209 | -0.00075 | 0.19 | NO
35 | LSM3 | LSM3 | LSM3 | 9441 | -0.0042 | 0.18 | NO
36 | PAPOLG | PAPOLG | PAPOLG | 9518 | -0.0056 | 0.18 | NO
37 | EXOSC2 | EXOSC2 | EXOSC2 | 9523 | -0.0056 | 0.18 | NO
38 | LSM7 | LSM7 | LSM7 | 10014 | -0.014 | 0.15 | NO
39 | XRN2 | XRN2 | XRN2 | 10201 | -0.016 | 0.15 | NO
40 | MPHOSPH6 | MPHOSPH6 | MPHOSPH6 | 10327 | -0.018 | 0.15 | NO
41 | LSM1 | LSM1 | LSM1 | 10572 | -0.022 | 0.14 | NO
42 | PAPOLA | PAPOLA | PAPOLA | 10606 | -0.022 | 0.14 | NO
43 | CNOT4 | CNOT4 | CNOT4 | 11103 | -0.031 | 0.13 | NO
44 | ZCCHC7 | ZCCHC7 | ZCCHC7 | 11291 | -0.034 | 0.13 | NO
45 | PAPD7 | PAPD7 | PAPD7 | 11380 | -0.036 | 0.13 | NO
46 | TTC37 | TTC37 | TTC37 | 11790 | -0.043 | 0.12 | NO
47 | NAA38 | NAA38 | NAA38 | 12097 | -0.049 | 0.12 | NO
48 | LSM2 | LSM2 | LSM2 | 12240 | -0.052 | 0.13 | NO
49 | EXOSC9 | EXOSC9 | EXOSC9 | 12337 | -0.054 | 0.14 | NO
50 | PAPOLB | PAPOLB | PAPOLB | 12390 | -0.055 | 0.15 | NO
51 | CNOT1 | CNOT1 | CNOT1 | 12513 | -0.058 | 0.16 | NO
52 | ENO1 | ENO1 | ENO1 | 12635 | -0.061 | 0.17 | NO
53 | LSM6 | LSM6 | LSM6 | 13538 | -0.083 | 0.15 | NO
54 | DCP1B | DCP1B | DCP1B | 14082 | -0.099 | 0.15 | NO
55 | CNOT6 | CNOT6 | CNOT6 | 15674 | -0.16 | 0.11 | NO
56 | ENO2 | ENO2 | ENO2 | 16013 | -0.18 | 0.14 | 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 ALK PATHWAY.

Figure S6. 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 BIOPEPTIDES 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 | MUSK | MUSK | MUSK | 14 | 1.9 | 0.19 | YES
2 | ACTA1 | ACTA1 | ACTA1 | 52 | 1.6 | 0.34 | YES
3 | RAPSN | RAPSN | RAPSN | 55 | 1.6 | 0.5 | YES
4 | CHRNA1 | CHRNA1 | CHRNA1 | 120 | 1.2 | 0.62 | YES
5 | LAMA2 | LAMA2 | LAMA2 | 516 | 0.57 | 0.65 | YES
6 | GIT2 | GIT2 | GIT2 | 2906 | 0.16 | 0.54 | NO
7 | DAG1 | DAG1 | DAG1 | 3086 | 0.14 | 0.55 | NO
8 | NRG2 | NRG2 | NRG2 | 3139 | 0.14 | 0.56 | NO
9 | LAMA4 | LAMA4 | LAMA4 | 3188 | 0.14 | 0.57 | NO
10 | PXN | PXN | PXN | 3390 | 0.13 | 0.57 | NO
11 | DMD | DMD | DMD | 4633 | 0.086 | 0.51 | NO
12 | NRG1 | NRG1 | NRG1 | 5462 | 0.065 | 0.48 | NO
13 | DVL1 | DVL1 | DVL1 | 5874 | 0.057 | 0.46 | NO
14 | PAK3 | PAK3 | PAK3 | 5938 | 0.055 | 0.46 | NO
15 | MAPK8 | MAPK8 | MAPK8 | 6650 | 0.042 | 0.43 | NO
16 | PAK2 | PAK2 | PAK2 | 6777 | 0.039 | 0.42 | NO
17 | MAPK1 | MAPK1 | MAPK1 | 8189 | 0.016 | 0.35 | NO
18 | CDC42 | CDC42 | CDC42 | 8952 | 0.0036 | 0.31 | NO
19 | SP1 | SP1 | SP1 | 10290 | -0.018 | 0.24 | NO
20 | SRC | SRC | SRC | 10349 | -0.019 | 0.24 | NO
21 | RAC1 | RAC1 | RAC1 | 10489 | -0.021 | 0.23 | NO
22 | PAK7 | PAK7 | PAK7 | 11138 | -0.031 | 0.2 | NO
23 | PAK1 | PAK1 | PAK1 | 11956 | -0.046 | 0.16 | NO
24 | PTK2 | PTK2 | PTK2 | 12010 | -0.048 | 0.16 | NO
25 | CTTN | CTTN | CTTN | 12474 | -0.057 | 0.14 | NO
26 | JUN | JUN | JUN | 12663 | -0.062 | 0.14 | NO
27 | UTRN | UTRN | UTRN | 12692 | -0.062 | 0.14 | NO
28 | MAPK3 | MAPK3 | MAPK3 | 12916 | -0.068 | 0.14 | NO
29 | ITGB1 | ITGB1 | ITGB1 | 12942 | -0.068 | 0.14 | NO
30 | PAK4 | PAK4 | PAK4 | 13417 | -0.08 | 0.13 | NO
31 | EGFR | EGFR | EGFR | 14574 | -0.12 | 0.077 | NO
32 | ITGA1 | ITGA1 | ITGA1 | 15082 | -0.14 | 0.064 | NO
33 | CHRM1 | CHRM1 | CHRM1 | 15321 | -0.15 | 0.066 | NO
34 | LAMA3 | LAMA3 | LAMA3 | 18345 | -0.52 | -0.045 | NO
35 | PAK6 | PAK6 | PAK6 | 18475 | -0.6 | 0.0092 | 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 BIOPEPTIDES PATHWAY.

Figure S8. 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 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 | PRKAG3 | PRKAG3 | PRKAG3 | 31 | 1.7 | 0.074 | YES
2 | CALML6 | CALML6 | CALML6 | 98 | 1.3 | 0.13 | YES
3 | FBP2 | FBP2 | FBP2 | 107 | 1.2 | 0.18 | YES
4 | PYGM | PYGM | PYGM | 124 | 1.2 | 0.23 | YES
5 | PHKG1 | PHKG1 | PHKG1 | 212 | 0.88 | 0.26 | YES
6 | PPP1R3A | PPP1R3A | PPP1R3A | 287 | 0.77 | 0.29 | YES
7 | PPP1R3C | PPP1R3C | PPP1R3C | 313 | 0.74 | 0.33 | YES
8 | SLC2A4 | SLC2A4 | SLC2A4 | 405 | 0.66 | 0.35 | YES
9 | GCK | GCK | GCK | 812 | 0.43 | 0.35 | YES
10 | GYS2 | GYS2 | GYS2 | 844 | 0.42 | 0.36 | YES
11 | PRKAA2 | PRKAA2 | PRKAA2 | 971 | 0.39 | 0.38 | YES
12 | SHC2 | SHC2 | SHC2 | 1092 | 0.37 | 0.38 | YES
13 | PPARGC1A | PPARGC1A | PPARGC1A | 1186 | 0.35 | 0.4 | YES
14 | PKLR | PKLR | PKLR | 1301 | 0.33 | 0.4 | YES
15 | FOXO1 | FOXO1 | FOXO1 | 1360 | 0.32 | 0.42 | YES
16 | SH2B2 | SH2B2 | SH2B2 | 1578 | 0.28 | 0.42 | YES
17 | PRKAB2 | PRKAB2 | PRKAB2 | 2442 | 0.19 | 0.38 | NO
18 | PRKACA | PRKACA | PRKACA | 2457 | 0.19 | 0.39 | NO
19 | PRKAR2A | PRKAR2A | PRKAR2A | 2472 | 0.19 | 0.39 | NO
20 | MAP2K1 | MAP2K1 | MAP2K1 | 2614 | 0.18 | 0.39 | NO
21 | PRKAR1B | PRKAR1B | PRKAR1B | 2826 | 0.16 | 0.39 | NO
22 | RAPGEF1 | RAPGEF1 | RAPGEF1 | 3400 | 0.13 | 0.36 | NO
23 | SORBS1 | SORBS1 | SORBS1 | 3687 | 0.12 | 0.35 | NO
24 | GYS1 | GYS1 | GYS1 | 3809 | 0.11 | 0.35 | NO
25 | PIK3CA | PIK3CA | PIK3CA | 4106 | 0.1 | 0.34 | NO
26 | PRKAR1A | PRKAR1A | PRKAR1A | 4152 | 0.1 | 0.34 | NO
27 | NRAS | NRAS | NRAS | 4165 | 0.099 | 0.35 | NO
28 | EIF4EBP1 | EIF4EBP1 | EIF4EBP1 | 4275 | 0.096 | 0.34 | NO
29 | ELK1 | ELK1 | ELK1 | 4452 | 0.091 | 0.34 | NO
30 | RHOQ | RHOQ | RHOQ | 4529 | 0.088 | 0.34 | NO
31 | PPP1R3B | PPP1R3B | PPP1R3B | 4808 | 0.081 | 0.33 | NO
32 | PRKAG1 | PRKAG1 | PRKAG1 | 4934 | 0.078 | 0.32 | NO
33 | HK2 | HK2 | HK2 | 4960 | 0.077 | 0.33 | NO
34 | GSK3B | GSK3B | GSK3B | 5150 | 0.072 | 0.32 | NO
35 | EIF4E2 | EIF4E2 | EIF4E2 | 5384 | 0.067 | 0.31 | NO
36 | AKT2 | AKT2 | AKT2 | 5388 | 0.067 | 0.31 | NO
37 | RPTOR | RPTOR | RPTOR | 5743 | 0.059 | 0.3 | NO
38 | PDE3B | PDE3B | PDE3B | 5910 | 0.056 | 0.29 | NO
39 | SHC4 | SHC4 | SHC4 | 5930 | 0.056 | 0.29 | NO
40 | RPS6KB2 | RPS6KB2 | RPS6KB2 | 6282 | 0.049 | 0.27 | NO
41 | PDPK1 | PDPK1 | PDPK1 | 6412 | 0.046 | 0.27 | NO
42 | MAP2K2 | MAP2K2 | MAP2K2 | 6534 | 0.044 | 0.26 | NO
43 | CRKL | CRKL | CRKL | 6557 | 0.044 | 0.27 | NO
44 | MAPK8 | MAPK8 | MAPK8 | 6650 | 0.042 | 0.26 | NO
45 | PIK3R2 | PIK3R2 | PIK3R2 | 6678 | 0.041 | 0.26 | NO
46 | INPP5K | INPP5K | INPP5K | 6683 | 0.041 | 0.26 | NO
47 | RAF1 | RAF1 | RAF1 | 6702 | 0.041 | 0.26 | NO
48 | PHKA1 | PHKA1 | PHKA1 | 6743 | 0.04 | 0.26 | NO
49 | SHC1 | SHC1 | SHC1 | 6801 | 0.039 | 0.26 | NO
50 | PPP1CC | PPP1CC | PPP1CC | 7037 | 0.035 | 0.25 | NO
51 | RPS6 | RPS6 | RPS6 | 7048 | 0.034 | 0.25 | NO
52 | TSC2 | TSC2 | TSC2 | 7171 | 0.032 | 0.25 | NO
53 | PRKACB | PRKACB | PRKACB | 7201 | 0.032 | 0.25 | NO
54 | TSC1 | TSC1 | TSC1 | 7404 | 0.029 | 0.24 | NO
55 | PIK3CG | PIK3CG | PIK3CG | 7634 | 0.025 | 0.23 | NO
56 | HK3 | HK3 | HK3 | 7643 | 0.025 | 0.23 | NO
57 | CBL | CBL | CBL | 7818 | 0.022 | 0.22 | NO
58 | PTPN1 | PTPN1 | PTPN1 | 7875 | 0.021 | 0.22 | NO
59 | PYGL | PYGL | PYGL | 8018 | 0.019 | 0.21 | NO
60 | MKNK1 | MKNK1 | MKNK1 | 8136 | 0.017 | 0.2 | NO
61 | RPS6KB1 | RPS6KB1 | RPS6KB1 | 8165 | 0.017 | 0.2 | NO
62 | MAPK1 | MAPK1 | MAPK1 | 8189 | 0.016 | 0.2 | NO
63 | PIK3R1 | PIK3R1 | PIK3R1 | 8367 | 0.013 | 0.2 | NO
64 | AKT1 | AKT1 | AKT1 | 8522 | 0.011 | 0.19 | NO
65 | CBLB | CBLB | CBLB | 8605 | 0.0097 | 0.18 | NO
66 | G6PC | G6PC | G6PC | 8711 | 0.0078 | 0.18 | NO
67 | FLOT1 | FLOT1 | FLOT1 | 8878 | 0.0047 | 0.17 | NO
68 | PPP1CA | PPP1CA | PPP1CA | 9002 | 0.0028 | 0.16 | NO
69 | INSR | INSR | INSR | 9066 | 0.0018 | 0.16 | NO
70 | HK1 | HK1 | HK1 | 9313 | -0.0024 | 0.15 | NO
71 | IRS1 | IRS1 | IRS1 | 9458 | -0.0047 | 0.14 | NO
72 | SOS1 | SOS1 | SOS1 | 9503 | -0.0053 | 0.14 | NO
73 | MTOR | MTOR | MTOR | 9624 | -0.0072 | 0.13 | NO
74 | ARAF | ARAF | ARAF | 9676 | -0.008 | 0.13 | NO
75 | GRB2 | GRB2 | GRB2 | 9816 | -0.01 | 0.12 | NO
76 | PIK3R5 | PIK3R5 | PIK3R5 | 9864 | -0.011 | 0.12 | NO
77 | FLOT2 | FLOT2 | FLOT2 | 10049 | -0.014 | 0.11 | NO
78 | ACACB | ACACB | ACACB | 10144 | -0.016 | 0.1 | NO
79 | MKNK2 | MKNK2 | MKNK2 | 10265 | -0.017 | 0.099 | NO
80 | RHEB | RHEB | RHEB | 10465 | -0.02 | 0.089 | NO
81 | PPP1CB | PPP1CB | PPP1CB | 10566 | -0.022 | 0.085 | NO
82 | PPP1R3D | PPP1R3D | PPP1R3D | 10722 | -0.024 | 0.078 | NO
83 | EXOC7 | EXOC7 | EXOC7 | 10745 | -0.025 | 0.078 | NO
84 | PRKAB1 | PRKAB1 | PRKAB1 | 10884 | -0.027 | 0.071 | NO
85 | SOCS2 | SOCS2 | SOCS2 | 10917 | -0.027 | 0.071 | NO
86 | CRK | CRK | CRK | 11094 | -0.031 | 0.062 | NO
87 | CALM1 | CALM1 | CALM1 | 11272 | -0.034 | 0.054 | NO
88 | CALM2 | CALM2 | CALM2 | 11656 | -0.041 | 0.036 | NO
89 | BAD | BAD | BAD | 11711 | -0.042 | 0.034 | NO
90 | SOS2 | SOS2 | SOS2 | 11737 | -0.042 | 0.035 | NO
91 | CALM3 | CALM3 | CALM3 | 11765 | -0.043 | 0.036 | NO
92 | PHKG2 | PHKG2 | PHKG2 | 11882 | -0.045 | 0.031 | NO
93 | INPP5D | INPP5D | INPP5D | 12252 | -0.052 | 0.014 | NO
94 | FASN | FASN | FASN | 12259 | -0.053 | 0.016 | NO
95 | LIPE | LIPE | LIPE | 12514 | -0.058 | 0.0044 | NO
96 | PRKCI | PRKCI | PRKCI | 12865 | -0.066 | -0.012 | NO
97 | MAPK3 | MAPK3 | MAPK3 | 12916 | -0.068 | -0.011 | NO
98 | KRAS | KRAS | KRAS | 12975 | -0.069 | -0.011 | NO
99 | ACACA | ACACA | ACACA | 13009 | -0.07 | -0.01 | NO
100 | IKBKB | IKBKB | IKBKB | 13030 | -0.07 | -0.008 | NO
101 | PRKAA1 | PRKAA1 | PRKAA1 | 13092 | -0.071 | -0.0082 | NO
102 | PDE3A | PDE3A | PDE3A | 13211 | -0.074 | -0.011 | NO
103 | PRKX | PRKX | PRKX | 13247 | -0.075 | -0.0098 | NO
104 | PHKA2 | PHKA2 | PHKA2 | 13329 | -0.077 | -0.011 | NO
105 | SOCS3 | SOCS3 | SOCS3 | 13471 | -0.081 | -0.015 | NO
106 | SOCS4 | SOCS4 | SOCS4 | 13493 | -0.082 | -0.012 | NO
107 | MAPK9 | MAPK9 | MAPK9 | 13672 | -0.087 | -0.018 | NO
108 | TRIP10 | TRIP10 | TRIP10 | 13724 | -0.088 | -0.017 | NO
109 | SHC3 | SHC3 | SHC3 | 14450 | -0.11 | -0.051 | NO
110 | EIF4E | EIF4E | EIF4E | 14566 | -0.12 | -0.052 | NO
111 | IRS2 | IRS2 | IRS2 | 14649 | -0.12 | -0.052 | NO
112 | PHKB | PHKB | PHKB | 14890 | -0.13 | -0.059 | NO
113 | BRAF | BRAF | BRAF | 15248 | -0.14 | -0.072 | NO
114 | SREBF1 | SREBF1 | SREBF1 | 15372 | -0.15 | -0.072 | NO
115 | PYGB | PYGB | PYGB | 15382 | -0.15 | -0.066 | NO
116 | PIK3R3 | PIK3R3 | PIK3R3 | 15423 | -0.15 | -0.061 | NO
117 | CALML3 | CALML3 | CALML3 | 15547 | -0.16 | -0.061 | NO
118 | SOCS1 | SOCS1 | SOCS1 | 15548 | -0.16 | -0.054 | NO
119 | AKT3 | AKT3 | AKT3 | 15743 | -0.17 | -0.057 | NO
120 | PCK2 | PCK2 | PCK2 | 15966 | -0.18 | -0.061 | NO
121 | MAPK10 | MAPK10 | MAPK10 | 16136 | -0.19 | -0.062 | NO
122 | PIK3CD | PIK3CD | PIK3CD | 16632 | -0.22 | -0.079 | NO
123 | PRKAG2 | PRKAG2 | PRKAG2 | 16817 | -0.24 | -0.078 | NO
124 | FBP1 | FBP1 | FBP1 | 17127 | -0.27 | -0.083 | NO
125 | PTPRF | PTPRF | PTPRF | 17189 | -0.27 | -0.074 | NO
126 | PIK3CB | PIK3CB | PIK3CB | 17255 | -0.28 | -0.065 | NO
127 | PRKCZ | PRKCZ | PRKCZ | 17333 | -0.29 | -0.056 | NO
128 | PRKAR2B | PRKAR2B | PRKAR2B | 17996 | -0.41 | -0.074 | NO
129 | PCK1 | PCK1 | PCK1 | 18029 | -0.42 | -0.057 | NO
130 | IRS4 | IRS4 | IRS4 | 18184 | -0.46 | -0.045 | NO
131 | CALML5 | CALML5 | CALML5 | 18544 | -0.66 | -0.035 | NO
132 | CBLC | CBLC | CBLC | 18644 | -0.91 | 0.00011 | 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 HDAC PATHWAY.

Figure S10. 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 INTEGRIN 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 | ACTA1 | ACTA1 | ACTA1 | 52 | 1.6 | 0.2 | YES
2 | TNNI1 | TNNI1 | TNNI1 | 68 | 1.4 | 0.39 | YES
3 | CHRNA1 | CHRNA1 | CHRNA1 | 120 | 1.2 | 0.54 | YES
4 | RYR2 | RYR2 | RYR2 | 491 | 0.59 | 0.6 | YES
5 | PRKG1 | PRKG1 | PRKG1 | 512 | 0.57 | 0.67 | YES
6 | PDE2A | PDE2A | PDE2A | 779 | 0.44 | 0.71 | YES
7 | PRKAR2A | PRKAR2A | PRKAR2A | 2472 | 0.19 | 0.65 | NO
8 | PRKAR1B | PRKAR1B | PRKAR1B | 2826 | 0.16 | 0.65 | NO
9 | PRKAR1A | PRKAR1A | PRKAR1A | 4152 | 0.1 | 0.59 | NO
10 | PRKG2 | PRKG2 | PRKG2 | 5351 | 0.068 | 0.54 | NO
11 | BDKRB2 | BDKRB2 | BDKRB2 | 5511 | 0.064 | 0.53 | NO
12 | PDE3B | PDE3B | PDE3B | 5910 | 0.056 | 0.52 | NO
13 | PRKACB | PRKACB | PRKACB | 7201 | 0.032 | 0.46 | NO
14 | AKT1 | AKT1 | AKT1 | 8522 | 0.011 | 0.39 | NO
15 | HSP90AA1 | HSP90AA1 | HSP90AA1 | 9375 | -0.0032 | 0.34 | NO
16 | SLC7A1 | SLC7A1 | SLC7A1 | 9392 | -0.0035 | 0.34 | NO
17 | FLT1 | FLT1 | FLT1 | 9849 | -0.011 | 0.32 | NO
18 | CALM1 | CALM1 | CALM1 | 11272 | -0.034 | 0.24 | NO
19 | CALM2 | CALM2 | CALM2 | 11656 | -0.041 | 0.23 | NO
20 | CALM3 | CALM3 | CALM3 | 11765 | -0.043 | 0.23 | NO
21 | PDE3A | PDE3A | PDE3A | 13211 | -0.074 | 0.16 | NO
22 | NOS3 | NOS3 | NOS3 | 13214 | -0.074 | 0.17 | NO
23 | KDR | KDR | KDR | 13241 | -0.075 | 0.18 | NO
24 | FLT4 | FLT4 | FLT4 | 13424 | -0.08 | 0.18 | NO
25 | KNG1 | KNG1 | KNG1 | 14167 | -0.1 | 0.15 | NO
26 | VEGFA | VEGFA | VEGFA | 14629 | -0.12 | 0.14 | NO
27 | CHRM1 | CHRM1 | CHRM1 | 15321 | -0.15 | 0.12 | NO
28 | PRKAR2B | PRKAR2B | PRKAR2B | 17996 | -0.41 | 0.035 | 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 INTEGRIN PATHWAY.

Figure S12. Get High-res Image For the top 5 core enriched genes in the pathway: BIOCARTA INTEGRIN 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 CREB 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 | CACNA1S | CACNA1S | CACNA1S | 18 | 1.8 | 0.054 | YES
2 | SGCA | SGCA | SGCA | 21 | 1.8 | 0.11 | YES
3 | CACNG1 | CACNG1 | CACNG1 | 36 | 1.7 | 0.16 | YES
4 | ACTC1 | ACTC1 | ACTC1 | 51 | 1.6 | 0.2 | YES
5 | TNNT2 | TNNT2 | TNNT2 | 63 | 1.5 | 0.25 | YES
6 | TTN | TTN | TTN | 73 | 1.4 | 0.29 | YES
7 | SGCG | SGCG | SGCG | 84 | 1.4 | 0.33 | YES
8 | MYH7 | MYH7 | MYH7 | 90 | 1.3 | 0.37 | YES
9 | TNNC1 | TNNC1 | TNNC1 | 94 | 1.3 | 0.41 | YES
10 | DES | DES | DES | 133 | 1.1 | 0.44 | YES
11 | MYL3 | MYL3 | MYL3 | 150 | 1.1 | 0.47 | YES
12 | MYH6 | MYH6 | MYH6 | 157 | 1 | 0.5 | YES
13 | MYL2 | MYL2 | MYL2 | 179 | 0.96 | 0.53 | YES
14 | CACNG6 | CACNG6 | CACNG6 | 188 | 0.92 | 0.56 | YES
15 | CACNB1 | CACNB1 | CACNB1 | 465 | 0.61 | 0.56 | YES
16 | RYR2 | RYR2 | RYR2 | 491 | 0.59 | 0.58 | YES
17 | LAMA2 | LAMA2 | LAMA2 | 516 | 0.57 | 0.59 | YES
18 | CACNA2D1 | CACNA2D1 | CACNA2D1 | 640 | 0.51 | 0.6 | YES
19 | MYBPC3 | MYBPC3 | MYBPC3 | 678 | 0.49 | 0.61 | YES
20 | SGCD | SGCD | SGCD | 697 | 0.48 | 0.63 | YES
21 | CACNA2D4 | CACNA2D4 | CACNA2D4 | 764 | 0.45 | 0.64 | YES
22 | TPM2 | TPM2 | TPM2 | 808 | 0.44 | 0.65 | YES
23 | PRKAA2 | PRKAA2 | PRKAA2 | 971 | 0.39 | 0.65 | YES
24 | ITGA7 | ITGA7 | ITGA7 | 985 | 0.39 | 0.66 | YES
25 | TNNI3 | TNNI3 | TNNI3 | 1348 | 0.32 | 0.65 | NO
26 | ITGA4 | ITGA4 | ITGA4 | 1509 | 0.29 | 0.65 | NO
27 | TGFB2 | TGFB2 | TGFB2 | 1749 | 0.26 | 0.65 | NO
28 | ATP2A2 | ATP2A2 | ATP2A2 | 1959 | 0.24 | 0.64 | NO
29 | CACNA2D2 | CACNA2D2 | CACNA2D2 | 2053 | 0.23 | 0.64 | NO
30 | TPM1 | TPM1 | TPM1 | 2088 | 0.22 | 0.65 | NO
31 | TGFB3 | TGFB3 | TGFB3 | 2217 | 0.21 | 0.65 | NO
32 | PRKAB2 | PRKAB2 | PRKAB2 | 2442 | 0.19 | 0.64 | NO
33 | SGCB | SGCB | SGCB | 2711 | 0.17 | 0.63 | NO
34 | CACNG8 | CACNG8 | CACNG8 | 2822 | 0.16 | 0.63 | NO
35 | IGF1 | IGF1 | IGF1 | 2833 | 0.16 | 0.64 | NO
36 | IL6 | IL6 | IL6 | 3025 | 0.15 | 0.63 | NO
37 | DAG1 | DAG1 | DAG1 | 3086 | 0.14 | 0.63 | NO
38 | CACNB4 | CACNB4 | CACNB4 | 3232 | 0.14 | 0.63 | NO
39 | ITGB6 | ITGB6 | ITGB6 | 3551 | 0.12 | 0.62 | NO
40 | ITGA6 | ITGA6 | ITGA6 | 4054 | 0.1 | 0.59 | NO
41 | ITGA9 | ITGA9 | ITGA9 | 4183 | 0.098 | 0.59 | NO
42 | ITGA5 | ITGA5 | ITGA5 | 4487 | 0.09 | 0.57 | NO
43 | TPM3 | TPM3 | TPM3 | 4561 | 0.087 | 0.57 | NO
44 | DMD | DMD | DMD | 4633 | 0.086 | 0.57 | NO
45 | PRKAG1 | PRKAG1 | PRKAG1 | 4934 | 0.078 | 0.56 | NO
46 | LMNA | LMNA | LMNA | 6759 | 0.04 | 0.46 | NO
47 | CACNB2 | CACNB2 | CACNB2 | 6909 | 0.037 | 0.45 | NO
48 | EMD | EMD | EMD | 9189 | -0.00032 | 0.33 | NO
49 | ITGA11 | ITGA11 | ITGA11 | 9821 | -0.01 | 0.3 | NO
50 | PRKAB1 | PRKAB1 | PRKAB1 | 10884 | -0.027 | 0.24 | NO
51 | ITGB3 | ITGB3 | ITGB3 | 11203 | -0.032 | 0.22 | NO
52 | CACNB3 | CACNB3 | CACNB3 | 11639 | -0.04 | 0.2 | NO
53 | CACNG4 | CACNG4 | CACNG4 | 12260 | -0.053 | 0.17 | NO
54 | CACNA1F | CACNA1F | CACNA1F | 12665 | -0.062 | 0.15 | NO
55 | ITGB1 | ITGB1 | ITGB1 | 12942 | -0.068 | 0.14 | NO
56 | PRKAA1 | PRKAA1 | PRKAA1 | 13092 | -0.071 | 0.13 | NO
57 | CACNA1C | CACNA1C | CACNA1C | 13154 | -0.073 | 0.13 | NO
58 | CACNG7 | CACNG7 | CACNG7 | 13331 | -0.077 | 0.12 | NO
59 | ACTB | ACTB | ACTB | 13571 | -0.084 | 0.11 | NO
60 | ACTG1 | ACTG1 | ACTG1 | 13739 | -0.089 | 0.11 | NO
61 | TPM4 | TPM4 | TPM4 | 13770 | -0.09 | 0.11 | NO
62 | ITGB5 | ITGB5 | ITGB5 | 14525 | -0.11 | 0.07 | NO
63 | ITGA2B | ITGA2B | ITGA2B | 14891 | -0.13 | 0.054 | NO
64 | ITGA1 | ITGA1 | ITGA1 | 15082 | -0.14 | 0.048 | NO
65 | ITGA8 | ITGA8 | ITGA8 | 15112 | -0.14 | 0.051 | NO
66 | CACNA2D3 | CACNA2D3 | CACNA2D3 | 15685 | -0.16 | 0.025 | NO
67 | TGFB1 | TGFB1 | TGFB1 | 15780 | -0.17 | 0.025 | NO
68 | CACNG5 | CACNG5 | CACNG5 | 16200 | -0.19 | 0.0079 | NO
69 | ITGA3 | ITGA3 | ITGA3 | 16265 | -0.2 | 0.01 | NO
70 | ACE | ACE | ACE | 16393 | -0.21 | 0.0097 | NO
71 | CACNA1D | CACNA1D | CACNA1D | 16681 | -0.23 | 0.0011 | NO
72 | ITGAV | ITGAV | ITGAV | 16738 | -0.23 | 0.005 | NO
73 | PRKAG2 | PRKAG2 | PRKAG2 | 16817 | -0.24 | 0.0079 | NO
74 | ITGA10 | ITGA10 | ITGA10 | 16990 | -0.25 | 0.0062 | NO
75 | SLC8A1 | SLC8A1 | SLC8A1 | 17299 | -0.29 | -0.0017 | NO
76 | ITGB7 | ITGB7 | ITGB7 | 17855 | -0.38 | -0.02 | NO
77 | ITGB8 | ITGB8 | ITGB8 | 18117 | -0.44 | -0.021 | NO
78 | ITGA2 | ITGA2 | ITGA2 | 18118 | -0.44 | -0.0078 | NO
79 | TNF | TNF | TNF | 18140 | -0.45 | 0.0045 | NO
80 | ITGB4 | ITGB4 | ITGB4 | 18615 | -0.76 | 0.0017 | 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 CREB PATHWAY.

Figure S14. Get High-res Image For the top 5 core enriched genes in the pathway: BIOCARTA CREB 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 PROPANOATE METABOLISM

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 | CAMK2A | CAMK2A | CAMK2A | 71 | 1.4 | 0.1 | YES
2 | CALML6 | CALML6 | CALML6 | 98 | 1.3 | 0.2 | YES
3 | CPEB1 | CPEB1 | CPEB1 | 420 | 0.64 | 0.23 | YES
4 | CAMK2B | CAMK2B | CAMK2B | 664 | 0.5 | 0.25 | YES
5 | ADCY2 | ADCY2 | ADCY2 | 1413 | 0.31 | 0.23 | YES
6 | ADCY1 | ADCY1 | ADCY1 | 1521 | 0.29 | 0.25 | YES
7 | ADCY9 | ADCY9 | ADCY9 | 1536 | 0.29 | 0.27 | YES
8 | ADCY5 | ADCY5 | ADCY5 | 1608 | 0.28 | 0.28 | YES
9 | SMC1B | SMC1B | SMC1B | 1733 | 0.26 | 0.3 | YES
10 | MOS | MOS | MOS | 1852 | 0.25 | 0.31 | YES
11 | CHP2 | CHP2 | CHP2 | 2059 | 0.23 | 0.32 | YES
12 | FBXO43 | FBXO43 | FBXO43 | 2391 | 0.2 | 0.31 | YES
13 | MAPK12 | MAPK12 | MAPK12 | 2446 | 0.19 | 0.32 | YES
14 | PRKACA | PRKACA | PRKACA | 2457 | 0.19 | 0.34 | YES
15 | STAG3 | STAG3 | STAG3 | 2494 | 0.19 | 0.35 | YES
16 | IGF1R | IGF1R | IGF1R | 2608 | 0.18 | 0.36 | YES
17 | MAP2K1 | MAP2K1 | MAP2K1 | 2614 | 0.18 | 0.37 | YES
18 | CAMK2D | CAMK2D | CAMK2D | 2622 | 0.18 | 0.38 | YES
19 | IGF1 | IGF1 | IGF1 | 2833 | 0.16 | 0.38 | YES
20 | BTRC | BTRC | BTRC | 3170 | 0.14 | 0.38 | NO
21 | CCNE1 | CCNE1 | CCNE1 | 3676 | 0.12 | 0.36 | NO
22 | ANAPC13 | ANAPC13 | ANAPC13 | 3944 | 0.11 | 0.35 | NO
23 | PPP3CB | PPP3CB | PPP3CB | 3987 | 0.1 | 0.36 | NO
24 | MAD2L2 | MAD2L2 | MAD2L2 | 4257 | 0.096 | 0.35 | NO
25 | SMC3 | SMC3 | SMC3 | 4932 | 0.078 | 0.32 | NO
26 | PLK1 | PLK1 | PLK1 | 5610 | 0.061 | 0.29 | NO
27 | FBXW11 | FBXW11 | FBXW11 | 5766 | 0.058 | 0.28 | NO
28 | PTTG2 | PTTG2 | PTTG2 | 5849 | 0.057 | 0.28 | NO
29 | CUL1 | CUL1 | CUL1 | 6000 | 0.054 | 0.28 | NO
30 | YWHAG | YWHAG | YWHAG | 6340 | 0.048 | 0.26 | NO
31 | ANAPC7 | ANAPC7 | ANAPC7 | 6419 | 0.046 | 0.26 | NO
32 | PPP3R1 | PPP3R1 | PPP3R1 | 6619 | 0.042 | 0.25 | NO
33 | ANAPC11 | ANAPC11 | ANAPC11 | 6917 | 0.037 | 0.24 | NO
34 | PPP1CC | PPP1CC | PPP1CC | 7037 | 0.035 | 0.24 | NO
35 | PRKACB | PRKACB | PRKACB | 7201 | 0.032 | 0.23 | NO
36 | BUB1 | BUB1 | BUB1 | 7453 | 0.028 | 0.22 | NO
37 | PPP3CA | PPP3CA | PPP3CA | 7555 | 0.026 | 0.22 | NO
38 | PPP2R5C | PPP2R5C | PPP2R5C | 7811 | 0.022 | 0.2 | NO
39 | MAPK1 | MAPK1 | MAPK1 | 8189 | 0.016 | 0.18 | NO
40 | SLK | SLK | SLK | 8396 | 0.013 | 0.18 | NO
41 | RPS6KA6 | RPS6KA6 | RPS6KA6 | 8606 | 0.0097 | 0.16 | NO
42 | YWHAZ | YWHAZ | YWHAZ | 8750 | 0.0072 | 0.16 | NO
43 | FBXO5 | FBXO5 | FBXO5 | 8775 | 0.0068 | 0.16 | NO
44 | AURKA | AURKA | AURKA | 8854 | 0.0053 | 0.15 | NO
45 | CDC27 | CDC27 | CDC27 | 8941 | 0.0037 | 0.15 | NO
46 | PPP1CA | PPP1CA | PPP1CA | 9002 | 0.0028 | 0.14 | NO
47 | ANAPC1 | ANAPC1 | ANAPC1 | 9015 | 0.0026 | 0.14 | NO
48 | CDC20 | CDC20 | CDC20 | 9016 | 0.0026 | 0.14 | NO
49 | SKP1 | SKP1 | SKP1 | 9106 | 0.001 | 0.14 | NO
50 | CDC23 | CDC23 | CDC23 | 9325 | -0.0025 | 0.13 | NO
51 | RBX1 | RBX1 | RBX1 | 9330 | -0.0026 | 0.13 | NO
52 | PPP2R5D | PPP2R5D | PPP2R5D | 9540 | -0.0058 | 0.12 | NO
53 | ANAPC5 | ANAPC5 | ANAPC5 | 9627 | -0.0072 | 0.11 | NO
54 | ADCY7 | ADCY7 | ADCY7 | 9648 | -0.0076 | 0.11 | NO
55 | PKMYT1 | PKMYT1 | PKMYT1 | 9854 | -0.011 | 0.1 | NO
56 | CDC16 | CDC16 | CDC16 | 9888 | -0.011 | 0.1 | NO
57 | CDK1 | CDK1 | CDK1 | 9957 | -0.013 | 0.099 | NO
58 | CDC26 | CDC26 | CDC26 | 9997 | -0.013 | 0.098 | NO
59 | CAMK2G | CAMK2G | CAMK2G | 10055 | -0.014 | 0.096 | NO
60 | ITPR1 | ITPR1 | ITPR1 | 10275 | -0.018 | 0.085 | NO
61 | PPP2CA | PPP2CA | PPP2CA | 10325 | -0.018 | 0.084 | NO
62 | ANAPC4 | ANAPC4 | ANAPC4 | 10340 | -0.019 | 0.084 | NO
63 | PPP2CB | PPP2CB | PPP2CB | 10431 | -0.02 | 0.081 | NO
64 | PPP2R1A | PPP2R1A | PPP2R1A | 10522 | -0.021 | 0.078 | NO
65 | PPP1CB | PPP1CB | PPP1CB | 10566 | -0.022 | 0.077 | NO
66 | YWHAE | YWHAE | YWHAE | 10594 | -0.022 | 0.077 | NO
67 | PPP2R5E | PPP2R5E | PPP2R5E | 10631 | -0.023 | 0.077 | NO
68 | CDC25C | CDC25C | CDC25C | 10679 | -0.024 | 0.076 | NO
69 | SPDYA | SPDYA | SPDYA | 10724 | -0.024 | 0.076 | NO
70 | PPP3CC | PPP3CC | PPP3CC | 10938 | -0.028 | 0.066 | NO
71 | ESPL1 | ESPL1 | ESPL1 | 10994 | -0.029 | 0.066 | NO
72 | CALM1 | CALM1 | CALM1 | 11272 | -0.034 | 0.053 | NO
73 | YWHAQ | YWHAQ | YWHAQ | 11471 | -0.038 | 0.045 | NO
74 | CCNB2 | CCNB2 | CCNB2 | 11539 | -0.038 | 0.044 | NO
75 | CALM2 | CALM2 | CALM2 | 11656 | -0.041 | 0.041 | NO
76 | SMC1A | SMC1A | SMC1A | 11665 | -0.041 | 0.044 | NO
77 | CALM3 | CALM3 | CALM3 | 11765 | -0.043 | 0.042 | NO
78 | YWHAB | YWHAB | YWHAB | 11792 | -0.043 | 0.043 | NO
79 | SGOL1 | SGOL1 | SGOL1 | 11963 | -0.046 | 0.038 | NO
80 | RPS6KA3 | RPS6KA3 | RPS6KA3 | 11985 | -0.047 | 0.04 | NO
81 | CDK2 | CDK2 | CDK2 | 12033 | -0.048 | 0.041 | NO
82 | CHP | CHP | CHP | 12098 | -0.049 | 0.041 | NO
83 | ANAPC2 | ANAPC2 | ANAPC2 | 12132 | -0.05 | 0.043 | NO
84 | MAD2L1 | MAD2L1 | MAD2L1 | 12201 | -0.051 | 0.043 | NO
85 | RPS6KA2 | RPS6KA2 | RPS6KA2 | 12206 | -0.051 | 0.047 | NO
86 | PPP2R1B | PPP2R1B | PPP2R1B | 12335 | -0.054 | 0.044 | NO
87 | YWHAH | YWHAH | YWHAH | 12361 | -0.055 | 0.047 | NO
88 | PPP2R5A | PPP2R5A | PPP2R5A | 12640 | -0.061 | 0.036 | NO
89 | ANAPC10 | ANAPC10 | ANAPC10 | 12752 | -0.064 | 0.035 | NO
90 | PPP3R2 | PPP3R2 | PPP3R2 | 12761 | -0.064 | 0.039 | NO
91 | MAPK3 | MAPK3 | MAPK3 | 12916 | -0.068 | 0.036 | NO
92 | PPP2R5B | PPP2R5B | PPP2R5B | 13113 | -0.072 | 0.031 | NO
93 | PRKX | PRKX | PRKX | 13247 | -0.075 | 0.029 | NO
94 | ADCY6 | ADCY6 | ADCY6 | 13267 | -0.076 | 0.034 | NO
95 | PGR | PGR | PGR | 13618 | -0.085 | 0.021 | NO
96 | AR | AR | AR | 14270 | -0.1 | -0.0062 | NO
97 | CCNB1 | CCNB1 | CCNB1 | 14428 | -0.11 | -0.0065 | NO
98 | PTTG1 | PTTG1 | PTTG1 | 14559 | -0.11 | -0.0051 | NO
99 | CALML3 | CALML3 | CALML3 | 15547 | -0.16 | -0.047 | NO
100 | ITPR2 | ITPR2 | ITPR2 | 15935 | -0.18 | -0.054 | NO
101 | SPDYC | SPDYC | SPDYC | 16132 | -0.19 | -0.051 | NO
102 | ADCY4 | ADCY4 | ADCY4 | 16309 | -0.2 | -0.046 | NO
103 | ADCY8 | ADCY8 | ADCY8 | 16454 | -0.21 | -0.038 | NO
104 | CCNE2 | CCNE2 | CCNE2 | 16457 | -0.21 | -0.022 | NO
105 | RPS6KA1 | RPS6KA1 | RPS6KA1 | 17543 | -0.32 | -0.057 | NO
106 | REC8 | REC8 | REC8 | 17861 | -0.38 | -0.046 | NO
107 | ITPR3 | ITPR3 | ITPR3 | 18360 | -0.52 | -0.034 | NO
108 | CALML5 | CALML5 | CALML5 | 18544 | -0.66 | 0.0055 | 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: KEGG PROPANOATE METABOLISM.

Figure S16. Get High-res Image For the top 5 core enriched genes in the pathway: KEGG PROPANOATE 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 RNA DEGRADATION

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 | CACNA1S | CACNA1S | CACNA1S | 18 | 1.8 | 0.052 | YES
2 | SGCA | SGCA | SGCA | 21 | 1.8 | 0.1 | YES
3 | CACNG1 | CACNG1 | CACNG1 | 36 | 1.7 | 0.15 | YES
4 | ACTC1 | ACTC1 | ACTC1 | 51 | 1.6 | 0.2 | YES
5 | TNNT2 | TNNT2 | TNNT2 | 63 | 1.5 | 0.24 | YES
6 | TTN | TTN | TTN | 73 | 1.4 | 0.28 | YES
7 | SGCG | SGCG | SGCG | 84 | 1.4 | 0.32 | YES
8 | MYH7 | MYH7 | MYH7 | 90 | 1.3 | 0.36 | YES
9 | TNNC1 | TNNC1 | TNNC1 | 94 | 1.3 | 0.4 | YES
10 | DES | DES | DES | 133 | 1.1 | 0.43 | YES
11 | MYL3 | MYL3 | MYL3 | 150 | 1.1 | 0.46 | YES
12 | MYH6 | MYH6 | MYH6 | 157 | 1 | 0.49 | YES
13 | MYL2 | MYL2 | MYL2 | 179 | 0.96 | 0.51 | YES
14 | CACNG6 | CACNG6 | CACNG6 | 188 | 0.92 | 0.54 | YES
15 | CACNB1 | CACNB1 | CACNB1 | 465 | 0.61 | 0.54 | YES
16 | RYR2 | RYR2 | RYR2 | 491 | 0.59 | 0.56 | YES
17 | LAMA2 | LAMA2 | LAMA2 | 516 | 0.57 | 0.57 | YES
18 | CACNA2D1 | CACNA2D1 | CACNA2D1 | 640 | 0.51 | 0.58 | YES
19 | MYBPC3 | MYBPC3 | MYBPC3 | 678 | 0.49 | 0.59 | YES
20 | SGCD | SGCD | SGCD | 697 | 0.48 | 0.61 | YES
21 | CACNA2D4 | CACNA2D4 | CACNA2D4 | 764 | 0.45 | 0.62 | YES
22 | TPM2 | TPM2 | TPM2 | 808 | 0.44 | 0.63 | YES
23 | ITGA7 | ITGA7 | ITGA7 | 985 | 0.39 | 0.63 | YES
24 | TNNI3 | TNNI3 | TNNI3 | 1348 | 0.32 | 0.62 | YES
25 | ADCY2 | ADCY2 | ADCY2 | 1413 | 0.31 | 0.62 | YES
26 | ITGA4 | ITGA4 | ITGA4 | 1509 | 0.29 | 0.63 | YES
27 | ADCY1 | ADCY1 | ADCY1 | 1521 | 0.29 | 0.64 | YES
28 | ADCY9 | ADCY9 | ADCY9 | 1536 | 0.29 | 0.64 | YES
29 | ADCY5 | ADCY5 | ADCY5 | 1608 | 0.28 | 0.65 | YES
30 | TGFB2 | TGFB2 | TGFB2 | 1749 | 0.26 | 0.65 | YES
31 | ATP2A2 | ATP2A2 | ATP2A2 | 1959 | 0.24 | 0.64 | YES
32 | CACNA2D2 | CACNA2D2 | CACNA2D2 | 2053 | 0.23 | 0.64 | YES
33 | TPM1 | TPM1 | TPM1 | 2088 | 0.22 | 0.65 | YES
34 | TGFB3 | TGFB3 | TGFB3 | 2217 | 0.21 | 0.65 | NO
35 | PRKACA | PRKACA | PRKACA | 2457 | 0.19 | 0.64 | NO
36 | SGCB | SGCB | SGCB | 2711 | 0.17 | 0.63 | NO
37 | CACNG8 | CACNG8 | CACNG8 | 2822 | 0.16 | 0.63 | NO
38 | IGF1 | IGF1 | IGF1 | 2833 | 0.16 | 0.64 | NO
39 | DAG1 | DAG1 | DAG1 | 3086 | 0.14 | 0.63 | NO
40 | CACNB4 | CACNB4 | CACNB4 | 3232 | 0.14 | 0.62 | NO
41 | ITGB6 | ITGB6 | ITGB6 | 3551 | 0.12 | 0.61 | NO
42 | ITGA6 | ITGA6 | ITGA6 | 4054 | 0.1 | 0.58 | NO
43 | ITGA9 | ITGA9 | ITGA9 | 4183 | 0.098 | 0.58 | NO
44 | ITGA5 | ITGA5 | ITGA5 | 4487 | 0.09 | 0.57 | NO
45 | TPM3 | TPM3 | TPM3 | 4561 | 0.087 | 0.56 | NO
46 | DMD | DMD | DMD | 4633 | 0.086 | 0.56 | NO
47 | GNAS | GNAS | GNAS | 6664 | 0.042 | 0.46 | NO
48 | LMNA | LMNA | LMNA | 6759 | 0.04 | 0.45 | NO
49 | CACNB2 | CACNB2 | CACNB2 | 6909 | 0.037 | 0.44 | NO
50 | PRKACB | PRKACB | PRKACB | 7201 | 0.032 | 0.43 | NO
51 | ADRB1 | ADRB1 | ADRB1 | 8371 | 0.013 | 0.37 | NO
52 | EMD | EMD | EMD | 9189 | -0.00032 | 0.32 | NO
53 | ADCY7 | ADCY7 | ADCY7 | 9648 | -0.0076 | 0.3 | NO
54 | ITGA11 | ITGA11 | ITGA11 | 9821 | -0.01 | 0.29 | NO
55 | ITGB3 | ITGB3 | ITGB3 | 11203 | -0.032 | 0.22 | NO
56 | CACNB3 | CACNB3 | CACNB3 | 11639 | -0.04 | 0.19 | NO
57 | CACNG4 | CACNG4 | CACNG4 | 12260 | -0.053 | 0.16 | NO
58 | CACNA1F | CACNA1F | CACNA1F | 12665 | -0.062 | 0.14 | NO
59 | ITGB1 | ITGB1 | ITGB1 | 12942 | -0.068 | 0.13 | NO
60 | CACNA1C | CACNA1C | CACNA1C | 13154 | -0.073 | 0.12 | NO
61 | PRKX | PRKX | PRKX | 13247 | -0.075 | 0.12 | NO
62 | ADCY6 | ADCY6 | ADCY6 | 13267 | -0.076 | 0.12 | NO
63 | CACNG7 | CACNG7 | CACNG7 | 13331 | -0.077 | 0.12 | NO
64 | ACTB | ACTB | ACTB | 13571 | -0.084 | 0.11 | NO
65 | ACTG1 | ACTG1 | ACTG1 | 13739 | -0.089 | 0.1 | NO
66 | TPM4 | TPM4 | TPM4 | 13770 | -0.09 | 0.1 | NO
67 | ITGB5 | ITGB5 | ITGB5 | 14525 | -0.11 | 0.064 | NO
68 | ITGA2B | ITGA2B | ITGA2B | 14891 | -0.13 | 0.048 | NO
69 | ITGA1 | ITGA1 | ITGA1 | 15082 | -0.14 | 0.042 | NO
70 | ITGA8 | ITGA8 | ITGA8 | 15112 | -0.14 | 0.045 | NO
71 | CACNA2D3 | CACNA2D3 | CACNA2D3 | 15685 | -0.16 | 0.018 | NO
72 | TGFB1 | TGFB1 | TGFB1 | 15780 | -0.17 | 0.018 | NO
73 | CACNG5 | CACNG5 | CACNG5 | 16200 | -0.19 | 0.0014 | NO
74 | ITGA3 | ITGA3 | ITGA3 | 16265 | -0.2 | 0.0037 | NO
75 | ADCY4 | ADCY4 | ADCY4 | 16309 | -0.2 | 0.0072 | NO
76 | ADCY8 | ADCY8 | ADCY8 | 16454 | -0.21 | 0.0056 | NO
77 | CACNA1D | CACNA1D | CACNA1D | 16681 | -0.23 | 0.000034 | NO
78 | ITGAV | ITGAV | ITGAV | 16738 | -0.23 | 0.0037 | NO
79 | ITGA10 | ITGA10 | ITGA10 | 16990 | -0.25 | -0.0024 | NO
80 | SLC8A1 | SLC8A1 | SLC8A1 | 17299 | -0.29 | -0.011 | NO
81 | ITGB7 | ITGB7 | ITGB7 | 17855 | -0.38 | -0.03 | NO
82 | PLN | PLN | PLN | 17874 | -0.38 | -0.019 | NO
83 | ITGB8 | ITGB8 | ITGB8 | 18117 | -0.44 | -0.02 | NO
84 | ITGA2 | ITGA2 | ITGA2 | 18118 | -0.44 | -0.0066 | NO
85 | TNF | TNF | TNF | 18140 | -0.45 | 0.0052 | NO
86 | ITGB4 | ITGB4 | ITGB4 | 18615 | -0.76 | 0.0017 | 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: KEGG RNA DEGRADATION.

Figure S18. Get High-res Image For the top 5 core enriched genes in the pathway: KEGG RNA 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 MAPK SIGNALING 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 | MYLPF | MYLPF | MYLPF | 16 | 1.8 | 0.047 | YES
2 | ACTN2 | ACTN2 | ACTN2 | 37 | 1.7 | 0.089 | YES
3 | MYH8 | MYH8 | MYH8 | 45 | 1.6 | 0.13 | YES
4 | MYH3 | MYH3 | MYH3 | 48 | 1.6 | 0.17 | YES
5 | MYH7B | MYH7B | MYH7B | 66 | 1.5 | 0.21 | YES
6 | MYH7 | MYH7 | MYH7 | 90 | 1.3 | 0.24 | YES
7 | ACTN3 | ACTN3 | ACTN3 | 108 | 1.2 | 0.28 | YES
8 | MYH2 | MYH2 | MYH2 | 135 | 1.1 | 0.3 | YES
9 | MYH1 | MYH1 | MYH1 | 152 | 1.1 | 0.33 | YES
10 | MYH6 | MYH6 | MYH6 | 157 | 1 | 0.36 | YES
11 | MYL2 | MYL2 | MYL2 | 179 | 0.96 | 0.38 | YES
12 | MYH4 | MYH4 | MYH4 | 182 | 0.95 | 0.4 | YES
13 | MYH13 | MYH13 | MYH13 | 184 | 0.94 | 0.43 | YES
14 | MYL7 | MYL7 | MYL7 | 235 | 0.84 | 0.45 | YES
15 | MYL10 | MYL10 | MYL10 | 252 | 0.82 | 0.47 | YES
16 | MYL5 | MYL5 | MYL5 | 609 | 0.52 | 0.46 | YES
17 | JAM3 | JAM3 | JAM3 | 716 | 0.47 | 0.47 | YES
18 | PRKCB | PRKCB | PRKCB | 1018 | 0.38 | 0.46 | YES
19 | EPB41L3 | EPB41L3 | EPB41L3 | 1147 | 0.36 | 0.46 | YES
20 | IGSF5 | IGSF5 | IGSF5 | 1164 | 0.36 | 0.47 | YES
21 | CSDA | CSDA | CSDA | 1209 | 0.35 | 0.48 | YES
22 | CTNNA3 | CTNNA3 | CTNNA3 | 1397 | 0.31 | 0.48 | NO
23 | MRAS | MRAS | MRAS | 1622 | 0.28 | 0.47 | NO
24 | CLDN15 | CLDN15 | CLDN15 | 1641 | 0.28 | 0.48 | NO
25 | JAM2 | JAM2 | JAM2 | 2264 | 0.21 | 0.45 | NO
26 | MPDZ | MPDZ | MPDZ | 3008 | 0.15 | 0.41 | NO
27 | MYH15 | MYH15 | MYH15 | 3325 | 0.13 | 0.4 | NO
28 | AMOTL1 | AMOTL1 | AMOTL1 | 3501 | 0.12 | 0.39 | NO
29 | MYL9 | MYL9 | MYL9 | 3603 | 0.12 | 0.39 | NO
30 | CSNK2A2 | CSNK2A2 | CSNK2A2 | 3698 | 0.12 | 0.39 | NO
31 | PARD3 | PARD3 | PARD3 | 4004 | 0.1 | 0.38 | NO
32 | NRAS | NRAS | NRAS | 4165 | 0.099 | 0.37 | NO
33 | EXOC3 | EXOC3 | EXOC3 | 4737 | 0.083 | 0.34 | NO
34 | PRKCE | PRKCE | PRKCE | 5225 | 0.07 | 0.32 | NO
35 | AKT2 | AKT2 | AKT2 | 5388 | 0.067 | 0.31 | NO
36 | CLDN19 | CLDN19 | CLDN19 | 5477 | 0.064 | 0.31 | NO
37 | ZAK | ZAK | ZAK | 5485 | 0.064 | 0.31 | NO
38 | CLDN10 | CLDN10 | CLDN10 | 5561 | 0.062 | 0.3 | NO
39 | EPB41L2 | EPB41L2 | EPB41L2 | 5588 | 0.062 | 0.3 | NO
40 | CLDN5 | CLDN5 | CLDN5 | 5723 | 0.059 | 0.3 | NO
41 | LLGL1 | LLGL1 | LLGL1 | 5774 | 0.058 | 0.3 | NO
42 | SPTAN1 | SPTAN1 | SPTAN1 | 6765 | 0.04 | 0.25 | NO
43 | CDK4 | CDK4 | CDK4 | 7011 | 0.035 | 0.23 | NO
44 | CLDN14 | CLDN14 | CLDN14 | 7168 | 0.033 | 0.23 | NO
45 | GNAI1 | GNAI1 | GNAI1 | 7313 | 0.03 | 0.22 | NO
46 | PRKCQ | PRKCQ | PRKCQ | 7346 | 0.03 | 0.22 | NO
47 | GNAI3 | GNAI3 | GNAI3 | 7423 | 0.029 | 0.22 | NO
48 | HCLS1 | HCLS1 | HCLS1 | 7744 | 0.024 | 0.2 | NO
49 | RRAS | RRAS | RRAS | 8058 | 0.019 | 0.18 | NO
50 | TJAP1 | TJAP1 | TJAP1 | 8153 | 0.017 | 0.18 | NO
51 | YES1 | YES1 | YES1 | 8220 | 0.016 | 0.17 | NO
52 | AKT1 | AKT1 | AKT1 | 8522 | 0.011 | 0.16 | NO
53 | CDC42 | CDC42 | CDC42 | 8952 | 0.0036 | 0.14 | NO
54 | RRAS2 | RRAS2 | RRAS2 | 9251 | -0.0015 | 0.12 | NO
55 | PPP2R2D | PPP2R2D | PPP2R2D | 9435 | -0.0041 | 0.11 | NO
56 | CTNNB1 | CTNNB1 | CTNNB1 | 9472 | -0.0049 | 0.11 | NO
57 | CSNK2B | CSNK2B | CSNK2B | 9681 | -0.0081 | 0.096 | NO
58 | RHOA | RHOA | RHOA | 9709 | -0.0086 | 0.095 | NO
59 | PPP2CA | PPP2CA | PPP2CA | 10325 | -0.018 | 0.062 | NO
60 | SRC | SRC | SRC | 10349 | -0.019 | 0.062 | NO
61 | PPP2CB | PPP2CB | PPP2CB | 10431 | -0.02 | 0.058 | NO
62 | MAGI1 | MAGI1 | MAGI1 | 10443 | -0.02 | 0.058 | NO
63 | CSNK2A1 | CSNK2A1 | CSNK2A1 | 10490 | -0.021 | 0.056 | NO
64 | PPP2R1A | PPP2R1A | PPP2R1A | 10522 | -0.021 | 0.054 | NO
65 | VAPA | VAPA | VAPA | 10635 | -0.023 | 0.049 | NO
66 | ASH1L | ASH1L | ASH1L | 10859 | -0.027 | 0.038 | NO
67 | PPP2R2A | PPP2R2A | PPP2R2A | 11225 | -0.033 | 0.019 | NO
68 | EXOC4 | EXOC4 | EXOC4 | 11528 | -0.038 | 0.0035 | NO
69 | EPB41 | EPB41 | EPB41 | 11662 | -0.041 | -0.0026 | NO
70 | MYL12A | MYL12A | MYL12A | 12155 | -0.051 | -0.028 | NO
71 | MAGI3 | MAGI3 | MAGI3 | 12191 | -0.051 | -0.028 | NO
72 | PPP2R1B | PPP2R1B | PPP2R1B | 12335 | -0.054 | -0.035 | NO
73 | SYMPK | SYMPK | SYMPK | 12350 | -0.054 | -0.034 | NO
74 | CASK | CASK | CASK | 12420 | -0.056 | -0.036 | NO
75 | CTTN | CTTN | CTTN | 12474 | -0.057 | -0.038 | NO
76 | MYH10 | MYH10 | MYH10 | 12600 | -0.06 | -0.043 | NO
77 | TJP1 | TJP1 | TJP1 | 12745 | -0.063 | -0.049 | NO
78 | PRKCI | PRKCI | PRKCI | 12865 | -0.066 | -0.054 | NO
79 | KRAS | KRAS | KRAS | 12975 | -0.069 | -0.058 | NO
80 | EPB41L1 | EPB41L1 | EPB41L1 | 13264 | -0.076 | -0.072 | NO
81 | GNAI2 | GNAI2 | GNAI2 | 13545 | -0.083 | -0.084 | NO
82 | ACTB | ACTB | ACTB | 13571 | -0.084 | -0.084 | NO
83 | PTEN | PTEN | PTEN | 13620 | -0.085 | -0.084 | NO
84 | CLDN18 | CLDN18 | CLDN18 | 13728 | -0.088 | -0.088 | NO
85 | ACTG1 | ACTG1 | ACTG1 | 13739 | -0.089 | -0.086 | NO
86 | ACTN4 | ACTN4 | ACTN4 | 13875 | -0.093 | -0.091 | NO
87 | PPP2R2B | PPP2R2B | PPP2R2B | 13954 | -0.095 | -0.092 | NO
88 | MAGI2 | MAGI2 | MAGI2 | 13981 | -0.096 | -0.091 | NO
89 | CTNNA1 | CTNNA1 | CTNNA1 | 14201 | -0.1 | -0.1 | NO
90 | MYL12B | MYL12B | MYL12B | 14213 | -0.1 | -0.098 | NO
91 | MPP5 | MPP5 | MPP5 | 14325 | -0.11 | -0.1 | NO
92 | RAB13 | RAB13 | RAB13 | 14453 | -0.11 | -0.11 | NO
93 | CLDN16 | CLDN16 | CLDN16 | 14686 | -0.12 | -0.12 | NO
94 | ACTN1 | ACTN1 | ACTN1 | 14784 | -0.12 | -0.12 | NO
95 | MLLT4 | MLLT4 | MLLT4 | 15118 | -0.14 | -0.13 | NO
96 | PARD6G | PARD6G | PARD6G | 15169 | -0.14 | -0.13 | NO
97 | CLDN9 | CLDN9 | CLDN9 | 15280 | -0.14 | -0.13 | NO
98 | CLDN1 | CLDN1 | CLDN1 | 15576 | -0.16 | -0.14 | NO
99 | AKT3 | AKT3 | AKT3 | 15743 | -0.17 | -0.15 | NO
100 | MYH14 | MYH14 | MYH14 | 15782 | -0.17 | -0.15 | NO
101 | CLDN20 | CLDN20 | CLDN20 | 15786 | -0.17 | -0.14 | NO
102 | PRKCA | PRKCA | PRKCA | 15797 | -0.17 | -0.14 | NO
103 | PPP2R2C | PPP2R2C | PPP2R2C | 15973 | -0.18 | -0.14 | NO
104 | CLDN11 | CLDN11 | CLDN11 | 15985 | -0.18 | -0.14 | NO
105 | RAB3B | RAB3B | RAB3B | 16068 | -0.18 | -0.14 | NO
106 | PRKCG | PRKCG | PRKCG | 16161 | -0.19 | -0.14 | NO
107 | MYH9 | MYH9 | MYH9 | 16354 | -0.2 | -0.14 | NO
108 | PRKCH | PRKCH | PRKCH | 16421 | -0.21 | -0.14 | NO
109 | PRKCD | PRKCD | PRKCD | 16920 | -0.25 | -0.16 | NO
110 | CLDN2 | CLDN2 | CLDN2 | 17067 | -0.26 | -0.16 | NO
111 | PARD6A | PARD6A | PARD6A | 17108 | -0.26 | -0.16 | NO
112 | PRKCZ | PRKCZ | PRKCZ | 17333 | -0.29 | -0.16 | NO
113 | CLDN6 | CLDN6 | CLDN6 | 17612 | -0.34 | -0.17 | NO
114 | PARD6B | PARD6B | PARD6B | 17857 | -0.38 | -0.17 | NO
115 | MYH11 | MYH11 | MYH11 | 17922 | -0.39 | -0.17 | NO
116 | LLGL2 | LLGL2 | LLGL2 | 18068 | -0.43 | -0.16 | NO
117 | CLDN23 | CLDN23 | CLDN23 | 18079 | -0.43 | -0.15 | NO
118 | F11R | F11R | F11R | 18128 | -0.44 | -0.14 | NO
119 | CLDN8 | CLDN8 | CLDN8 | 18172 | -0.46 | -0.13 | NO
120 | INADL | INADL | INADL | 18191 | -0.46 | -0.12 | NO
121 | CGN | CGN | CGN | 18262 | -0.49 | -0.12 | NO
122 | TJP2 | TJP2 | TJP2 | 18277 | -0.49 | -0.1 | NO
123 | CTNNA2 | CTNNA2 | CTNNA2 | 18298 | -0.5 | -0.091 | NO
124 | OCLN | OCLN | OCLN | 18511 | -0.63 | -0.086 | NO
125 | CLDN3 | CLDN3 | CLDN3 | 18514 | -0.63 | -0.07 | NO
126 | TJP3 | TJP3 | TJP3 | 18580 | -0.7 | -0.055 | NO
127 | CRB3 | CRB3 | CRB3 | 18607 | -0.75 | -0.037 | NO
128 | CLDN7 | CLDN7 | CLDN7 | 18608 | -0.75 | -0.018 | NO
129 | CLDN4 | CLDN4 | CLDN4 | 18612 | -0.75 | 0.0018 | 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: KEGG MAPK SIGNALING PATHWAY.

Figure S20. Get High-res Image For the top 5 core enriched genes in the pathway: KEGG MAPK SIGNALING 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

- up-regulated, please check the list of up-regulated genes

- down-regulated, please check the list of down-regulated genes

Expression level

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

- highly expressed genes, please check the list of high (top 30%) expressed genes

- low expressed genes, please check the list of low (bottom 30%) expressed genes

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

- significantly differently expressed genes by eBayes lm fit, please check the list of significant genes

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
--- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | ---
BIOCARTA FAS PATHWAY | 29 | genes.ES.table | 0.52 | 1.7 | 0.026 | 0.28 | 0.44 | 0.41 | 0.23 | 0.32 | 0 | 0.08
BIOCARTA FCER1 PATHWAY | 37 | genes.ES.table | 0.57 | 1.6 | 0.03 | 0.24 | 0.66 | 0.3 | 0.13 | 0.26 | 0.13 | 0.04
BIOCARTA HIVNEF PATHWAY | 57 | genes.ES.table | 0.44 | 1.7 | 0.022 | 0.38 | 0.36 | 0.32 | 0.22 | 0.25 | 0 | 0.12
BIOCARTA IL2RB PATHWAY | 37 | genes.ES.table | 0.67 | 1.8 | 0.002 | 0.69 | 0.24 | 0.35 | 0.11 | 0.31 | 0 | 0.18
BIOCARTA DEATH PATHWAY | 32 | genes.ES.table | 0.5 | 1.6 | 0.044 | 0.26 | 0.75 | 0.41 | 0.21 | 0.32 | 0.16 | 0.039
BIOCARTA TNFR1 PATHWAY | 28 | genes.ES.table | 0.41 | 1.5 | 0.064 | 0.3 | 0.81 | 0.43 | 0.29 | 0.31 | 0.2 | 0.047
BIOCARTA TOLL PATHWAY | 36 | genes.ES.table | 0.62 | 1.8 | 0.008 | 0.49 | 0.33 | 0.5 | 0.23 | 0.39 | 0 | 0.15
KEGG SELENOAMINO ACID METABOLISM | 25 | genes.ES.table | 0.47 | 1.5 | 0.075 | 0.31 | 0.84 | 0.12 | 0.067 | 0.11 | 0.21 | 0.044
KEGG LYSOSOME | 120 | genes.ES.table | 0.44 | 1.7 | 0.029 | 0.26 | 0.52 | 0.42 | 0.26 | 0.31 | 0.11 | 0.062
KEGG APOPTOSIS | 84 | genes.ES.table | 0.48 | 1.7 | 0.012 | 0.24 | 0.53 | 0.27 | 0.13 | 0.24 | 0.1 | 0.052

genes ES table in pathway: BIOCARTA FAS PATHWAY

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 | SYK | SYK | SYK | 246 | 0.52 | 0.088 | YES
2 | PTPN6 | PTPN6 | PTPN6 | 664 | 0.38 | 0.14 | YES
3 | IL2RB | IL2RB | IL2RB | 678 | 0.38 | 0.21 | YES
4 | FAS | FAS | FAS | 929 | 0.33 | 0.26 | YES
5 | IKZF3 | IKZF3 | IKZF3 | 1011 | 0.32 | 0.32 | YES
6 | IL2RA | IL2RA | IL2RA | 1102 | 0.3 | 0.37 | YES
7 | IL2RG | IL2RG | IL2RG | 1158 | 0.3 | 0.43 | YES
8 | NMI | NMI | NMI | 1218 | 0.29 | 0.48 | YES
9 | PIK3CG | PIK3CG | PIK3CG | 1231 | 0.29 | 0.54 | YES
10 | FASLG | FASLG | FASLG | 1592 | 0.25 | 0.56 | YES
11 | FOS | FOS | FOS | 1646 | 0.24 | 0.61 | YES
12 | PIK3R1 | PIK3R1 | PIK3R1 | 1803 | 0.23 | 0.64 | YES
13 | CFLAR | CFLAR | CFLAR | 2063 | 0.21 | 0.67 | YES
14 | BCL2 | BCL2 | BCL2 | 3460 | 0.12 | 0.62 | NO
15 | SOCS3 | SOCS3 | SOCS3 | 3488 | 0.12 | 0.64 | NO
16 | PPIA | PPIA | PPIA | 5808 | 0.049 | 0.52 | NO
17 | STAT5A | STAT5A | STAT5A | 7233 | 0.022 | 0.45 | NO
18 | MYC | MYC | MYC | 7525 | 0.017 | 0.44 | NO
19 | IRS1 | IRS1 | IRS1 | 7827 | 0.012 | 0.43 | NO
20 | JAK1 | JAK1 | JAK1 | 7938 | 0.01 | 0.42 | NO
21 | AKT1 | AKT1 | AKT1 | 8385 | 0.0033 | 0.4 | NO
22 | GRB2 | GRB2 | GRB2 | 8509 | 0.0016 | 0.39 | NO
23 | MAPK3 | MAPK3 | MAPK3 | 9190 | -0.0085 | 0.36 | NO
24 | PIK3CA | PIK3CA | PIK3CA | 9529 | -0.013 | 0.34 | NO
25 | BAD | BAD | BAD | 10418 | -0.026 | 0.3 | NO
26 | RPS6KB1 | RPS6KB1 | RPS6KB1 | 10646 | -0.03 | 0.29 | NO
27 | STAT5B | STAT5B | STAT5B | 10891 | -0.033 | 0.29 | NO
28 | SOCS1 | SOCS1 | SOCS1 | 11152 | -0.037 | 0.28 | NO
29 | MAPK1 | MAPK1 | MAPK1 | 11700 | -0.046 | 0.26 | NO
30 | SOS1 | SOS1 | SOS1 | 11857 | -0.048 | 0.26 | NO
31 | RAF1 | RAF1 | RAF1 | 12049 | -0.051 | 0.26 | NO
32 | HRAS | HRAS | HRAS | 12160 | -0.054 | 0.26 | NO
33 | SHC1 | SHC1 | SHC1 | 12560 | -0.061 | 0.25 | NO
34 | CBL | CBL | CBL | 13366 | -0.079 | 0.23 | NO
35 | BCL2L1 | BCL2L1 | BCL2L1 | 13490 | -0.082 | 0.24 | NO
36 | JAK3 | JAK3 | JAK3 | 13646 | -0.086 | 0.24 | NO
37 | CRKL | CRKL | CRKL | 14924 | -0.13 | 0.2 | 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: BIOCARTA FAS PATHWAY.

Figure S22. 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 FCER1 PATHWAY

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 | TLR3 | TLR3 | TLR3 | 145 | 0.59 | 0.13 | YES
2 | TLR4 | TLR4 | TLR4 | 1048 | 0.31 | 0.15 | YES
3 | TLR6 | TLR6 | TLR6 | 1179 | 0.3 | 0.21 | YES
4 | TLR7 | TLR7 | TLR7 | 1230 | 0.29 | 0.28 | YES
5 | TLR2 | TLR2 | TLR2 | 1400 | 0.27 | 0.33 | YES
6 | FOS | FOS | FOS | 1646 | 0.24 | 0.37 | YES
7 | NFKBIA | NFKBIA | NFKBIA | 2163 | 0.2 | 0.39 | YES
8 | TLR10 | TLR10 | TLR10 | 2304 | 0.19 | 0.42 | YES
9 | CD14 | CD14 | CD14 | 2365 | 0.18 | 0.46 | YES
10 | MAP2K6 | MAP2K6 | MAP2K6 | 2714 | 0.16 | 0.48 | YES
11 | MYD88 | MYD88 | MYD88 | 2730 | 0.16 | 0.52 | YES
12 | MAP3K1 | MAP3K1 | MAP3K1 | 3095 | 0.14 | 0.53 | YES
13 | LY96 | LY96 | LY96 | 3291 | 0.13 | 0.55 | YES
14 | MAP2K3 | MAP2K3 | MAP2K3 | 3479 | 0.12 | 0.57 | YES
15 | NFKB1 | NFKB1 | NFKB1 | 3926 | 0.1 | 0.56 | YES
16 | TLR9 | TLR9 | TLR9 | 3931 | 0.1 | 0.59 | YES
17 | EIF2AK2 | EIF2AK2 | EIF2AK2 | 3951 | 0.1 | 0.61 | YES
18 | JUN | JUN | JUN | 4213 | 0.09 | 0.62 | YES
19 | IKBKB | IKBKB | IKBKB | 4606 | 0.078 | 0.61 | NO
20 | TRAF6 | TRAF6 | TRAF6 | 6361 | 0.038 | 0.53 | NO
21 | RELA | RELA | RELA | 6853 | 0.028 | 0.51 | NO
22 | IKBKG | IKBKG | IKBKG | 6993 | 0.026 | 0.51 | NO
23 | TIRAP | TIRAP | TIRAP | 7426 | 0.018 | 0.49 | NO
24 | IRAK1 | IRAK1 | IRAK1 | 8442 | 0.0026 | 0.43 | NO
25 | TOLLIP | TOLLIP | TOLLIP | 8630 | -0.00024 | 0.42 | NO
26 | ECSIT | ECSIT | ECSIT | 9311 | -0.01 | 0.39 | NO
27 | PGLYRP1 | PGLYRP1 | PGLYRP1 | 9752 | -0.016 | 0.37 | NO
28 | TAB2 | TAB2 | TAB2 | 10251 | -0.024 | 0.35 | NO
29 | TAB1 | TAB1 | TAB1 | 10800 | -0.032 | 0.33 | NO
30 | MAP2K4 | MAP2K4 | MAP2K4 | 10806 | -0.032 | 0.33 | NO
31 | MAPK14 | MAPK14 | MAPK14 | 10901 | -0.033 | 0.34 | NO
32 | CHUK | CHUK | CHUK | 11646 | -0.045 | 0.31 | NO
33 | MAPK8 | MAPK8 | MAPK8 | 12112 | -0.053 | 0.29 | NO
34 | MAP3K14 | MAP3K14 | MAP3K14 | 12186 | -0.054 | 0.3 | NO
35 | MAP3K7 | MAP3K7 | MAP3K7 | 13963 | -0.094 | 0.23 | NO
36 | ELK1 | ELK1 | ELK1 | 14080 | -0.098 | 0.24 | 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: BIOCARTA FCER1 PATHWAY.

Figure S24. 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 HIVNEF PATHWAY

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 | MAP3K5 | MAP3K5 | MAP3K5 | 443 | 0.44 | 0.049 | YES
2 | TNF | TNF | TNF | 480 | 0.43 | 0.12 | YES
3 | CASP8 | CASP8 | CASP8 | 511 | 0.42 | 0.18 | YES
4 | FAS | FAS | FAS | 929 | 0.33 | 0.22 | YES
5 | BIRC3 | BIRC3 | BIRC3 | 1330 | 0.28 | 0.24 | YES
6 | PRKCD | PRKCD | PRKCD | 1637 | 0.24 | 0.26 | YES
7 | CASP6 | CASP6 | CASP6 | 1694 | 0.24 | 0.3 | YES
8 | CFLAR | CFLAR | CFLAR | 2063 | 0.21 | 0.31 | YES
9 | NFKBIA | NFKBIA | NFKBIA | 2163 | 0.2 | 0.34 | YES
10 | CASP7 | CASP7 | CASP7 | 2378 | 0.18 | 0.36 | YES
11 | BAG4 | BAG4 | BAG4 | 2539 | 0.17 | 0.38 | YES
12 | TNFRSF1B | TNFRSF1B | TNFRSF1B | 2849 | 0.15 | 0.39 | YES
13 | MAP3K1 | MAP3K1 | MAP3K1 | 3095 | 0.14 | 0.4 | YES
14 | CASP2 | CASP2 | CASP2 | 3442 | 0.12 | 0.4 | YES
15 | BCL2 | BCL2 | BCL2 | 3460 | 0.12 | 0.42 | YES
16 | TRADD | TRADD | TRADD | 3575 | 0.12 | 0.43 | YES
17 | NFKB1 | NFKB1 | NFKB1 | 3926 | 0.1 | 0.43 | YES
18 | ARHGDIB | ARHGDIB | ARHGDIB | 4046 | 0.097 | 0.44 | YES
19 | PSEN1 | PSEN1 | PSEN1 | 4609 | 0.078 | 0.42 | NO
20 | CRADD | CRADD | CRADD | 5025 | 0.066 | 0.41 | NO
21 | GSN | GSN | GSN | 5036 | 0.066 | 0.42 | NO
22 | RIPK1 | RIPK1 | RIPK1 | 5071 | 0.065 | 0.43 | NO
23 | TNFRSF1A | TNFRSF1A | TNFRSF1A | 5365 | 0.058 | 0.42 | NO
24 | LMNA | LMNA | LMNA | 5851 | 0.048 | 0.4 | NO
25 | PTK2 | PTK2 | PTK2 | 6229 | 0.04 | 0.39 | NO
26 | ACTG1 | ACTG1 | ACTG1 | 6265 | 0.04 | 0.39 | NO
27 | RELA | RELA | RELA | 6853 | 0.028 | 0.37 | NO
28 | RASA1 | RASA1 | RASA1 | 6866 | 0.028 | 0.37 | NO
29 | TRAF2 | TRAF2 | TRAF2 | 7075 | 0.024 | 0.36 | NO
30 | FADD | FADD | FADD | 7200 | 0.022 | 0.36 | NO
31 | CASP3 | CASP3 | CASP3 | 7498 | 0.018 | 0.35 | NO
32 | MDM2 | MDM2 | MDM2 | 7712 | 0.014 | 0.34 | NO
33 | MAP2K7 | MAP2K7 | MAP2K7 | 7992 | 0.0096 | 0.32 | NO
34 | LMNB1 | LMNB1 | LMNB1 | 8236 | 0.0055 | 0.31 | NO
35 | BIRC2 | BIRC2 | BIRC2 | 8245 | 0.0055 | 0.31 | NO
36 | BID | BID | BID | 8257 | 0.0053 | 0.31 | NO
37 | XIAP | XIAP | XIAP | 8715 | -0.0015 | 0.29 | NO
38 | NUMA1 | NUMA1 | NUMA1 | 8993 | -0.0056 | 0.28 | NO
39 | DAXX | DAXX | DAXX | 9615 | -0.014 | 0.24 | NO
40 | CYCS | CYCS | CYCS | 9958 | -0.02 | 0.23 | NO
41 | PARP1 | PARP1 | PARP1 | 10705 | -0.031 | 0.19 | NO
42 | PRKDC | PRKDC | PRKDC | 10938 | -0.034 | 0.19 | NO
43 | SPTAN1 | SPTAN1 | SPTAN1 | 11372 | -0.041 | 0.17 | NO
44 | PAK2 | PAK2 | PAK2 | 11487 | -0.042 | 0.17 | NO
45 | CHUK | CHUK | CHUK | 11646 | -0.045 | 0.17 | NO
46 | MAPK8 | MAPK8 | MAPK8 | 12112 | -0.053 | 0.15 | NO
47 | MAP3K14 | MAP3K14 | MAP3K14 | 12186 | -0.054 | 0.16 | NO
48 | DFFB | DFFB | DFFB | 12372 | -0.058 | 0.16 | NO
49 | DFFA | DFFA | DFFA | 12598 | -0.062 | 0.16 | NO
50 | CDK11A | CDK11A | CDK11A | 13474 | -0.082 | 0.12 | NO
51 | APAF1 | APAF1 | APAF1 | 13510 | -0.082 | 0.13 | NO
52 | CDK11B | CDK11B | CDK11B | 14024 | -0.096 | 0.12 | NO
53 | LMNB2 | LMNB2 | LMNB2 | 14151 | -0.1 | 0.13 | NO
54 | TRAF1 | TRAF1 | TRAF1 | 14761 | -0.12 | 0.12 | NO
55 | RB1 | RB1 | RB1 | 15408 | -0.15 | 0.11 | NO
56 | CASP9 | CASP9 | CASP9 | 15566 | -0.16 | 0.13 | NO
57 | PSEN2 | PSEN2 | PSEN2 | 16624 | -0.24 | 0.11 | 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: BIOCARTA HIVNEF PATHWAY.

Figure S26. Get High-res Image For the top 5 core enriched genes in the pathway: BIOCARTA HIVNEF 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 IL2RB PATHWAY

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 | TLR3 | TLR3 | TLR3 | 145 | 0.59 | 0.033 | YES
2 | TLR1 | TLR1 | TLR1 | 282 | 0.5 | 0.061 | YES
3 | IL1B | IL1B | IL1B | 393 | 0.46 | 0.087 | YES
4 | TNF | TNF | TNF | 480 | 0.43 | 0.11 | YES
5 | CASP8 | CASP8 | CASP8 | 511 | 0.42 | 0.14 | YES
6 | IRF5 | IRF5 | IRF5 | 520 | 0.42 | 0.17 | YES
7 | TLR5 | TLR5 | TLR5 | 673 | 0.38 | 0.19 | YES
8 | MAPK10 | MAPK10 | MAPK10 | 781 | 0.36 | 0.21 | YES
9 | IFNB1 | IFNB1 | IFNB1 | 867 | 0.34 | 0.23 | YES
10 | CCL4 | CCL4 | CCL4 | 1009 | 0.32 | 0.24 | YES
11 | IRF7 | IRF7 | IRF7 | 1014 | 0.32 | 0.26 | YES
12 | TLR4 | TLR4 | TLR4 | 1048 | 0.31 | 0.28 | YES
13 | CCL3 | CCL3 | CCL3 | 1157 | 0.3 | 0.3 | YES
14 | TLR6 | TLR6 | TLR6 | 1179 | 0.3 | 0.32 | YES
15 | TLR7 | TLR7 | TLR7 | 1230 | 0.29 | 0.33 | YES
16 | PIK3CG | PIK3CG | PIK3CG | 1231 | 0.29 | 0.35 | YES
17 | IL8 | IL8 | IL8 | 1259 | 0.28 | 0.37 | YES
18 | CXCL11 | CXCL11 | CXCL11 | 1292 | 0.28 | 0.39 | YES
19 | CD86 | CD86 | CD86 | 1320 | 0.28 | 0.41 | YES
20 | TICAM1 | TICAM1 | TICAM1 | 1339 | 0.28 | 0.43 | YES
21 | TICAM2 | TICAM2 | TICAM2 | 1360 | 0.27 | 0.44 | YES
22 | TLR2 | TLR2 | TLR2 | 1400 | 0.27 | 0.46 | YES
23 | MAPK13 | MAPK13 | MAPK13 | 1421 | 0.27 | 0.48 | YES
24 | CTSK | CTSK | CTSK | 1448 | 0.26 | 0.5 | YES
25 | CXCL10 | CXCL10 | CXCL10 | 1509 | 0.26 | 0.51 | YES
26 | CCL5 | CCL5 | CCL5 | 1581 | 0.25 | 0.52 | YES
27 | FOS | FOS | FOS | 1646 | 0.24 | 0.54 | YES
28 | PIK3R1 | PIK3R1 | PIK3R1 | 1803 | 0.23 | 0.55 | YES
29 | IKBKE | IKBKE | IKBKE | 1979 | 0.21 | 0.55 | YES
30 | MAP3K8 | MAP3K8 | MAP3K8 | 2088 | 0.2 | 0.56 | YES
31 | PIK3CB | PIK3CB | PIK3CB | 2111 | 0.2 | 0.57 | YES
32 | NFKBIA | NFKBIA | NFKBIA | 2163 | 0.2 | 0.58 | YES
33 | CD80 | CD80 | CD80 | 2282 | 0.19 | 0.59 | YES
34 | IL6 | IL6 | IL6 | 2288 | 0.19 | 0.6 | YES
35 | PIK3R3 | PIK3R3 | PIK3R3 | 2317 | 0.19 | 0.62 | YES
36 | CD14 | CD14 | CD14 | 2365 | 0.18 | 0.62 | YES
37 | IL12A | IL12A | IL12A | 2369 | 0.18 | 0.64 | YES
38 | TLR8 | TLR8 | TLR8 | 2454 | 0.18 | 0.64 | YES
39 | CXCL9 | CXCL9 | CXCL9 | 2478 | 0.17 | 0.66 | YES
40 | MAP2K6 | MAP2K6 | MAP2K6 | 2714 | 0.16 | 0.66 | YES
41 | MYD88 | MYD88 | MYD88 | 2730 | 0.16 | 0.66 | YES
42 | IL12B | IL12B | IL12B | 2840 | 0.15 | 0.67 | YES
43 | LY96 | LY96 | LY96 | 3291 | 0.13 | 0.66 | NO
44 | MAP2K3 | MAP2K3 | MAP2K3 | 3479 | 0.12 | 0.65 | NO
45 | IRAK4 | IRAK4 | IRAK4 | 3481 | 0.12 | 0.66 | NO
46 | SPP1 | SPP1 | SPP1 | 3743 | 0.11 | 0.65 | NO
47 | NFKB1 | NFKB1 | NFKB1 | 3926 | 0.1 | 0.65 | NO
48 | TLR9 | TLR9 | TLR9 | 3931 | 0.1 | 0.66 | NO
49 | STAT1 | STAT1 | STAT1 | 4205 | 0.091 | 0.65 | NO
50 | JUN | JUN | JUN | 4213 | 0.09 | 0.66 | NO
51 | IKBKB | IKBKB | IKBKB | 4606 | 0.078 | 0.64 | NO
52 | IFNAR1 | IFNAR1 | IFNAR1 | 4870 | 0.071 | 0.63 | NO
53 | CD40 | CD40 | CD40 | 4882 | 0.07 | 0.64 | NO
54 | RIPK1 | RIPK1 | RIPK1 | 5071 | 0.065 | 0.63 | NO
55 | IRF3 | IRF3 | IRF3 | 6310 | 0.039 | 0.57 | NO
56 | TRAF6 | TRAF6 | TRAF6 | 6361 | 0.038 | 0.57 | NO
57 | LBP | LBP | LBP | 6826 | 0.029 | 0.54 | NO
58 | RELA | RELA | RELA | 6853 | 0.028 | 0.54 | NO
59 | IKBKG | IKBKG | IKBKG | 6993 | 0.026 | 0.54 | NO
60 | FADD | FADD | FADD | 7200 | 0.022 | 0.53 | NO
61 | PIK3CD | PIK3CD | PIK3CD | 7327 | 0.02 | 0.52 | NO
62 | TIRAP | TIRAP | TIRAP | 7426 | 0.018 | 0.52 | NO
63 | PIK3R2 | PIK3R2 | PIK3R2 | 7455 | 0.018 | 0.52 | NO
64 | PIK3R5 | PIK3R5 | PIK3R5 | 7524 | 0.017 | 0.52 | NO
65 | MAP2K7 | MAP2K7 | MAP2K7 | 7992 | 0.0096 | 0.49 | NO
66 | RAC1 | RAC1 | RAC1 | 8132 | 0.0072 | 0.48 | NO
67 | TRAF3 | TRAF3 | TRAF3 | 8136 | 0.0072 | 0.48 | NO
68 | AKT1 | AKT1 | AKT1 | 8385 | 0.0033 | 0.47 | NO
69 | IRAK1 | IRAK1 | IRAK1 | 8442 | 0.0026 | 0.47 | NO
70 | TOLLIP | TOLLIP | TOLLIP | 8630 | -0.00024 | 0.46 | NO
71 | IFNAR2 | IFNAR2 | IFNAR2 | 9049 | -0.0064 | 0.44 | NO
72 | MAPK3 | MAPK3 | MAPK3 | 9190 | -0.0085 | 0.43 | NO
73 | MAP2K2 | MAP2K2 | MAP2K2 | 9277 | -0.0098 | 0.43 | NO
74 | PIK3CA | PIK3CA | PIK3CA | 9529 | -0.013 | 0.41 | NO
75 | MAPK9 | MAPK9 | MAPK9 | 10237 | -0.024 | 0.38 | NO
76 | TAB2 | TAB2 | TAB2 | 10251 | -0.024 | 0.38 | NO
77 | TAB1 | TAB1 | TAB1 | 10800 | -0.032 | 0.35 | NO
78 | MAP2K4 | MAP2K4 | MAP2K4 | 10806 | -0.032 | 0.35 | NO
79 | MAPK11 | MAPK11 | MAPK11 | 10842 | -0.033 | 0.35 | NO
80 | MAPK14 | MAPK14 | MAPK14 | 10901 | -0.033 | 0.35 | NO
81 | CHUK | CHUK | CHUK | 11646 | -0.045 | 0.32 | NO
82 | MAPK1 | MAPK1 | MAPK1 | 11700 | -0.046 | 0.32 | NO
83 | MAPK8 | MAPK8 | MAPK8 | 12112 | -0.053 | 0.3 | NO
84 | MAP2K1 | MAP2K1 | MAP2K1 | 13567 | -0.084 | 0.22 | NO
85 | MAP3K7 | MAP3K7 | MAP3K7 | 13963 | -0.094 | 0.21 | NO
86 | AKT3 | AKT3 | AKT3 | 14802 | -0.12 | 0.17 | NO
87 | AKT2 | AKT2 | AKT2 | 14805 | -0.12 | 0.18 | NO
88 | MAPK12 | MAPK12 | MAPK12 | 17592 | -0.36 | 0.057 | 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: BIOCARTA IL2RB PATHWAY.

Figure S28. Get High-res Image For the top 5 core enriched genes in the pathway: BIOCARTA IL2RB 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 DEATH PATHWAY

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 | CASP8 | CASP8 | CASP8 | 511 | 0.42 | 0.092 | YES
2 | CASP10 | CASP10 | CASP10 | 631 | 0.39 | 0.2 | YES
3 | FAS | FAS | FAS | 929 | 0.33 | 0.27 | YES
4 | FASLG | FASLG | FASLG | 1592 | 0.25 | 0.31 | YES
5 | CASP6 | CASP6 | CASP6 | 1694 | 0.24 | 0.37 | YES
6 | CFLAR | CFLAR | CFLAR | 2063 | 0.21 | 0.41 | YES
7 | RIPK2 | RIPK2 | RIPK2 | 2336 | 0.18 | 0.45 | YES
8 | CASP7 | CASP7 | CASP7 | 2378 | 0.18 | 0.5 | YES
9 | MAP3K1 | MAP3K1 | MAP3K1 | 3095 | 0.14 | 0.5 | YES
10 | PTPN13 | PTPN13 | PTPN13 | 3829 | 0.1 | 0.49 | YES
11 | ARHGDIB | ARHGDIB | ARHGDIB | 4046 | 0.097 | 0.5 | YES
12 | JUN | JUN | JUN | 4213 | 0.09 | 0.52 | YES
13 | PAK1 | PAK1 | PAK1 | 5268 | 0.061 | 0.48 | NO
14 | LMNA | LMNA | LMNA | 5851 | 0.048 | 0.46 | NO
15 | FADD | FADD | FADD | 7200 | 0.022 | 0.4 | NO
16 | CASP3 | CASP3 | CASP3 | 7498 | 0.018 | 0.39 | NO
17 | DAXX | DAXX | DAXX | 9615 | -0.014 | 0.28 | NO
18 | PARP1 | PARP1 | PARP1 | 10705 | -0.031 | 0.23 | NO
19 | MAP2K4 | MAP2K4 | MAP2K4 | 10806 | -0.032 | 0.23 | NO
20 | PRKDC | PRKDC | PRKDC | 10938 | -0.034 | 0.23 | NO
21 | FAF1 | FAF1 | FAF1 | 10983 | -0.035 | 0.24 | NO
22 | SPTAN1 | SPTAN1 | SPTAN1 | 11372 | -0.041 | 0.23 | NO
23 | PAK2 | PAK2 | PAK2 | 11487 | -0.042 | 0.24 | NO
24 | MAPK8 | MAPK8 | MAPK8 | 12112 | -0.053 | 0.22 | NO
25 | DFFB | DFFB | DFFB | 12372 | -0.058 | 0.22 | NO
26 | DFFA | DFFA | DFFA | 12598 | -0.062 | 0.23 | NO
27 | MAP3K7 | MAP3K7 | MAP3K7 | 13963 | -0.094 | 0.18 | NO
28 | LMNB2 | LMNB2 | LMNB2 | 14151 | -0.1 | 0.2 | NO
29 | RB1 | RB1 | RB1 | 15408 | -0.15 | 0.17 | 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: BIOCARTA DEATH PATHWAY.

Figure S30. Get High-res Image For the top 5 core enriched genes in the pathway: BIOCARTA DEATH 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 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 | TNF | TNF | TNF | 480 | 0.43 | 0.026 | YES
2 | CASP8 | CASP8 | CASP8 | 511 | 0.42 | 0.075 | YES
3 | IFIH1 | IFIH1 | IFIH1 | 532 | 0.42 | 0.12 | YES
4 | CASP10 | CASP10 | CASP10 | 631 | 0.39 | 0.16 | YES
5 | MAPK10 | MAPK10 | MAPK10 | 781 | 0.36 | 0.2 | YES
6 | IFNB1 | IFNB1 | IFNB1 | 867 | 0.34 | 0.24 | YES
7 | DHX58 | DHX58 | DHX58 | 940 | 0.33 | 0.27 | YES
8 | DDX58 | DDX58 | DDX58 | 943 | 0.33 | 0.31 | YES
9 | NLRX1 | NLRX1 | NLRX1 | 974 | 0.32 | 0.35 | YES
10 | IRF7 | IRF7 | IRF7 | 1014 | 0.32 | 0.39 | YES
11 | IL8 | IL8 | IL8 | 1259 | 0.28 | 0.41 | YES
12 | MAPK13 | MAPK13 | MAPK13 | 1421 | 0.27 | 0.43 | YES
13 | CXCL10 | CXCL10 | CXCL10 | 1509 | 0.26 | 0.46 | YES
14 | IFNE | IFNE | IFNE | 1773 | 0.23 | 0.47 | YES
15 | IKBKE | IKBKE | IKBKE | 1979 | 0.21 | 0.49 | YES
16 | NFKBIA | NFKBIA | NFKBIA | 2163 | 0.2 | 0.5 | YES
17 | IL12A | IL12A | IL12A | 2369 | 0.18 | 0.51 | YES
18 | ISG15 | ISG15 | ISG15 | 2698 | 0.16 | 0.51 | YES
19 | IL12B | IL12B | IL12B | 2840 | 0.15 | 0.52 | YES
20 | RNF125 | RNF125 | RNF125 | 2878 | 0.15 | 0.54 | YES
21 | MAP3K1 | MAP3K1 | MAP3K1 | 3095 | 0.14 | 0.54 | YES
22 | TRADD | TRADD | TRADD | 3575 | 0.12 | 0.53 | NO
23 | NFKB1 | NFKB1 | NFKB1 | 3926 | 0.1 | 0.52 | NO
24 | TRIM25 | TRIM25 | TRIM25 | 3962 | 0.1 | 0.54 | NO
25 | TMEM173 | TMEM173 | TMEM173 | 4048 | 0.096 | 0.54 | NO
26 | IKBKB | IKBKB | IKBKB | 4606 | 0.078 | 0.52 | NO
27 | RIPK1 | RIPK1 | RIPK1 | 5071 | 0.065 | 0.5 | NO
28 | TANK | TANK | TANK | 5718 | 0.051 | 0.48 | NO
29 | ATG5 | ATG5 | ATG5 | 5815 | 0.049 | 0.48 | NO
30 | CYLD | CYLD | CYLD | 5971 | 0.046 | 0.47 | NO
31 | IRF3 | IRF3 | IRF3 | 6310 | 0.039 | 0.46 | NO
32 | TRAF6 | TRAF6 | TRAF6 | 6361 | 0.038 | 0.46 | NO
33 | RELA | RELA | RELA | 6853 | 0.028 | 0.44 | NO
34 | IKBKG | IKBKG | IKBKG | 6993 | 0.026 | 0.44 | NO
35 | TRAF2 | TRAF2 | TRAF2 | 7075 | 0.024 | 0.43 | NO
36 | FADD | FADD | FADD | 7200 | 0.022 | 0.43 | NO
37 | ATG12 | ATG12 | ATG12 | 7411 | 0.019 | 0.42 | NO
38 | TBK1 | TBK1 | TBK1 | 7457 | 0.018 | 0.42 | NO
39 | DDX3X | DDX3X | DDX3X | 7721 | 0.014 | 0.41 | NO
40 | TRAF3 | TRAF3 | TRAF3 | 8136 | 0.0072 | 0.39 | NO
41 | PIN1 | PIN1 | PIN1 | 8285 | 0.0049 | 0.38 | NO
42 | OTUD5 | OTUD5 | OTUD5 | 9306 | -0.01 | 0.32 | NO
43 | DAK | DAK | DAK | 9448 | -0.012 | 0.32 | NO
44 | MAPK9 | MAPK9 | MAPK9 | 10237 | -0.024 | 0.28 | NO
45 | MAVS | MAVS | MAVS | 10534 | -0.028 | 0.27 | NO
46 | MAPK11 | MAPK11 | MAPK11 | 10842 | -0.033 | 0.26 | NO
47 | MAPK14 | MAPK14 | MAPK14 | 10901 | -0.033 | 0.26 | NO
48 | CHUK | CHUK | CHUK | 11646 | -0.045 | 0.22 | NO
49 | MAPK8 | MAPK8 | MAPK8 | 12112 | -0.053 | 0.2 | NO
50 | IFNW1 | IFNW1 | IFNW1 | 12264 | -0.056 | 0.2 | NO
51 | SIKE1 | SIKE1 | SIKE1 | 13676 | -0.087 | 0.14 | NO
52 | MAP3K7 | MAP3K7 | MAP3K7 | 13963 | -0.094 | 0.13 | NO
53 | AZI2 | AZI2 | AZI2 | 14388 | -0.11 | 0.12 | NO
54 | NFKBIB | NFKBIB | NFKBIB | 15975 | -0.18 | 0.058 | NO
55 | TBKBP1 | TBKBP1 | TBKBP1 | 17555 | -0.35 | 0.016 | NO
56 | MAPK12 | MAPK12 | MAPK12 | 17592 | -0.36 | 0.057 | 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: BIOCARTA TNFR1 PATHWAY.

Figure S32. 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: BIOCARTA TOLL PATHWAY

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 | AP1M2 | AP1M2 | AP1M2 | 34 | 0.72 | 0.055 | YES
2 | ATP6V0A4 | ATP6V0A4 | ATP6V0A4 | 210 | 0.54 | 0.089 | YES
3 | AP1S3 | AP1S3 | AP1S3 | 568 | 0.4 | 0.1 | YES
4 | LAMP3 | LAMP3 | LAMP3 | 820 | 0.35 | 0.12 | YES
5 | CTSW | CTSW | CTSW | 1349 | 0.27 | 0.11 | YES
6 | CTSG | CTSG | CTSG | 1422 | 0.27 | 0.13 | YES
7 | CTSK | CTSK | CTSK | 1448 | 0.26 | 0.15 | YES
8 | CTSS | CTSS | CTSS | 1458 | 0.26 | 0.17 | YES
9 | CTSO | CTSO | CTSO | 1464 | 0.26 | 0.19 | YES
10 | AGA | AGA | AGA | 1470 | 0.26 | 0.21 | YES
11 | TCIRG1 | TCIRG1 | TCIRG1 | 1792 | 0.23 | 0.21 | YES
12 | DNASE2 | DNASE2 | DNASE2 | 1817 | 0.23 | 0.23 | YES
13 | CTSH | CTSH | CTSH | 1907 | 0.22 | 0.24 | YES
14 | NPC2 | NPC2 | NPC2 | 1931 | 0.22 | 0.26 | YES
15 | ATP6V0D2 | ATP6V0D2 | ATP6V0D2 | 1951 | 0.22 | 0.27 | YES
16 | HYAL1 | HYAL1 | HYAL1 | 2123 | 0.2 | 0.28 | YES
17 | ACP5 | ACP5 | ACP5 | 2264 | 0.19 | 0.29 | YES
18 | HEXB | HEXB | HEXB | 2291 | 0.19 | 0.3 | YES
19 | LAPTM5 | LAPTM5 | LAPTM5 | 2474 | 0.18 | 0.3 | YES
20 | CTSE | CTSE | CTSE | 2483 | 0.17 | 0.32 | YES
21 | CTSB | CTSB | CTSB | 2501 | 0.17 | 0.33 | YES
22 | SUMF1 | SUMF1 | SUMF1 | 2837 | 0.15 | 0.32 | YES
23 | ABCB9 | ABCB9 | ABCB9 | 2960 | 0.14 | 0.33 | YES
24 | LAPTM4B | LAPTM4B | LAPTM4B | 3039 | 0.14 | 0.34 | YES
25 | MANBA | MANBA | MANBA | 3105 | 0.14 | 0.34 | YES
26 | CTSC | CTSC | CTSC | 3216 | 0.13 | 0.35 | YES
27 | CD68 | CD68 | CD68 | 3235 | 0.13 | 0.36 | YES
28 | CTSD | CTSD | CTSD | 3297 | 0.13 | 0.36 | YES
29 | GNPTAB | GNPTAB | GNPTAB | 3387 | 0.12 | 0.37 | YES
30 | GLA | GLA | GLA | 3486 | 0.12 | 0.37 | YES
31 | CTSZ | CTSZ | CTSZ | 3489 | 0.12 | 0.38 | YES
32 | GBA | GBA | GBA | 3496 | 0.12 | 0.39 | YES
33 | CLN5 | CLN5 | CLN5 | 3709 | 0.11 | 0.39 | YES
34 | ATP6V1H | ATP6V1H | ATP6V1H | 3723 | 0.11 | 0.4 | YES
35 | ASAH1 | ASAH1 | ASAH1 | 3788 | 0.11 | 0.4 | YES
36 | ATP6AP1 | ATP6AP1 | ATP6AP1 | 3894 | 0.1 | 0.4 | YES
37 | FUCA1 | FUCA1 | FUCA1 | 3899 | 0.1 | 0.41 | YES
38 | GUSB | GUSB | GUSB | 3984 | 0.099 | 0.42 | YES
39 | CLN3 | CLN3 | CLN3 | 4016 | 0.098 | 0.42 | YES
40 | SLC11A1 | SLC11A1 | SLC11A1 | 4090 | 0.095 | 0.42 | YES
41 | NAGPA | NAGPA | NAGPA | 4181 | 0.091 | 0.43 | YES
42 | MFSD8 | MFSD8 | MFSD8 | 4239 | 0.089 | 0.43 | YES
43 | PSAP | PSAP | PSAP | 4515 | 0.08 | 0.42 | YES
44 | ENTPD4 | ENTPD4 | ENTPD4 | 4563 | 0.079 | 0.43 | YES
45 | TPP1 | TPP1 | TPP1 | 4576 | 0.079 | 0.43 | YES
46 | LAMP1 | LAMP1 | LAMP1 | 4689 | 0.075 | 0.43 | YES
47 | MAN2B1 | MAN2B1 | MAN2B1 | 4751 | 0.074 | 0.43 | YES
48 | GLB1 | GLB1 | GLB1 | 4827 | 0.072 | 0.44 | YES
49 | ACP2 | ACP2 | ACP2 | 4857 | 0.071 | 0.44 | YES
50 | LGMN | LGMN | LGMN | 4902 | 0.07 | 0.44 | YES
51 | ATP6V0D1 | ATP6V0D1 | ATP6V0D1 | 5094 | 0.065 | 0.44 | NO
52 | SLC11A2 | SLC11A2 | SLC11A2 | 5185 | 0.063 | 0.44 | NO
53 | LAMP2 | LAMP2 | LAMP2 | 5345 | 0.059 | 0.43 | NO
54 | AP4M1 | AP4M1 | AP4M1 | 5454 | 0.056 | 0.43 | NO
55 | AP1S1 | AP1S1 | AP1S1 | 5493 | 0.056 | 0.44 | NO
56 | AP4S1 | AP4S1 | AP4S1 | 5599 | 0.053 | 0.43 | NO
57 | NEU1 | NEU1 | NEU1 | 5625 | 0.053 | 0.44 | NO
58 | CLTB | CLTB | CLTB | 5679 | 0.052 | 0.44 | NO
59 | GM2A | GM2A | GM2A | 5739 | 0.05 | 0.44 | NO
60 | IDS | IDS | IDS | 5865 | 0.048 | 0.44 | NO
61 | ATP6V0B | ATP6V0B | ATP6V0B | 5885 | 0.048 | 0.44 | NO
62 | SCARB2 | SCARB2 | SCARB2 | 5937 | 0.046 | 0.44 | NO
63 | GNS | GNS | GNS | 6080 | 0.044 | 0.44 | NO
64 | SORT1 | SORT1 | SORT1 | 6199 | 0.041 | 0.43 | NO
65 | MCOLN1 | MCOLN1 | MCOLN1 | 6260 | 0.04 | 0.43 | NO
66 | HEXA | HEXA | HEXA | 6351 | 0.038 | 0.43 | NO
67 | AP3B1 | AP3B1 | AP3B1 | 6364 | 0.037 | 0.43 | NO
68 | CTSA | CTSA | CTSA | 6409 | 0.036 | 0.43 | NO
69 | CLTA | CLTA | CLTA | 6560 | 0.034 | 0.43 | NO
70 | AP3S1 | AP3S1 | AP3S1 | 6678 | 0.031 | 0.42 | NO
71 | IGF2R | IGF2R | IGF2R | 6855 | 0.028 | 0.42 | NO
72 | CD164 | CD164 | CD164 | 7079 | 0.024 | 0.41 | NO
73 | CD63 | CD63 | CD63 | 7248 | 0.022 | 0.4 | NO
74 | IDUA | IDUA | IDUA | 7367 | 0.02 | 0.4 | NO
75 | SGSH | SGSH | SGSH | 7737 | 0.014 | 0.38 | NO
76 | AP1B1 | AP1B1 | AP1B1 | 7798 | 0.013 | 0.37 | NO
77 | AP1G1 | AP1G1 | AP1G1 | 7939 | 0.01 | 0.37 | NO
78 | GNPTG | GNPTG | GNPTG | 8006 | 0.0094 | 0.36 | NO
79 | M6PR | M6PR | M6PR | 8032 | 0.009 | 0.36 | NO
80 | SMPD1 | SMPD1 | SMPD1 | 8096 | 0.0077 | 0.36 | NO
81 | NAGA | NAGA | NAGA | 8146 | 0.007 | 0.36 | NO
82 | AP4B1 | AP4B1 | AP4B1 | 8155 | 0.0069 | 0.36 | NO
83 | ARSA | ARSA | ARSA | 8239 | 0.0055 | 0.36 | NO
84 | ATP6V0A2 | ATP6V0A2 | ATP6V0A2 | 8242 | 0.0055 | 0.36 | NO
85 | GAA | GAA | GAA | 8365 | 0.0036 | 0.35 | NO
86 | ATP6V0C | ATP6V0C | ATP6V0C | 8453 | 0.0025 | 0.34 | NO
87 | CLTC | CLTC | CLTC | 8583 | 0.00036 | 0.34 | NO
88 | LAPTM4A | LAPTM4A | LAPTM4A | 8730 | -0.0017 | 0.33 | NO
89 | CTSL2 | CTSL2 | CTSL2 | 8942 | -0.0049 | 0.32 | NO
90 | PPT1 | PPT1 | PPT1 | 9101 | -0.007 | 0.31 | NO
91 | AP3M1 | AP3M1 | AP3M1 | 9617 | -0.014 | 0.28 | NO
92 | LIPA | LIPA | LIPA | 9621 | -0.014 | 0.28 | NO
93 | CTSL1 | CTSL1 | CTSL1 | 9977 | -0.02 | 0.27 | NO
94 | ABCA2 | ABCA2 | ABCA2 | 10118 | -0.022 | 0.26 | NO
95 | CTNS | CTNS | CTNS | 10436 | -0.027 | 0.25 | NO
96 | GGA3 | GGA3 | GGA3 | 10468 | -0.027 | 0.25 | NO
97 | AP3M2 | AP3M2 | AP3M2 | 10486 | -0.028 | 0.25 | NO
98 | AP3S2 | AP3S2 | AP3S2 | 10606 | -0.03 | 0.24 | NO
99 | AP3D1 | AP3D1 | AP3D1 | 10732 | -0.031 | 0.24 | NO
100 | NPC1 | NPC1 | NPC1 | 10795 | -0.032 | 0.24 | NO
101 | PLA2G15 | PLA2G15 | PLA2G15 | 10833 | -0.032 | 0.24 | NO
102 | NAPSA | NAPSA | NAPSA | 11032 | -0.035 | 0.23 | NO
103 | NAGLU | NAGLU | NAGLU | 11060 | -0.036 | 0.23 | NO
104 | ATP6V0A1 | ATP6V0A1 | ATP6V0A1 | 11123 | -0.037 | 0.23 | NO
105 | CTSF | CTSF | CTSF | 11201 | -0.038 | 0.23 | NO
106 | AP4E1 | AP4E1 | AP4E1 | 11264 | -0.039 | 0.23 | NO
107 | SLC17A5 | SLC17A5 | SLC17A5 | 11332 | -0.04 | 0.23 | NO
108 | GALNS | GALNS | GALNS | 11932 | -0.05 | 0.2 | NO
109 | ARSB | ARSB | ARSB | 12059 | -0.052 | 0.2 | NO
110 | AP1S2 | AP1S2 | AP1S2 | 12273 | -0.056 | 0.19 | NO
111 | ARSG | ARSG | ARSG | 12476 | -0.06 | 0.19 | NO
112 | GGA1 | GGA1 | GGA1 | 12762 | -0.066 | 0.18 | NO
113 | GGA2 | GGA2 | GGA2 | 13275 | -0.077 | 0.16 | NO
114 | GALC | GALC | GALC | 14136 | -0.099 | 0.12 | NO
115 | AP1M1 | AP1M1 | AP1M1 | 14623 | -0.12 | 0.1 | NO
116 | PPT2 | PPT2 | PPT2 | 14792 | -0.12 | 0.1 | NO
117 | PSAPL1 | PSAPL1 | PSAPL1 | 16655 | -0.24 | 0.019 | NO
118 | DNASE2B | DNASE2B | DNASE2B | 17139 | -0.29 | 0.016 | NO
119 | AP3B2 | AP3B2 | AP3B2 | 17884 | -0.4 | 0.0083 | NO
120 | CLTCL1 | CLTCL1 | CLTCL1 | 17926 | -0.41 | 0.039 | 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: BIOCARTA TOLL PATHWAY.

Figure S34. Get High-res Image For the top 5 core enriched genes in the pathway: BIOCARTA TOLL 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 SELENOAMINO ACID 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 | TNFRSF10A | TNFRSF10A | TNFRSF10A | 87 | 0.64 | 0.047 | YES
2 | TNFSF10 | TNFSF10 | TNFSF10 | 92 | 0.64 | 0.098 | YES
3 | IL1B | IL1B | IL1B | 393 | 0.46 | 0.12 | YES
4 | TNF | TNF | TNF | 480 | 0.43 | 0.15 | YES
5 | TNFRSF10C | TNFRSF10C | TNFRSF10C | 484 | 0.43 | 0.18 | YES
6 | CASP8 | CASP8 | CASP8 | 511 | 0.42 | 0.22 | YES
7 | IL1A | IL1A | IL1A | 541 | 0.41 | 0.25 | YES
8 | CASP10 | CASP10 | CASP10 | 631 | 0.39 | 0.27 | YES
9 | FAS | FAS | FAS | 929 | 0.33 | 0.28 | YES
10 | CSF2RB | CSF2RB | CSF2RB | 992 | 0.32 | 0.31 | YES
11 | IL3RA | IL3RA | IL3RA | 1065 | 0.31 | 0.33 | YES
12 | PIK3CG | PIK3CG | PIK3CG | 1231 | 0.29 | 0.34 | YES
13 | BIRC3 | BIRC3 | BIRC3 | 1330 | 0.28 | 0.36 | YES
14 | PRKAR2B | PRKAR2B | PRKAR2B | 1460 | 0.26 | 0.37 | YES
15 | IL1R1 | IL1R1 | IL1R1 | 1606 | 0.25 | 0.39 | YES
16 | CASP6 | CASP6 | CASP6 | 1694 | 0.24 | 0.4 | YES
17 | PIK3R1 | PIK3R1 | PIK3R1 | 1803 | 0.23 | 0.41 | YES
18 | CFLAR | CFLAR | CFLAR | 2063 | 0.21 | 0.42 | YES
19 | PIK3CB | PIK3CB | PIK3CB | 2111 | 0.2 | 0.43 | YES
20 | NFKBIA | NFKBIA | NFKBIA | 2163 | 0.2 | 0.44 | YES
21 | IRAK2 | IRAK2 | IRAK2 | 2187 | 0.2 | 0.46 | YES
22 | PIK3R3 | PIK3R3 | PIK3R3 | 2317 | 0.19 | 0.46 | YES
23 | CASP7 | CASP7 | CASP7 | 2378 | 0.18 | 0.48 | YES
24 | MYD88 | MYD88 | MYD88 | 2730 | 0.16 | 0.47 | NO
25 | BCL2 | BCL2 | BCL2 | 3460 | 0.12 | 0.44 | NO
26 | IRAK4 | IRAK4 | IRAK4 | 3481 | 0.12 | 0.45 | NO
27 | ENDOD1 | ENDOD1 | ENDOD1 | 3532 | 0.12 | 0.46 | NO
28 | TRADD | TRADD | TRADD | 3575 | 0.12 | 0.46 | NO
29 | PRKX | PRKX | PRKX | 3626 | 0.11 | 0.47 | NO
30 | NFKB1 | NFKB1 | NFKB1 | 3926 | 0.1 | 0.46 | NO
31 | PPP3CC | PPP3CC | PPP3CC | 4512 | 0.08 | 0.44 | NO
32 | IKBKB | IKBKB | IKBKB | 4606 | 0.078 | 0.44 | NO
33 | CHP | CHP | CHP | 5049 | 0.066 | 0.42 | NO
34 | RIPK1 | RIPK1 | RIPK1 | 5071 | 0.065 | 0.42 | NO
35 | BAX | BAX | BAX | 5106 | 0.065 | 0.43 | NO
36 | CAPN1 | CAPN1 | CAPN1 | 5177 | 0.063 | 0.43 | NO
37 | TNFRSF1A | TNFRSF1A | TNFRSF1A | 5365 | 0.058 | 0.42 | NO
38 | TP53 | TP53 | TP53 | 5421 | 0.057 | 0.42 | NO
39 | CAPN2 | CAPN2 | CAPN2 | 6016 | 0.045 | 0.4 | NO
40 | PPP3CA | PPP3CA | PPP3CA | 6281 | 0.039 | 0.38 | NO
41 | AIFM1 | AIFM1 | AIFM1 | 6774 | 0.03 | 0.36 | NO
42 | RELA | RELA | RELA | 6853 | 0.028 | 0.36 | NO
43 | IKBKG | IKBKG | IKBKG | 6993 | 0.026 | 0.35 | NO
44 | TRAF2 | TRAF2 | TRAF2 | 7075 | 0.024 | 0.35 | NO
45 | FADD | FADD | FADD | 7200 | 0.022 | 0.35 | NO
46 | PIK3CD | PIK3CD | PIK3CD | 7327 | 0.02 | 0.34 | NO
47 | PIK3R2 | PIK3R2 | PIK3R2 | 7455 | 0.018 | 0.34 | NO
48 | CASP3 | CASP3 | CASP3 | 7498 | 0.018 | 0.34 | NO
49 | PIK3R5 | PIK3R5 | PIK3R5 | 7524 | 0.017 | 0.34 | NO
50 | ENDOG | ENDOG | ENDOG | 7763 | 0.014 | 0.32 | NO
51 | BIRC2 | BIRC2 | BIRC2 | 8245 | 0.0055 | 0.3 | NO
52 | BID | BID | BID | 8257 | 0.0053 | 0.3 | NO
53 | AKT1 | AKT1 | AKT1 | 8385 | 0.0033 | 0.29 | NO
54 | IRAK1 | IRAK1 | IRAK1 | 8442 | 0.0026 | 0.29 | NO
55 | XIAP | XIAP | XIAP | 8715 | -0.0015 | 0.27 | NO
56 | TNFRSF10B | TNFRSF10B | TNFRSF10B | 9406 | -0.012 | 0.24 | NO
57 | PIK3CA | PIK3CA | PIK3CA | 9529 | -0.013 | 0.23 | NO
58 | CYCS | CYCS | CYCS | 9958 | -0.02 | 0.21 | NO
59 | IL1RAP | IL1RAP | IL1RAP | 10120 | -0.022 | 0.2 | NO
60 | PRKAR2A | PRKAR2A | PRKAR2A | 10207 | -0.023 | 0.2 | NO
61 | BAD | BAD | BAD | 10418 | -0.026 | 0.19 | NO
62 | PRKACB | PRKACB | PRKACB | 10850 | -0.033 | 0.17 | NO
63 | CHUK | CHUK | CHUK | 11646 | -0.045 | 0.13 | NO
64 | MAP3K14 | MAP3K14 | MAP3K14 | 12186 | -0.054 | 0.11 | NO
65 | PPP3CB | PPP3CB | PPP3CB | 12319 | -0.056 | 0.1 | NO
66 | DFFB | DFFB | DFFB | 12372 | -0.058 | 0.11 | NO
67 | DFFA | DFFA | DFFA | 12598 | -0.062 | 0.1 | NO
68 | PPP3R1 | PPP3R1 | PPP3R1 | 12759 | -0.066 | 0.096 | NO
69 | ATM | ATM | ATM | 12942 | -0.069 | 0.092 | NO
70 | BCL2L1 | BCL2L1 | BCL2L1 | 13490 | -0.082 | 0.069 | NO
71 | APAF1 | APAF1 | APAF1 | 13510 | -0.082 | 0.075 | NO
72 | TNFRSF10D | TNFRSF10D | TNFRSF10D | 13621 | -0.085 | 0.076 | NO
73 | EXOG | EXOG | EXOG | 13821 | -0.09 | 0.072 | NO
74 | PRKACA | PRKACA | PRKACA | 14062 | -0.097 | 0.067 | NO
75 | PRKAR1A | PRKAR1A | PRKAR1A | 14223 | -0.1 | 0.067 | NO
76 | PPP3R2 | PPP3R2 | PPP3R2 | 14252 | -0.1 | 0.074 | NO
77 | AKT3 | AKT3 | AKT3 | 14802 | -0.12 | 0.054 | NO
78 | AKT2 | AKT2 | AKT2 | 14805 | -0.12 | 0.064 | NO
79 | NGF | NGF | NGF | 15056 | -0.13 | 0.061 | NO
80 | CASP9 | CASP9 | CASP9 | 15566 | -0.16 | 0.047 | NO
81 | PRKAR1B | PRKAR1B | PRKAR1B | 16529 | -0.23 | 0.014 | NO
82 | IRAK3 | IRAK3 | IRAK3 | 17332 | -0.32 | -0.0042 | NO
83 | NTRK1 | NTRK1 | NTRK1 | 17959 | -0.42 | -0.004 | NO
84 | CHP2 | CHP2 | CHP2 | 18258 | -0.51 | 0.021 | 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 SELENOAMINO ACID METABOLISM.

Figure S36. Get High-res Image For the top 5 core enriched genes in the pathway: KEGG SELENOAMINO 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 LYSOSOME

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 | FCER1A | FCER1A | FCER1A | 75 | 0.65 | 0.05 | YES
2 | VAV3 | VAV3 | VAV3 | 239 | 0.53 | 0.086 | YES
3 | SYK | SYK | SYK | 246 | 0.52 | 0.13 | YES
4 | PLA2G4A | PLA2G4A | PLA2G4A | 404 | 0.46 | 0.16 | YES
5 | PLA2G10 | PLA2G10 | PLA2G10 | 445 | 0.44 | 0.19 | YES
6 | CSF2 | CSF2 | CSF2 | 455 | 0.44 | 0.23 | YES
7 | TNF | TNF | TNF | 480 | 0.43 | 0.26 | YES
8 | MAPK10 | MAPK10 | MAPK10 | 781 | 0.36 | 0.28 | YES
9 | PLA2G3 | PLA2G3 | PLA2G3 | 789 | 0.36 | 0.31 | YES
10 | VAV1 | VAV1 | VAV1 | 910 | 0.33 | 0.33 | YES
11 | LCP2 | LCP2 | LCP2 | 1018 | 0.32 | 0.35 | YES
12 | MS4A2 | MS4A2 | MS4A2 | 1050 | 0.31 | 0.37 | YES
13 | PIK3CG | PIK3CG | PIK3CG | 1231 | 0.29 | 0.39 | YES
14 | MAPK13 | MAPK13 | MAPK13 | 1421 | 0.27 | 0.4 | YES
15 | INPP5D | INPP5D | INPP5D | 1423 | 0.27 | 0.42 | YES
16 | LYN | LYN | LYN | 1523 | 0.26 | 0.44 | YES
17 | PRKCD | PRKCD | PRKCD | 1637 | 0.24 | 0.45 | YES
18 | PIK3R1 | PIK3R1 | PIK3R1 | 1803 | 0.23 | 0.46 | YES
19 | BTK | BTK | BTK | 2052 | 0.21 | 0.47 | YES
20 | LAT | LAT | LAT | 2057 | 0.21 | 0.48 | YES
21 | IL13 | IL13 | IL13 | 2081 | 0.2 | 0.5 | YES
22 | PIK3CB | PIK3CB | PIK3CB | 2111 | 0.2 | 0.52 | YES
23 | FCER1G | FCER1G | FCER1G | 2115 | 0.2 | 0.53 | YES
24 | PLCG2 | PLCG2 | PLCG2 | 2125 | 0.2 | 0.55 | YES
25 | PIK3R3 | PIK3R3 | PIK3R3 | 2317 | 0.19 | 0.55 | YES
26 | RAC2 | RAC2 | RAC2 | 2407 | 0.18 | 0.56 | YES
27 | MAP2K6 | MAP2K6 | MAP2K6 | 2714 | 0.16 | 0.56 | YES
28 | PLA2G12A | PLA2G12A | PLA2G12A | 2764 | 0.16 | 0.57 | YES
29 | MAP2K3 | MAP2K3 | MAP2K3 | 3479 | 0.12 | 0.54 | NO
30 | JMJD7-PLA2G4B | JMJD7-PLA2G4B | JMJD7-PLA2G4B | 3584 | 0.11 | 0.55 | NO
31 | PLA2G2F | PLA2G2F | PLA2G2F | 3928 | 0.1 | 0.54 | NO
32 | PLA2G2A | PLA2G2A | PLA2G2A | 4271 | 0.088 | 0.52 | NO
33 | SOS2 | SOS2 | SOS2 | 4492 | 0.081 | 0.52 | NO
34 | PLA2G1B | PLA2G1B | PLA2G1B | 5187 | 0.063 | 0.49 | NO
35 | PLA2G2D | PLA2G2D | PLA2G2D | 6217 | 0.041 | 0.44 | NO
36 | PIK3CD | PIK3CD | PIK3CD | 7327 | 0.02 | 0.38 | NO
37 | PIK3R2 | PIK3R2 | PIK3R2 | 7455 | 0.018 | 0.37 | NO
38 | PIK3R5 | PIK3R5 | PIK3R5 | 7524 | 0.017 | 0.37 | NO
39 | KRAS | KRAS | KRAS | 7688 | 0.015 | 0.36 | NO
40 | VAV2 | VAV2 | VAV2 | 7969 | 0.0099 | 0.35 | NO
41 | MAP2K7 | MAP2K7 | MAP2K7 | 7992 | 0.0096 | 0.35 | NO
42 | RAC1 | RAC1 | RAC1 | 8132 | 0.0072 | 0.34 | NO
43 | AKT1 | AKT1 | AKT1 | 8385 | 0.0033 | 0.33 | NO
44 | GRB2 | GRB2 | GRB2 | 8509 | 0.0016 | 0.32 | NO
45 | MAPK3 | MAPK3 | MAPK3 | 9190 | -0.0085 | 0.29 | NO
46 | MAP2K2 | MAP2K2 | MAP2K2 | 9277 | -0.0098 | 0.28 | NO
47 | PIK3CA | PIK3CA | PIK3CA | 9529 | -0.013 | 0.27 | NO
48 | PLA2G5 | PLA2G5 | PLA2G5 | 10200 | -0.023 | 0.24 | NO
49 | MAPK9 | MAPK9 | MAPK9 | 10237 | -0.024 | 0.24 | NO
50 | MAP2K4 | MAP2K4 | MAP2K4 | 10806 | -0.032 | 0.21 | NO
51 | MAPK11 | MAPK11 | MAPK11 | 10842 | -0.033 | 0.21 | NO
52 | MAPK14 | MAPK14 | MAPK14 | 10901 | -0.033 | 0.21 | NO
53 | PLA2G6 | PLA2G6 | PLA2G6 | 11685 | -0.046 | 0.17 | NO
54 | MAPK1 | MAPK1 | MAPK1 | 11700 | -0.046 | 0.17 | NO
55 | SOS1 | SOS1 | SOS1 | 11857 | -0.048 | 0.17 | NO
56 | RAF1 | RAF1 | RAF1 | 12049 | -0.051 | 0.16 | NO
57 | MAPK8 | MAPK8 | MAPK8 | 12112 | -0.053 | 0.16 | NO
58 | PDK1 | PDK1 | PDK1 | 12211 | -0.054 | 0.16 | NO
59 | PRKCE | PRKCE | PRKCE | 12720 | -0.065 | 0.14 | NO
60 | NRAS | NRAS | NRAS | 13504 | -0.082 | 0.11 | NO
61 | MAP2K1 | MAP2K1 | MAP2K1 | 13567 | -0.084 | 0.11 | NO
62 | GAB2 | GAB2 | GAB2 | 14507 | -0.11 | 0.068 | NO
63 | PRKCA | PRKCA | PRKCA | 14599 | -0.12 | 0.073 | NO
64 | FYN | FYN | FYN | 14791 | -0.12 | 0.073 | NO
65 | AKT3 | AKT3 | AKT3 | 14802 | -0.12 | 0.083 | NO
66 | AKT2 | AKT2 | AKT2 | 14805 | -0.12 | 0.093 | NO
67 | PLCG1 | PLCG1 | PLCG1 | 14964 | -0.13 | 0.095 | NO
68 | PLA2G4E | PLA2G4E | PLA2G4E | 15124 | -0.14 | 0.098 | NO
69 | RAC3 | RAC3 | RAC3 | 15667 | -0.16 | 0.083 | NO
70 | PRKCB | PRKCB | PRKCB | 16822 | -0.26 | 0.042 | NO
71 | PLA2G12B | PLA2G12B | PLA2G12B | 17302 | -0.31 | 0.043 | NO
72 | MAPK12 | MAPK12 | MAPK12 | 17592 | -0.36 | 0.057 | 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 LYSOSOME.

Figure S38. Get High-res Image For the top 5 core enriched genes in the pathway: KEGG LYSOSOME, 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 APOPTOSIS

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 | RAET1L | RAET1L | RAET1L | 56 | 0.68 | 0.032 | YES
2 | TNFRSF10A | TNFRSF10A | TNFRSF10A | 87 | 0.64 | 0.064 | YES
3 | TNFSF10 | TNFSF10 | TNFSF10 | 92 | 0.64 | 0.097 | YES
4 | VAV3 | VAV3 | VAV3 | 239 | 0.53 | 0.12 | YES
5 | SYK | SYK | SYK | 246 | 0.52 | 0.14 | YES
6 | KLRC1 | KLRC1 | KLRC1 | 435 | 0.44 | 0.16 | YES
7 | CSF2 | CSF2 | CSF2 | 455 | 0.44 | 0.18 | YES
8 | TNF | TNF | TNF | 480 | 0.43 | 0.2 | YES
9 | TNFRSF10C | TNFRSF10C | TNFRSF10C | 484 | 0.43 | 0.22 | YES
10 | PTPN6 | PTPN6 | PTPN6 | 664 | 0.38 | 0.23 | YES
11 | KLRD1 | KLRD1 | KLRD1 | 719 | 0.37 | 0.25 | YES
12 | GZMB | GZMB | GZMB | 725 | 0.37 | 0.27 | YES
13 | KIR2DL4 | KIR2DL4 | KIR2DL4 | 834 | 0.35 | 0.28 | YES
14 | FCGR3B | FCGR3B | FCGR3B | 860 | 0.34 | 0.3 | YES
15 | IFNB1 | IFNB1 | IFNB1 | 867 | 0.34 | 0.31 | YES
16 | VAV1 | VAV1 | VAV1 | 910 | 0.33 | 0.33 | YES
17 | FAS | FAS | FAS | 929 | 0.33 | 0.34 | YES
18 | LCP2 | LCP2 | LCP2 | 1018 | 0.32 | 0.36 | YES
19 | IFNG | IFNG | IFNG | 1131 | 0.3 | 0.37 | YES
20 | KIR2DL3 | KIR2DL3 | KIR2DL3 | 1225 | 0.29 | 0.38 | YES
21 | PIK3CG | PIK3CG | PIK3CG | 1231 | 0.29 | 0.39 | YES
22 | ITGAL | ITGAL | ITGAL | 1506 | 0.26 | 0.39 | YES
23 | HLA-C | HLA-C | HLA-C | 1582 | 0.25 | 0.4 | YES
24 | FASLG | FASLG | FASLG | 1592 | 0.25 | 0.41 | YES
25 | KIR3DL1 | KIR3DL1 | KIR3DL1 | 1666 | 0.24 | 0.42 | YES
26 | PTK2B | PTK2B | PTK2B | 1720 | 0.24 | 0.43 | YES
27 | HLA-G | HLA-G | HLA-G | 1784 | 0.23 | 0.44 | YES
28 | PIK3R1 | PIK3R1 | PIK3R1 | 1803 | 0.23 | 0.45 | YES
29 | BRAF | BRAF | BRAF | 1854 | 0.22 | 0.46 | YES
30 | LCK | LCK | LCK | 1885 | 0.22 | 0.47 | YES
31 | HLA-B | HLA-B | HLA-B | 1908 | 0.22 | 0.48 | YES
32 | PRF1 | PRF1 | PRF1 | 2040 | 0.21 | 0.48 | YES
33 | SH2D1B | SH2D1B | SH2D1B | 2048 | 0.21 | 0.49 | YES
34 | LAT | LAT | LAT | 2057 | 0.21 | 0.5 | YES
35 | SH2D1A | SH2D1A | SH2D1A | 2062 | 0.21 | 0.51 | YES
36 | PIK3CB | PIK3CB | PIK3CB | 2111 | 0.2 | 0.52 | YES
37 | FCER1G | FCER1G | FCER1G | 2115 | 0.2 | 0.53 | YES
38 | PLCG2 | PLCG2 | PLCG2 | 2125 | 0.2 | 0.54 | YES
39 | HLA-E | HLA-E | HLA-E | 2192 | 0.19 | 0.55 | YES
40 | NCR1 | NCR1 | NCR1 | 2283 | 0.19 | 0.55 | YES
41 | PIK3R3 | PIK3R3 | PIK3R3 | 2317 | 0.19 | 0.56 | YES
42 | RAC2 | RAC2 | RAC2 | 2407 | 0.18 | 0.56 | YES
43 | NCR3 | NCR3 | NCR3 | 2434 | 0.18 | 0.57 | YES
44 | NFATC1 | NFATC1 | NFATC1 | 2472 | 0.18 | 0.58 | YES
45 | ITGB2 | ITGB2 | ITGB2 | 2654 | 0.16 | 0.58 | YES
46 | HLA-A | HLA-A | HLA-A | 2702 | 0.16 | 0.58 | YES
47 | CD244 | CD244 | CD244 | 2785 | 0.16 | 0.59 | YES
48 | KLRK1 | KLRK1 | KLRK1 | 2852 | 0.15 | 0.59 | YES
49 | FCGR3A | FCGR3A | FCGR3A | 2857 | 0.15 | 0.6 | YES
50 | TYROBP | TYROBP | TYROBP | 2858 | 0.15 | 0.61 | YES
51 | IFNGR1 | IFNGR1 | IFNGR1 | 3401 | 0.12 | 0.58 | NO
52 | KIR3DL2 | KIR3DL2 | KIR3DL2 | 3412 | 0.12 | 0.59 | NO
53 | HCST | HCST | HCST | 3687 | 0.11 | 0.58 | NO
54 | ICAM2 | ICAM2 | ICAM2 | 3776 | 0.11 | 0.58 | NO
55 | MICA | MICA | MICA | 4327 | 0.086 | 0.56 | NO
56 | SOS2 | SOS2 | SOS2 | 4492 | 0.081 | 0.55 | NO
57 | PPP3CC | PPP3CC | PPP3CC | 4512 | 0.08 | 0.56 | NO
58 | IFNAR1 | IFNAR1 | IFNAR1 | 4870 | 0.071 | 0.54 | NO
59 | CHP | CHP | CHP | 5049 | 0.066 | 0.54 | NO
60 | RAET1G | RAET1G | RAET1G | 5051 | 0.066 | 0.54 | NO
61 | PAK1 | PAK1 | PAK1 | 5268 | 0.061 | 0.53 | NO
62 | CD247 | CD247 | CD247 | 5598 | 0.053 | 0.52 | NO
63 | ARAF | ARAF | ARAF | 5820 | 0.049 | 0.5 | NO
64 | ICAM1 | ICAM1 | ICAM1 | 5953 | 0.046 | 0.5 | NO
65 | PPP3CA | PPP3CA | PPP3CA | 6281 | 0.039 | 0.48 | NO
66 | SH3BP2 | SH3BP2 | SH3BP2 | 6710 | 0.031 | 0.46 | NO
67 | PIK3CD | PIK3CD | PIK3CD | 7327 | 0.02 | 0.43 | NO
68 | PIK3R2 | PIK3R2 | PIK3R2 | 7455 | 0.018 | 0.42 | NO
69 | CASP3 | CASP3 | CASP3 | 7498 | 0.018 | 0.42 | NO
70 | PIK3R5 | PIK3R5 | PIK3R5 | 7524 | 0.017 | 0.42 | NO
71 | ULBP2 | ULBP2 | ULBP2 | 7563 | 0.016 | 0.42 | NO
72 | KRAS | KRAS | KRAS | 7688 | 0.015 | 0.42 | NO
73 | VAV2 | VAV2 | VAV2 | 7969 | 0.0099 | 0.4 | NO
74 | RAET1E | RAET1E | RAET1E | 8099 | 0.0077 | 0.4 | NO
75 | RAC1 | RAC1 | RAC1 | 8132 | 0.0072 | 0.39 | NO
76 | NFATC4 | NFATC4 | NFATC4 | 8199 | 0.0061 | 0.39 | NO
77 | BID | BID | BID | 8257 | 0.0053 | 0.39 | NO
78 | NFATC3 | NFATC3 | NFATC3 | 8345 | 0.0038 | 0.38 | NO
79 | GRB2 | GRB2 | GRB2 | 8509 | 0.0016 | 0.38 | NO
80 | IFNGR2 | IFNGR2 | IFNGR2 | 8593 | 0.00025 | 0.37 | NO
81 | KIR2DS4 | KIR2DS4 | KIR2DS4 | 8693 | -0.0012 | 0.36 | NO
82 | IFNAR2 | IFNAR2 | IFNAR2 | 9049 | -0.0064 | 0.35 | NO
83 | MAPK3 | MAPK3 | MAPK3 | 9190 | -0.0085 | 0.34 | NO
84 | MAP2K2 | MAP2K2 | MAP2K2 | 9277 | -0.0098 | 0.34 | NO
85 | TNFRSF10B | TNFRSF10B | TNFRSF10B | 9406 | -0.012 | 0.33 | NO
86 | PIK3CA | PIK3CA | PIK3CA | 9529 | -0.013 | 0.32 | NO
87 | NFATC2 | NFATC2 | NFATC2 | 9868 | -0.018 | 0.3 | NO
88 | KLRC3 | KLRC3 | KLRC3 | 10086 | -0.021 | 0.3 | NO
89 | KIR2DL1 | KIR2DL1 | KIR2DL1 | 10768 | -0.032 | 0.26 | NO
90 | PTPN11 | PTPN11 | PTPN11 | 10820 | -0.032 | 0.26 | NO
91 | ULBP3 | ULBP3 | ULBP3 | 11020 | -0.035 | 0.25 | NO
92 | NFAT5 | NFAT5 | NFAT5 | 11471 | -0.042 | 0.23 | NO
93 | MAPK1 | MAPK1 | MAPK1 | 11700 | -0.046 | 0.22 | NO
94 | SOS1 | SOS1 | SOS1 | 11857 | -0.048 | 0.21 | NO
95 | RAF1 | RAF1 | RAF1 | 12049 | -0.051 | 0.2 | NO
96 | HRAS | HRAS | HRAS | 12160 | -0.054 | 0.2 | NO
97 | CD48 | CD48 | CD48 | 12226 | -0.055 | 0.2 | NO
98 | PPP3CB | PPP3CB | PPP3CB | 12319 | -0.056 | 0.2 | NO
99 | PRKCG | PRKCG | PRKCG | 12417 | -0.058 | 0.2 | NO
100 | SHC1 | SHC1 | SHC1 | 12560 | -0.061 | 0.19 | NO
101 | PPP3R1 | PPP3R1 | PPP3R1 | 12759 | -0.066 | 0.18 | NO
102 | NRAS | NRAS | NRAS | 13504 | -0.082 | 0.15 | NO
103 | MAP2K1 | MAP2K1 | MAP2K1 | 13567 | -0.084 | 0.15 | NO
104 | TNFRSF10D | TNFRSF10D | TNFRSF10D | 13621 | -0.085 | 0.15 | NO
105 | SHC4 | SHC4 | SHC4 | 13906 | -0.093 | 0.14 | NO
106 | PPP3R2 | PPP3R2 | PPP3R2 | 14252 | -0.1 | 0.13 | NO
107 | PRKCA | PRKCA | PRKCA | 14599 | -0.12 | 0.12 | NO
108 | FYN | FYN | FYN | 14791 | -0.12 | 0.11 | NO
109 | SHC3 | SHC3 | SHC3 | 14823 | -0.12 | 0.12 | NO
110 | PLCG1 | PLCG1 | PLCG1 | 14964 | -0.13 | 0.12 | NO
111 | ZAP70 | ZAP70 | ZAP70 | 15270 | -0.14 | 0.11 | NO
112 | KLRC2 | KLRC2 | KLRC2 | 15357 | -0.15 | 0.11 | NO
113 | ULBP1 | ULBP1 | ULBP1 | 15629 | -0.16 | 0.1 | NO
114 | RAC3 | RAC3 | RAC3 | 15667 | -0.16 | 0.11 | NO
115 | SHC2 | SHC2 | SHC2 | 16328 | -0.21 | 0.085 | NO
116 | PRKCB | PRKCB | PRKCB | 16822 | -0.26 | 0.072 | NO
117 | CHP2 | CHP2 | CHP2 | 18258 | -0.51 | 0.021 | 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 APOPTOSIS.

Figure S40. Get High-res Image For the top 5 core enriched genes in the pathway: KEGG APOPTOSIS, 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

- up-regulated, please check the list of up-regulated genes

- down-regulated, please check the list of down-regulated genes

Expression level

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

- highly expressed genes, please check the list of high (top 30%) expressed genes

- low expressed genes, please check the list of low (bottom 30%) expressed genes

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

- significantly differently expressed genes by eBayes lm fit, please check the list of significant genes

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 CARM ER PATHWAY | 34 | genes.ES.table | 0.36 | 1.3 | 0.17 | 1 | 0.98 | 0.12 | 0.053 | 0.11 | 0.91 | 0.45
BIOCARTA PYK2 PATHWAY | 27 | genes.ES.table | 0.36 | 1.4 | 0.12 | 1 | 0.92 | 0.3 | 0.34 | 0.2 | 1 | 0.6
KEGG TYROSINE METABOLISM | 39 | genes.ES.table | 0.5 | 1.4 | 0.092 | 1 | 0.95 | 0.28 | 0.15 | 0.24 | 0.92 | 0.47
KEGG STARCH AND SUCROSE METABOLISM | 39 | genes.ES.table | 0.6 | 1.6 | 0.024 | 1 | 0.75 | 0.28 | 0.095 | 0.26 | 1 | 0.54
KEGG BUTANOATE METABOLISM | 31 | genes.ES.table | 0.48 | 1.4 | 0.093 | 1 | 0.92 | 0.19 | 0.034 | 0.19 | 1 | 0.54
KEGG RETINOL METABOLISM | 52 | genes.ES.table | 0.65 | 1.6 | 0.0094 | 1 | 0.67 | 0.36 | 0.071 | 0.34 | 1 | 0.61
KEGG PORPHYRIN AND CHLOROPHYLL METABOLISM | 31 | genes.ES.table | 0.58 | 1.5 | 0.063 | 1 | 0.78 | 0.19 | 0.062 | 0.18 | 1 | 0.5
KEGG METABOLISM OF XENOBIOTICS BY CYTOCHROME P450 | 58 | genes.ES.table | 0.57 | 1.4 | 0.049 | 1 | 0.91 | 0.36 | 0.15 | 0.31 | 1 | 0.65
KEGG DRUG METABOLISM CYTOCHROME P450 | 59 | genes.ES.table | 0.54 | 1.4 | 0.093 | 1 | 0.96 | 0.3 | 0.1 | 0.28 | 0.85 | 0.42
KEGG DRUG METABOLISM OTHER ENZYMES | 41 | genes.ES.table | 0.55 | 1.4 | 0.12 | 1 | 0.96 | 0.24 | 0.082 | 0.22 | 0.97 | 0.48

genes ES table in pathway: BIOCARTA CARM ER 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 | UGT2B10 | UGT2B10 | UGT2B10 | 74 | 0.69 | 0.056 | YES
2 | UGT2A3 | UGT2A3 | UGT2A3 | 75 | 0.69 | 0.12 | YES
3 | CYP2B6 | CYP2B6 | CYP2B6 | 106 | 0.65 | 0.17 | YES
4 | UGT2B15 | UGT2B15 | UGT2B15 | 245 | 0.53 | 0.21 | YES
5 | CYP2C18 | CYP2C18 | CYP2C18 | 268 | 0.52 | 0.25 | YES
6 | CYP26C1 | CYP26C1 | CYP26C1 | 327 | 0.49 | 0.29 | YES
7 | UGT2B7 | UGT2B7 | UGT2B7 | 367 | 0.48 | 0.33 | YES
8 | CYP2C9 | CYP2C9 | CYP2C9 | 544 | 0.42 | 0.36 | YES
9 | ADH1B | ADH1B | ADH1B | 643 | 0.4 | 0.38 | YES
10 | UGT2B11 | UGT2B11 | UGT2B11 | 678 | 0.4 | 0.42 | YES
11 | CYP26A1 | CYP26A1 | CYP26A1 | 681 | 0.4 | 0.45 | YES
12 | ALDH1A2 | ALDH1A2 | ALDH1A2 | 796 | 0.38 | 0.48 | YES
13 | CYP3A5 | CYP3A5 | CYP3A5 | 832 | 0.37 | 0.51 | YES
14 | BCMO1 | BCMO1 | BCMO1 | 895 | 0.36 | 0.54 | YES
15 | ADH6 | ADH6 | ADH6 | 912 | 0.36 | 0.57 | YES
16 | RDH16 | RDH16 | RDH16 | 1092 | 0.33 | 0.58 | YES
17 | UGT1A6 | UGT1A6 | UGT1A6 | 1158 | 0.33 | 0.61 | YES
18 | ADH1C | ADH1C | ADH1C | 1246 | 0.32 | 0.63 | YES
19 | ALDH1A1 | ALDH1A1 | ALDH1A1 | 1326 | 0.31 | 0.65 | YES
20 | ADH1A | ADH1A | ADH1A | 1848 | 0.26 | 0.65 | NO
21 | CYP3A7 | CYP3A7 | CYP3A7 | 2445 | 0.21 | 0.64 | NO
22 | CYP2C8 | CYP2C8 | CYP2C8 | 2778 | 0.19 | 0.63 | NO
23 | CYP4A22 | CYP4A22 | CYP4A22 | 3361 | 0.16 | 0.62 | NO
24 | UGT1A1 | UGT1A1 | UGT1A1 | 3717 | 0.15 | 0.61 | NO
25 | CYP4A11 | CYP4A11 | CYP4A11 | 4019 | 0.14 | 0.61 | NO
26 | CYP2A13 | CYP2A13 | CYP2A13 | 4212 | 0.13 | 0.61 | NO
27 | RPE65 | RPE65 | RPE65 | 4528 | 0.12 | 0.6 | NO
28 | UGT1A9 | UGT1A9 | UGT1A9 | 4541 | 0.12 | 0.61 | NO
29 | CYP3A43 | CYP3A43 | CYP3A43 | 5409 | 0.095 | 0.57 | NO
30 | CYP26B1 | CYP26B1 | CYP26B1 | 6601 | 0.067 | 0.51 | NO
31 | RDH8 | RDH8 | RDH8 | 7186 | 0.055 | 0.49 | NO
32 | ADH4 | ADH4 | ADH4 | 7264 | 0.053 | 0.49 | NO
33 | RETSAT | RETSAT | RETSAT | 7269 | 0.053 | 0.49 | NO
34 | DGAT2 | DGAT2 | DGAT2 | 7611 | 0.047 | 0.48 | NO
35 | RDH10 | RDH10 | RDH10 | 7971 | 0.041 | 0.46 | NO
36 | UGT2B4 | UGT2B4 | UGT2B4 | 8093 | 0.039 | 0.46 | NO
37 | CYP1A2 | CYP1A2 | CYP1A2 | 9088 | 0.024 | 0.41 | NO
38 | DGAT1 | DGAT1 | DGAT1 | 9279 | 0.021 | 0.4 | NO
39 | PNPLA4 | PNPLA4 | PNPLA4 | 9760 | 0.013 | 0.37 | NO
40 | RDH5 | RDH5 | RDH5 | 10170 | 0.0076 | 0.35 | NO
41 | DHRS3 | DHRS3 | DHRS3 | 10172 | 0.0076 | 0.35 | NO
42 | LRAT | LRAT | LRAT | 10822 | -0.0022 | 0.32 | NO
43 | ADH5 | ADH5 | ADH5 | 11948 | -0.02 | 0.26 | NO
44 | DHRS4 | DHRS4 | DHRS4 | 12379 | -0.027 | 0.24 | NO
45 | RDH11 | RDH11 | RDH11 | 13849 | -0.054 | 0.16 | NO
46 | DHRS4L2 | DHRS4L2 | DHRS4L2 | 14040 | -0.058 | 0.16 | NO
47 | DHRS9 | DHRS9 | DHRS9 | 14597 | -0.07 | 0.14 | NO
48 | CYP2A6 | CYP2A6 | CYP2A6 | 15304 | -0.088 | 0.1 | NO
49 | UGT2A1 | UGT2A1 | UGT2A1 | 17251 | -0.19 | 0.016 | NO
50 | CYP1A1 | CYP1A1 | CYP1A1 | 17551 | -0.22 | 0.018 | NO
51 | RDH12 | RDH12 | RDH12 | 17600 | -0.22 | 0.035 | NO
52 | AWAT2 | AWAT2 | AWAT2 | 17801 | -0.25 | 0.045 | 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 CARM ER PATHWAY.

Figure S42. Get High-res Image For the top 5 core enriched genes in the pathway: BIOCARTA CARM ER 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 PYK2 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 | UGT2B10 | UGT2B10 | UGT2B10 | 74 | 0.69 | 0.083 | YES
2 | UGT2A3 | UGT2A3 | UGT2A3 | 75 | 0.69 | 0.17 | YES
3 | MGAM | MGAM | MGAM | 91 | 0.67 | 0.25 | YES
4 | ENPP3 | ENPP3 | ENPP3 | 173 | 0.58 | 0.32 | YES
5 | AMY2B | AMY2B | AMY2B | 223 | 0.54 | 0.39 | YES
6 | UGT2B15 | UGT2B15 | UGT2B15 | 245 | 0.53 | 0.45 | YES
7 | UGT2B7 | UGT2B7 | UGT2B7 | 367 | 0.48 | 0.5 | YES
8 | UGT2B11 | UGT2B11 | UGT2B11 | 678 | 0.4 | 0.54 | YES
9 | AMY2A | AMY2A | AMY2A | 694 | 0.39 | 0.59 | YES
10 | UGT1A6 | UGT1A6 | UGT1A6 | 1158 | 0.33 | 0.6 | YES
11 | GCK | GCK | GCK | 1766 | 0.26 | 0.6 | YES
12 | AMY1A | AMY1A | AMY1A | 2556 | 0.21 | 0.59 | NO
13 | UGT1A1 | UGT1A1 | UGT1A1 | 3717 | 0.15 | 0.54 | NO
14 | UGT1A9 | UGT1A9 | UGT1A9 | 4541 | 0.12 | 0.51 | NO
15 | G6PC | G6PC | G6PC | 5492 | 0.093 | 0.47 | NO
16 | GAA | GAA | GAA | 5744 | 0.087 | 0.47 | NO
17 | PYGB | PYGB | PYGB | 7010 | 0.058 | 0.41 | NO
18 | HK2 | HK2 | HK2 | 7056 | 0.057 | 0.42 | NO
19 | UGDH | UGDH | UGDH | 7070 | 0.056 | 0.42 | NO
20 | TREH | TREH | TREH | 7581 | 0.048 | 0.4 | NO
21 | GYS1 | GYS1 | GYS1 | 7772 | 0.044 | 0.4 | NO
22 | UGT2B4 | UGT2B4 | UGT2B4 | 8093 | 0.039 | 0.38 | NO
23 | GPI | GPI | GPI | 9189 | 0.022 | 0.33 | NO
24 | GYS2 | GYS2 | GYS2 | 9435 | 0.019 | 0.32 | NO
25 | GBA3 | GBA3 | GBA3 | 9550 | 0.016 | 0.31 | NO
26 | HK1 | HK1 | HK1 | 10265 | 0.0062 | 0.27 | NO
27 | HK3 | HK3 | HK3 | 10349 | 0.0051 | 0.27 | NO
28 | GANC | GANC | GANC | 11494 | -0.012 | 0.21 | NO
29 | GUSB | GUSB | GUSB | 13061 | -0.038 | 0.13 | NO
30 | PGM2L1 | PGM2L1 | PGM2L1 | 13232 | -0.041 | 0.13 | NO
31 | UGP2 | UGP2 | UGP2 | 14958 | -0.079 | 0.045 | NO
32 | PYGM | PYGM | PYGM | 15741 | -0.1 | 0.016 | NO
33 | AGL | AGL | AGL | 15978 | -0.11 | 0.017 | NO
34 | PGM2 | PGM2 | PGM2 | 15983 | -0.11 | 0.031 | NO
35 | PGM1 | PGM1 | PGM1 | 16287 | -0.12 | 0.03 | NO
36 | ENPP1 | ENPP1 | ENPP1 | 16398 | -0.13 | 0.04 | NO
37 | UGT2A1 | UGT2A1 | UGT2A1 | 17251 | -0.19 | 0.018 | NO
38 | PYGL | PYGL | PYGL | 17524 | -0.21 | 0.03 | NO
39 | GBE1 | GBE1 | GBE1 | 17752 | -0.24 | 0.048 | 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 PYK2 PATHWAY.

Figure S44. Get High-res Image For the top 5 core enriched genes in the pathway: BIOCARTA PYK2 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 TYROSINE METABOLISM

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 | UGT2B10 | UGT2B10 | UGT2B10 | 74 | 0.69 | 0.14 | YES
2 | UGT2A3 | UGT2A3 | UGT2A3 | 75 | 0.69 | 0.28 | YES
3 | UGT2B15 | UGT2B15 | UGT2B15 | 245 | 0.53 | 0.38 | YES
4 | UGT2B7 | UGT2B7 | UGT2B7 | 367 | 0.48 | 0.47 | YES
5 | UGT2B11 | UGT2B11 | UGT2B11 | 678 | 0.4 | 0.54 | YES
6 | UGT1A6 | UGT1A6 | UGT1A6 | 1158 | 0.33 | 0.58 | YES
7 | UGT1A1 | UGT1A1 | UGT1A1 | 3717 | 0.15 | 0.47 | NO
8 | PPOX | PPOX | PPOX | 4171 | 0.13 | 0.48 | NO
9 | UGT1A9 | UGT1A9 | UGT1A9 | 4541 | 0.12 | 0.48 | NO
10 | CPOX | CPOX | CPOX | 7218 | 0.054 | 0.35 | NO
11 | UGT2B4 | UGT2B4 | UGT2B4 | 8093 | 0.039 | 0.31 | NO
12 | COX15 | COX15 | COX15 | 8137 | 0.038 | 0.32 | NO
13 | ALAD | ALAD | ALAD | 8635 | 0.031 | 0.3 | NO
14 | EARS2 | EARS2 | EARS2 | 9288 | 0.021 | 0.26 | NO
15 | ALAS2 | ALAS2 | ALAS2 | 10228 | 0.0068 | 0.22 | NO
16 | UROD | UROD | UROD | 10714 | -0.00046 | 0.19 | NO
17 | UROS | UROS | UROS | 10951 | -0.0041 | 0.18 | NO
18 | HMOX2 | HMOX2 | HMOX2 | 11399 | -0.011 | 0.16 | NO
19 | HMBS | HMBS | HMBS | 11952 | -0.02 | 0.13 | NO
20 | BLVRB | BLVRB | BLVRB | 12299 | -0.026 | 0.12 | NO
21 | GUSB | GUSB | GUSB | 13061 | -0.038 | 0.084 | NO
22 | FECH | FECH | FECH | 13245 | -0.042 | 0.083 | NO
23 | EPRS | EPRS | EPRS | 13285 | -0.042 | 0.09 | NO
24 | FTH1 | FTH1 | FTH1 | 14891 | -0.077 | 0.02 | NO
25 | BLVRA | BLVRA | BLVRA | 15020 | -0.08 | 0.029 | NO
26 | COX10 | COX10 | COX10 | 15189 | -0.085 | 0.038 | NO
27 | ALAS1 | ALAS1 | ALAS1 | 15878 | -0.11 | 0.023 | NO
28 | MMAB | MMAB | MMAB | 16482 | -0.13 | 0.018 | NO
29 | CP | CP | CP | 16612 | -0.14 | 0.04 | NO
30 | HMOX1 | HMOX1 | HMOX1 | 16686 | -0.14 | 0.066 | NO
31 | UGT2A1 | UGT2A1 | UGT2A1 | 17251 | -0.19 | 0.075 | 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: KEGG TYROSINE METABOLISM.

Figure S46. 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 STARCH AND SUCROSE METABOLISM

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 | UGT2B10 | UGT2B10 | UGT2B10 | 74 | 0.69 | 0.055 | YES
2 | UGT2A3 | UGT2A3 | UGT2A3 | 75 | 0.69 | 0.12 | YES
3 | CYP2B6 | CYP2B6 | CYP2B6 | 106 | 0.65 | 0.17 | YES
4 | UGT2B15 | UGT2B15 | UGT2B15 | 245 | 0.53 | 0.21 | YES
5 | CYP2C18 | CYP2C18 | CYP2C18 | 268 | 0.52 | 0.25 | YES
6 | DHDH | DHDH | DHDH | 325 | 0.49 | 0.29 | YES
7 | UGT2B7 | UGT2B7 | UGT2B7 | 367 | 0.48 | 0.33 | YES
8 | CYP2C9 | CYP2C9 | CYP2C9 | 544 | 0.42 | 0.36 | YES
9 | ADH1B | ADH1B | ADH1B | 643 | 0.4 | 0.38 | YES
10 | UGT2B11 | UGT2B11 | UGT2B11 | 678 | 0.4 | 0.42 | YES
11 | CYP3A5 | CYP3A5 | CYP3A5 | 832 | 0.37 | 0.44 | YES
12 | ADH6 | ADH6 | ADH6 | 912 | 0.36 | 0.47 | YES
13 | UGT1A6 | UGT1A6 | UGT1A6 | 1158 | 0.33 | 0.48 | YES
14 | ADH1C | ADH1C | ADH1C | 1246 | 0.32 | 0.5 | YES
15 | GSTA1 | GSTA1 | GSTA1 | 1287 | 0.31 | 0.53 | YES
16 | GSTA2 | GSTA2 | GSTA2 | 1775 | 0.26 | 0.52 | YES
17 | ADH1A | ADH1A | ADH1A | 1848 | 0.26 | 0.54 | YES
18 | GSTO2 | GSTO2 | GSTO2 | 1873 | 0.26 | 0.56 | YES
19 | CYP3A7 | CYP3A7 | CYP3A7 | 2445 | 0.21 | 0.55 | YES
20 | CYP2S1 | CYP2S1 | CYP2S1 | 2478 | 0.21 | 0.57 | YES
21 | CYP2C8 | CYP2C8 | CYP2C8 | 2778 | 0.19 | 0.57 | YES
22 | AKR1C2 | AKR1C2 | AKR1C2 | 3149 | 0.17 | 0.56 | NO
23 | MGST1 | MGST1 | MGST1 | 3507 | 0.16 | 0.56 | NO
24 | UGT1A1 | UGT1A1 | UGT1A1 | 3717 | 0.15 | 0.56 | NO
25 | GSTT1 | GSTT1 | GSTT1 | 3866 | 0.14 | 0.56 | NO
26 | GSTT2 | GSTT2 | GSTT2 | 4507 | 0.12 | 0.54 | NO
27 | UGT1A9 | UGT1A9 | UGT1A9 | 4541 | 0.12 | 0.55 | NO
28 | AKR1C1 | AKR1C1 | AKR1C1 | 4948 | 0.11 | 0.54 | NO
29 | GSTM2 | GSTM2 | GSTM2 | 5166 | 0.1 | 0.53 | NO
30 | CYP3A43 | CYP3A43 | CYP3A43 | 5409 | 0.095 | 0.53 | NO
31 | ALDH3B2 | ALDH3B2 | ALDH3B2 | 5798 | 0.086 | 0.52 | NO
32 | GSTP1 | GSTP1 | GSTP1 | 6945 | 0.059 | 0.46 | NO
33 | GSTM5 | GSTM5 | GSTM5 | 7249 | 0.053 | 0.45 | NO
34 | ADH4 | ADH4 | ADH4 | 7264 | 0.053 | 0.45 | NO
35 | AKR1C4 | AKR1C4 | AKR1C4 | 7856 | 0.043 | 0.42 | NO
36 | UGT2B4 | UGT2B4 | UGT2B4 | 8093 | 0.039 | 0.41 | NO
37 | CYP1B1 | CYP1B1 | CYP1B1 | 8095 | 0.039 | 0.42 | NO
38 | GSTK1 | GSTK1 | GSTK1 | 8562 | 0.032 | 0.39 | NO
39 | ALDH3A1 | ALDH3A1 | ALDH3A1 | 9056 | 0.024 | 0.37 | NO
40 | CYP1A2 | CYP1A2 | CYP1A2 | 9088 | 0.024 | 0.37 | NO
41 | GSTA4 | GSTA4 | GSTA4 | 9592 | 0.016 | 0.34 | NO
42 | GSTO1 | GSTO1 | GSTO1 | 10424 | 0.0037 | 0.3 | NO
43 | CYP2E1 | CYP2E1 | CYP2E1 | 10869 | -0.0028 | 0.28 | NO
44 | MGST3 | MGST3 | MGST3 | 11760 | -0.016 | 0.23 | NO
45 | GSTM4 | GSTM4 | GSTM4 | 11920 | -0.019 | 0.22 | NO
46 | ADH5 | ADH5 | ADH5 | 11948 | -0.02 | 0.22 | NO
47 | ALDH3B1 | ALDH3B1 | ALDH3B1 | 12634 | -0.031 | 0.19 | NO
48 | MGST2 | MGST2 | MGST2 | 13719 | -0.051 | 0.14 | NO
49 | GSTZ1 | GSTZ1 | GSTZ1 | 14800 | -0.075 | 0.083 | NO
50 | GSTM3 | GSTM3 | GSTM3 | 15341 | -0.089 | 0.062 | NO
51 | CYP2F1 | CYP2F1 | CYP2F1 | 16145 | -0.12 | 0.029 | NO
52 | GSTA3 | GSTA3 | GSTA3 | 16453 | -0.13 | 0.024 | NO
53 | EPHX1 | EPHX1 | EPHX1 | 16582 | -0.14 | 0.029 | NO
54 | ALDH1A3 | ALDH1A3 | ALDH1A3 | 16697 | -0.14 | 0.035 | NO
55 | UGT2A1 | UGT2A1 | UGT2A1 | 17251 | -0.19 | 0.021 | NO
56 | GSTM1 | GSTM1 | GSTM1 | 17345 | -0.2 | 0.033 | NO
57 | AKR1C3 | AKR1C3 | AKR1C3 | 17516 | -0.21 | 0.042 | NO
58 | CYP1A1 | CYP1A1 | CYP1A1 | 17551 | -0.22 | 0.059 | 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: KEGG STARCH AND SUCROSE METABOLISM.

Figure S48. 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 BUTANOATE METABOLISM

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 | PRKCA | PRKCA | PRKCA | 1080 | 0.34 | 0.12 | YES
2 | MAP3K1 | MAP3K1 | MAP3K1 | 1307 | 0.31 | 0.28 | YES
3 | SRC | SRC | SRC | 3145 | 0.17 | 0.27 | YES
4 | PLCG1 | PLCG1 | PLCG1 | 3763 | 0.15 | 0.32 | YES
5 | MAPK8 | MAPK8 | MAPK8 | 5098 | 0.1 | 0.3 | YES
6 | JUN | JUN | JUN | 5256 | 0.099 | 0.34 | YES
7 | SOS1 | SOS1 | SOS1 | 6210 | 0.076 | 0.33 | YES
8 | BCAR1 | BCAR1 | BCAR1 | 6377 | 0.072 | 0.36 | YES
9 | MAPK3 | MAPK3 | MAPK3 | 7776 | 0.044 | 0.31 | NO
10 | CALM3 | CALM3 | CALM3 | 8106 | 0.039 | 0.32 | NO
11 | GNAQ | GNAQ | GNAQ | 8353 | 0.035 | 0.32 | NO
12 | GRB2 | GRB2 | GRB2 | 8362 | 0.035 | 0.34 | NO
13 | SHC1 | SHC1 | SHC1 | 8632 | 0.031 | 0.34 | NO
14 | CALM2 | CALM2 | CALM2 | 8969 | 0.026 | 0.34 | NO
15 | MAP2K3 | MAP2K3 | MAP2K3 | 9231 | 0.021 | 0.33 | NO
16 | MAP2K4 | MAP2K4 | MAP2K4 | 9407 | 0.019 | 0.34 | NO
17 | PAK1 | PAK1 | PAK1 | 9552 | 0.016 | 0.34 | NO
18 | PTK2B | PTK2B | PTK2B | 10032 | 0.0096 | 0.32 | NO
19 | CRKL | CRKL | CRKL | 10118 | 0.0082 | 0.32 | NO
20 | MAPK1 | MAPK1 | MAPK1 | 10326 | 0.0054 | 0.31 | NO
21 | MAPK14 | MAPK14 | MAPK14 | 10384 | 0.0045 | 0.31 | NO
22 | RAC1 | RAC1 | RAC1 | 11403 | -0.011 | 0.26 | NO
23 | RAF1 | RAF1 | RAF1 | 12065 | -0.022 | 0.23 | NO
24 | CALM1 | CALM1 | CALM1 | 13039 | -0.038 | 0.2 | NO
25 | PRKCB | PRKCB | PRKCB | 13258 | -0.042 | 0.21 | NO
26 | MAP2K2 | MAP2K2 | MAP2K2 | 14068 | -0.059 | 0.2 | NO
27 | MAP2K1 | MAP2K1 | MAP2K1 | 15149 | -0.084 | 0.19 | 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: KEGG BUTANOATE METABOLISM.

Figure S50. Get High-res Image For the top 5 core enriched genes in the pathway: KEGG BUTANOATE 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 RETINOL METABOLISM

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 | HMGCS2 | HMGCS2 | HMGCS2 | 112 | 0.64 | 0.11 | YES
2 | ACSM3 | ACSM3 | ACSM3 | 253 | 0.52 | 0.2 | YES
3 | ABAT | ABAT | ABAT | 438 | 0.45 | 0.27 | YES
4 | ACSM1 | ACSM1 | ACSM1 | 540 | 0.42 | 0.34 | YES
5 | ACSM2A | ACSM2A | ACSM2A | 550 | 0.42 | 0.42 | YES
6 | GAD2 | GAD2 | GAD2 | 633 | 0.4 | 0.48 | YES
7 | ACSM5 | ACSM5 | ACSM5 | 3720 | 0.15 | 0.34 | NO
8 | BDH2 | BDH2 | BDH2 | 4769 | 0.11 | 0.31 | NO
9 | ALDH7A1 | ALDH7A1 | ALDH7A1 | 5294 | 0.098 | 0.3 | NO
10 | BDH1 | BDH1 | BDH1 | 6245 | 0.076 | 0.26 | NO
11 | ALDH2 | ALDH2 | ALDH2 | 7280 | 0.053 | 0.21 | NO
12 | HADHA | HADHA | HADHA | 10097 | 0.0085 | 0.064 | NO
13 | L2HGDH | L2HGDH | L2HGDH | 10257 | 0.0063 | 0.057 | NO
14 | ALDH5A1 | ALDH5A1 | ALDH5A1 | 11025 | -0.0051 | 0.017 | NO
15 | HMGCL | HMGCL | HMGCL | 11047 | -0.0055 | 0.017 | NO
16 | HMGCS1 | HMGCS1 | HMGCS1 | 12206 | -0.024 | -0.041 | NO
17 | ECHS1 | ECHS1 | ECHS1 | 12457 | -0.028 | -0.05 | NO
18 | PDHA1 | PDHA1 | PDHA1 | 12856 | -0.035 | -0.065 | NO
19 | ALDH9A1 | ALDH9A1 | ALDH9A1 | 13601 | -0.049 | -0.096 | NO
20 | AACS | AACS | AACS | 13752 | -0.052 | -0.094 | NO
21 | OXCT2 | OXCT2 | OXCT2 | 13900 | -0.055 | -0.092 | NO
22 | ALDH3A2 | ALDH3A2 | ALDH3A2 | 13931 | -0.056 | -0.084 | NO
23 | PDHB | PDHB | PDHB | 14025 | -0.058 | -0.079 | NO
24 | ALDH1B1 | ALDH1B1 | ALDH1B1 | 14457 | -0.067 | -0.09 | NO
25 | HADH | HADH | HADH | 16401 | -0.13 | -0.17 | NO
26 | ACAT2 | ACAT2 | ACAT2 | 16739 | -0.15 | -0.16 | NO
27 | ACAT1 | ACAT1 | ACAT1 | 16834 | -0.15 | -0.14 | NO
28 | ACADS | ACADS | ACADS | 17248 | -0.19 | -0.13 | NO
29 | OXCT1 | OXCT1 | OXCT1 | 18229 | -0.33 | -0.12 | NO
30 | GAD1 | GAD1 | GAD1 | 18309 | -0.35 | -0.063 | NO
31 | AKR1B10 | AKR1B10 | AKR1B10 | 18519 | -0.45 | 0.0068 | 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: KEGG RETINOL METABOLISM.

Figure S52. Get High-res Image For the top 5 core enriched genes in the pathway: KEGG RETINOL 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 PORPHYRIN AND CHLOROPHYLL METABOLISM

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 | CLDN19 | CLDN19 | CLDN19 | 27 | 0.82 | 0.039 | YES
2 | CLDN6 | CLDN6 | CLDN6 | 92 | 0.67 | 0.068 | YES
3 | PRKCQ | PRKCQ | PRKCQ | 102 | 0.65 | 0.1 | YES
4 | PARD6B | PARD6B | PARD6B | 180 | 0.57 | 0.12 | YES
5 | CLDN2 | CLDN2 | CLDN2 | 199 | 0.55 | 0.15 | YES
6 | CLDN11 | CLDN11 | CLDN11 | 405 | 0.46 | 0.16 | YES
7 | RAB3B | RAB3B | RAB3B | 518 | 0.43 | 0.18 | YES
8 | CRB3 | CRB3 | CRB3 | 732 | 0.39 | 0.18 | YES
9 | CLDN3 | CLDN3 | CLDN3 | 904 | 0.36 | 0.19 | YES
10 | PPP2R2C | PPP2R2C | PPP2R2C | 1030 | 0.34 | 0.2 | YES
11 | CGN | CGN | CGN | 1038 | 0.34 | 0.22 | YES
12 | PRKCA | PRKCA | PRKCA | 1080 | 0.34 | 0.24 | YES
13 | CLDN23 | CLDN23 | CLDN23 | 1207 | 0.32 | 0.24 | YES
14 | LLGL2 | LLGL2 | LLGL2 | 1248 | 0.32 | 0.26 | YES
15 | IGSF5 | IGSF5 | IGSF5 | 1275 | 0.31 | 0.27 | YES
16 | CTNNA2 | CTNNA2 | CTNNA2 | 1304 | 0.31 | 0.28 | YES
17 | CLDN9 | CLDN9 | CLDN9 | 1401 | 0.3 | 0.3 | YES
18 | OCLN | OCLN | OCLN | 1506 | 0.29 | 0.3 | YES
19 | CLDN4 | CLDN4 | CLDN4 | 1598 | 0.28 | 0.31 | YES
20 | MYH11 | MYH11 | MYH11 | 1628 | 0.28 | 0.32 | YES
21 | CLDN8 | CLDN8 | CLDN8 | 1663 | 0.27 | 0.34 | YES
22 | CLDN20 | CLDN20 | CLDN20 | 1731 | 0.27 | 0.35 | YES
23 | PRKCZ | PRKCZ | PRKCZ | 1801 | 0.26 | 0.36 | YES
24 | CLDN18 | CLDN18 | CLDN18 | 1829 | 0.26 | 0.37 | YES
25 | TJP3 | TJP3 | TJP3 | 1835 | 0.26 | 0.38 | YES
26 | TJP2 | TJP2 | TJP2 | 1915 | 0.25 | 0.39 | YES
27 | PPP2R2B | PPP2R2B | PPP2R2B | 2214 | 0.23 | 0.38 | YES
28 | PARD6A | PARD6A | PARD6A | 2336 | 0.22 | 0.39 | YES
29 | MYH14 | MYH14 | MYH14 | 2388 | 0.22 | 0.4 | YES
30 | CLDN7 | CLDN7 | CLDN7 | 2635 | 0.2 | 0.39 | YES
31 | MAGI2 | MAGI2 | MAGI2 | 2717 | 0.2 | 0.4 | YES
32 | PRKCG | PRKCG | PRKCG | 2750 | 0.19 | 0.4 | YES
33 | JAM3 | JAM3 | JAM3 | 2910 | 0.19 | 0.4 | YES
34 | SRC | SRC | SRC | 3145 | 0.17 | 0.4 | YES
35 | MYH15 | MYH15 | MYH15 | 3321 | 0.16 | 0.4 | YES
36 | F11R | F11R | F11R | 3377 | 0.16 | 0.4 | YES
37 | EPB41L1 | EPB41L1 | EPB41L1 | 3470 | 0.16 | 0.41 | YES
38 | CLDN14 | CLDN14 | CLDN14 | 3631 | 0.15 | 0.41 | YES
39 | CLDN1 | CLDN1 | CLDN1 | 3700 | 0.15 | 0.41 | YES
40 | INADL | INADL | INADL | 3952 | 0.14 | 0.4 | NO
41 | MAGI1 | MAGI1 | MAGI1 | 4327 | 0.13 | 0.39 | NO
42 | MYH10 | MYH10 | MYH10 | 5302 | 0.098 | 0.34 | NO
43 | PRKCI | PRKCI | PRKCI | 5319 | 0.098 | 0.35 | NO
44 | GNAI1 | GNAI1 | GNAI1 | 5449 | 0.094 | 0.34 | NO
45 | MLLT4 | MLLT4 | MLLT4 | 5630 | 0.089 | 0.34 | NO
46 | MYL9 | MYL9 | MYL9 | 5910 | 0.083 | 0.33 | NO
47 | CLDN16 | CLDN16 | CLDN16 | 5965 | 0.082 | 0.33 | NO
48 | KRAS | KRAS | KRAS | 6009 | 0.08 | 0.33 | NO
49 | MAGI3 | MAGI3 | MAGI3 | 6304 | 0.074 | 0.32 | NO
50 | MYH9 | MYH9 | MYH9 | 6314 | 0.074 | 0.32 | NO
51 | RRAS | RRAS | RRAS | 6358 | 0.073 | 0.32 | NO
52 | PPP2R1A | PPP2R1A | PPP2R1A | 6441 | 0.071 | 0.32 | NO
53 | PRKCE | PRKCE | PRKCE | 6495 | 0.07 | 0.32 | NO
54 | LLGL1 | LLGL1 | LLGL1 | 6522 | 0.069 | 0.32 | NO
55 | TJP1 | TJP1 | TJP1 | 6718 | 0.064 | 0.32 | NO
56 | SYMPK | SYMPK | SYMPK | 6742 | 0.064 | 0.32 | NO
57 | MPP5 | MPP5 | MPP5 | 6905 | 0.06 | 0.31 | NO
58 | AKT3 | AKT3 | AKT3 | 6911 | 0.06 | 0.32 | NO
59 | CLDN15 | CLDN15 | CLDN15 | 6954 | 0.059 | 0.32 | NO
60 | ACTN4 | ACTN4 | ACTN4 | 6981 | 0.059 | 0.32 | NO
61 | PRKCD | PRKCD | PRKCD | 7784 | 0.044 | 0.28 | NO
62 | ACTG1 | ACTG1 | ACTG1 | 7795 | 0.044 | 0.28 | NO
63 | MPDZ | MPDZ | MPDZ | 8043 | 0.04 | 0.27 | NO
64 | EXOC4 | EXOC4 | EXOC4 | 8068 | 0.04 | 0.27 | NO
65 | AKT2 | AKT2 | AKT2 | 8212 | 0.037 | 0.26 | NO
66 | SPTAN1 | SPTAN1 | SPTAN1 | 8213 | 0.037 | 0.26 | NO
67 | PTEN | PTEN | PTEN | 8282 | 0.036 | 0.26 | NO
68 | CTTN | CTTN | CTTN | 8597 | 0.031 | 0.25 | NO
69 | CASK | CASK | CASK | 8863 | 0.027 | 0.23 | NO
70 | CTNNA1 | CTNNA1 | CTNNA1 | 8876 | 0.027 | 0.23 | NO
71 | EPB41 | EPB41 | EPB41 | 8882 | 0.027 | 0.24 | NO
72 | PARD3 | PARD3 | PARD3 | 9004 | 0.025 | 0.23 | NO
73 | CSNK2A2 | CSNK2A2 | CSNK2A2 | 9018 | 0.025 | 0.23 | NO
74 | ASH1L | ASH1L | ASH1L | 9092 | 0.024 | 0.23 | NO
75 | CSNK2A1 | CSNK2A1 | CSNK2A1 | 9190 | 0.022 | 0.22 | NO
76 | MYL12B | MYL12B | MYL12B | 9563 | 0.016 | 0.2 | NO
77 | PPP2R2D | PPP2R2D | PPP2R2D | 9668 | 0.015 | 0.2 | NO
78 | GNAI2 | GNAI2 | GNAI2 | 9921 | 0.011 | 0.19 | NO
79 | RAB13 | RAB13 | RAB13 | 10207 | 0.0071 | 0.17 | NO
80 | AMOTL1 | AMOTL1 | AMOTL1 | 10435 | 0.0036 | 0.16 | NO
81 | TJAP1 | TJAP1 | TJAP1 | 10453 | 0.0034 | 0.16 | NO
82 | CTNNB1 | CTNNB1 | CTNNB1 | 10556 | 0.0018 | 0.15 | NO
83 | AKT1 | AKT1 | AKT1 | 10790 | -0.0018 | 0.14 | NO
84 | CTNNA3 | CTNNA3 | CTNNA3 | 10814 | -0.0021 | 0.14 | NO
85 | CSNK2B | CSNK2B | CSNK2B | 10925 | -0.0036 | 0.13 | NO
86 | MYL7 | MYL7 | MYL7 | 11043 | -0.0055 | 0.13 | NO
87 | PARD6G | PARD6G | PARD6G | 11060 | -0.0058 | 0.13 | NO
88 | PPP2R2A | PPP2R2A | PPP2R2A | 11792 | -0.017 | 0.088 | NO
89 | PPP2CA | PPP2CA | PPP2CA | 11993 | -0.02 | 0.078 | NO
90 | NRAS | NRAS | NRAS | 12015 | -0.021 | 0.078 | NO
91 | ACTB | ACTB | ACTB | 12142 | -0.023 | 0.072 | NO
92 | EPB41L3 | EPB41L3 | EPB41L3 | 12146 | -0.023 | 0.073 | NO
93 | MYL12A | MYL12A | MYL12A | 12298 | -0.026 | 0.066 | NO
94 | RHOA | RHOA | RHOA | 12637 | -0.031 | 0.05 | NO
95 | ACTN1 | ACTN1 | ACTN1 | 12644 | -0.031 | 0.051 | NO
96 | GNAI3 | GNAI3 | GNAI3 | 12750 | -0.033 | 0.047 | NO
97 | EPB41L2 | EPB41L2 | EPB41L2 | 12899 | -0.036 | 0.04 | NO
98 | PPP2CB | PPP2CB | PPP2CB | 13128 | -0.04 | 0.03 | NO
99 | CDC42 | CDC42 | CDC42 | 13159 | -0.04 | 0.03 | NO
100 | PRKCB | PRKCB | PRKCB | 13258 | -0.042 | 0.027 | NO
101 | CDK4 | CDK4 | CDK4 | 13343 | -0.044 | 0.025 | NO
102 | PPP2R1B | PPP2R1B | PPP2R1B | 13491 | -0.046 | 0.019 | NO
103 | CSDA | CSDA | CSDA | 13680 | -0.05 | 0.012 | NO
104 | YES1 | YES1 | YES1 | 13832 | -0.053 | 0.006 | NO
105 | RRAS2 | RRAS2 | RRAS2 | 13982 | -0.056 | 0.00077 | NO
106 | EXOC3 | EXOC3 | EXOC3 | 14174 | -0.06 | -0.0066 | NO
107 | CLDN5 | CLDN5 | CLDN5 | 14414 | -0.066 | -0.016 | NO
108 | VAPA | VAPA | VAPA | 14733 | -0.073 | -0.03 | NO
109 | ZAK | ZAK | ZAK | 14992 | -0.08 | -0.04 | NO
110 | CLDN10 | CLDN10 | CLDN10 | 15310 | -0.088 | -0.052 | NO
111 | PRKCH | PRKCH | PRKCH | 15979 | -0.11 | -0.083 | NO
112 | MYH6 | MYH6 | MYH6 | 16100 | -0.12 | -0.084 | NO
113 | ACTN3 | ACTN3 | ACTN3 | 16759 | -0.15 | -0.11 | NO
114 | MRAS | MRAS | MRAS | 16802 | -0.15 | -0.11 | NO
115 | MYL5 | MYL5 | MYL5 | 17413 | -0.2 | -0.13 | NO
116 | HCLS1 | HCLS1 | HCLS1 | 17582 | -0.22 | -0.13 | NO
117 | MYH7B | MYH7B | MYH7B | 17691 | -0.23 | -0.12 | NO
118 | MYH4 | MYH4 | MYH4 | 17697 | -0.23 | -0.11 | NO
119 | MYH3 | MYH3 | MYH3 | 17707 | -0.23 | -0.1 | NO
120 | MYH2 | MYH2 | MYH2 | 17758 | -0.24 | -0.091 | NO
121 | MYH7 | MYH7 | MYH7 | 17798 | -0.25 | -0.081 | NO
122 | MYLPF | MYLPF | MYLPF | 17835 | -0.25 | -0.07 | NO
123 | MYL2 | MYL2 | MYL2 | 17895 | -0.26 | -0.061 | NO
124 | MYL10 | MYL10 | MYL10 | 18057 | -0.29 | -0.055 | NO
125 | MYH8 | MYH8 | MYH8 | 18067 | -0.29 | -0.041 | NO
126 | ACTN2 | ACTN2 | ACTN2 | 18171 | -0.32 | -0.031 | NO
127 | MYH13 | MYH13 | MYH13 | 18299 | -0.35 | -0.021 | NO
128 | JAM2 | JAM2 | JAM2 | 18426 | -0.4 | -0.008 | NO
129 | MYH1 | MYH1 | MYH1 | 18432 | -0.4 | 0.012 | 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: KEGG PORPHYRIN AND CHLOROPHYLL METABOLISM.

Figure S54. Get High-res Image For the top 5 core enriched genes in the pathway: KEGG PORPHYRIN AND CHLOROPHYLL 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 METABOLISM OF XENOBIOTICS BY CYTOCHROME P450

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 | TRPM5 | TRPM5 | TRPM5 | 17 | 0.86 | 0.093 | YES
2 | ADCY8 | ADCY8 | ADCY8 | 60 | 0.72 | 0.17 | YES
3 | GNG3 | GNG3 | GNG3 | 416 | 0.46 | 0.2 | YES
4 | TAS2R14 | TAS2R14 | TAS2R14 | 556 | 0.42 | 0.24 | YES
5 | TAS2R4 | TAS2R4 | TAS2R4 | 667 | 0.4 | 0.28 | YES
6 | CACNA1B | CACNA1B | CACNA1B | 813 | 0.37 | 0.31 | YES
7 | TAS2R38 | TAS2R38 | TAS2R38 | 900 | 0.36 | 0.34 | YES
8 | SCNN1G | SCNN1G | SCNN1G | 1022 | 0.34 | 0.37 | YES
9 | SCNN1A | SCNN1A | SCNN1A | 1148 | 0.33 | 0.4 | YES
10 | TAS2R43 | TAS2R43 | TAS2R43 | 1171 | 0.32 | 0.44 | YES
11 | TAS2R5 | TAS2R5 | TAS2R5 | 1233 | 0.32 | 0.47 | YES
12 | TAS2R19 | TAS2R19 | TAS2R19 | 1473 | 0.29 | 0.49 | YES
13 | TAS2R31 | TAS2R31 | TAS2R31 | 1516 | 0.29 | 0.52 | YES
14 | TAS2R20 | TAS2R20 | TAS2R20 | 1819 | 0.26 | 0.53 | YES
15 | ACCN1 | ACCN1 | ACCN1 | 1841 | 0.26 | 0.56 | YES
16 | TAS2R10 | TAS2R10 | TAS2R10 | 1916 | 0.25 | 0.58 | YES
17 | ITPR3 | ITPR3 | ITPR3 | 3290 | 0.17 | 0.52 | NO
18 | TAS2R13 | TAS2R13 | TAS2R13 | 4150 | 0.13 | 0.49 | NO
19 | PDE1A | PDE1A | PDE1A | 4538 | 0.12 | 0.48 | NO
20 | SCNN1B | SCNN1B | SCNN1B | 4721 | 0.11 | 0.49 | NO
21 | ADCY6 | ADCY6 | ADCY6 | 4750 | 0.11 | 0.5 | NO
22 | PLCB2 | PLCB2 | PLCB2 | 4872 | 0.11 | 0.5 | NO
23 | GRM4 | GRM4 | GRM4 | 5020 | 0.1 | 0.51 | NO
24 | GNB3 | GNB3 | GNB3 | 6199 | 0.077 | 0.45 | NO
25 | GNAS | GNAS | GNAS | 6234 | 0.076 | 0.46 | NO
26 | TAS2R46 | TAS2R46 | TAS2R46 | 7627 | 0.047 | 0.39 | NO
27 | GNB1 | GNB1 | GNB1 | 8785 | 0.028 | 0.33 | NO
28 | TAS1R3 | TAS1R3 | TAS1R3 | 9541 | 0.017 | 0.29 | NO
29 | PRKACB | PRKACB | PRKACB | 12733 | -0.033 | 0.12 | NO
30 | PRKX | PRKX | PRKX | 14053 | -0.058 | 0.058 | NO
31 | PRKACA | PRKACA | PRKACA | 16390 | -0.13 | -0.053 | NO
32 | ADCY4 | ADCY4 | ADCY4 | 16429 | -0.13 | -0.041 | NO
33 | TAS2R42 | TAS2R42 | TAS2R42 | 16995 | -0.16 | -0.054 | NO
34 | KCNB1 | KCNB1 | KCNB1 | 17211 | -0.18 | -0.045 | NO
35 | TAS1R1 | TAS1R1 | TAS1R1 | 17375 | -0.2 | -0.032 | NO
36 | GNG13 | GNG13 | GNG13 | 18193 | -0.32 | -0.042 | NO
37 | CACNA1A | CACNA1A | CACNA1A | 18628 | -0.6 | 0.00097 | 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: KEGG METABOLISM OF XENOBIOTICS BY CYTOCHROME P450.

Figure S56. Get High-res Image For the top 5 core enriched genes in the pathway: KEGG METABOLISM OF XENOBIOTICS BY CYTOCHROME P450, 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 DRUG METABOLISM CYTOCHROME P450

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 | DDC | DDC | DDC | 218 | 0.55 | 0.09 | YES
2 | HGD | HGD | HGD | 467 | 0.44 | 0.16 | YES
3 | ADH1B | ADH1B | ADH1B | 643 | 0.4 | 0.23 | YES
4 | ADH6 | ADH6 | ADH6 | 912 | 0.36 | 0.28 | YES
5 | ADH1C | ADH1C | ADH1C | 1246 | 0.32 | 0.32 | YES
6 | PNMT | PNMT | PNMT | 1670 | 0.27 | 0.35 | YES
7 | DBH | DBH | DBH | 1706 | 0.27 | 0.4 | YES
8 | TH | TH | TH | 1794 | 0.26 | 0.44 | YES
9 | ADH1A | ADH1A | ADH1A | 1848 | 0.26 | 0.49 | YES
10 | TPO | TPO | TPO | 2687 | 0.2 | 0.48 | YES
11 | MAOB | MAOB | MAOB | 2854 | 0.19 | 0.5 | YES
12 | MAOA | MAOA | MAOA | 4185 | 0.13 | 0.46 | NO
13 | IL4I1 | IL4I1 | IL4I1 | 5099 | 0.1 | 0.43 | NO
14 | FAH | FAH | FAH | 5486 | 0.093 | 0.42 | NO
15 | ALDH3B2 | ALDH3B2 | ALDH3B2 | 5798 | 0.086 | 0.42 | NO
16 | HEMK1 | HEMK1 | HEMK1 | 5922 | 0.083 | 0.43 | NO
17 | NAT6 | NAT6 | NAT6 | 6024 | 0.08 | 0.44 | NO
18 | AOC2 | AOC2 | AOC2 | 6113 | 0.078 | 0.45 | NO
19 | LCMT1 | LCMT1 | LCMT1 | 6732 | 0.064 | 0.43 | NO
20 | GOT2 | GOT2 | GOT2 | 6806 | 0.062 | 0.44 | NO
21 | ADH4 | ADH4 | ADH4 | 7264 | 0.053 | 0.42 | NO
22 | DCT | DCT | DCT | 8371 | 0.035 | 0.37 | NO
23 | ALDH3A1 | ALDH3A1 | ALDH3A1 | 9056 | 0.024 | 0.34 | NO
24 | WBSCR22 | WBSCR22 | WBSCR22 | 10358 | 0.005 | 0.27 | NO
25 | TRMT11 | TRMT11 | TRMT11 | 11339 | -0.01 | 0.22 | NO
26 | ADH5 | ADH5 | ADH5 | 11948 | -0.02 | 0.19 | NO
27 | COMT | COMT | COMT | 12158 | -0.023 | 0.18 | NO
28 | GOT1 | GOT1 | GOT1 | 12232 | -0.024 | 0.18 | NO
29 | ALDH3B1 | ALDH3B1 | ALDH3B1 | 12634 | -0.031 | 0.17 | NO
30 | MIF | MIF | MIF | 12813 | -0.034 | 0.17 | NO
31 | METTL6 | METTL6 | METTL6 | 13050 | -0.038 | 0.16 | NO
32 | METTL2B | METTL2B | METTL2B | 13350 | -0.044 | 0.15 | NO
33 | TAT | TAT | TAT | 14629 | -0.071 | 0.097 | NO
34 | GSTZ1 | GSTZ1 | GSTZ1 | 14800 | -0.075 | 0.1 | NO
35 | LCMT2 | LCMT2 | LCMT2 | 14824 | -0.075 | 0.12 | NO
36 | AOC3 | AOC3 | AOC3 | 15457 | -0.093 | 0.098 | NO
37 | HPD | HPD | HPD | 15556 | -0.096 | 0.11 | NO
38 | ALDH1A3 | ALDH1A3 | ALDH1A3 | 16697 | -0.14 | 0.077 | NO
39 | AOX1 | AOX1 | AOX1 | 16766 | -0.15 | 0.1 | 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 DRUG METABOLISM CYTOCHROME P450.

Figure S58. Get High-res Image For the top 5 core enriched genes in the pathway: KEGG DRUG METABOLISM CYTOCHROME P450, 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 DRUG METABOLISM OTHER ENZYMES

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 | UGT2B10 | UGT2B10 | UGT2B10 | 74 | 0.69 | 0.092 | YES
2 | UGT2A3 | UGT2A3 | UGT2A3 | 75 | 0.69 | 0.19 | YES
3 | UGT2B15 | UGT2B15 | UGT2B15 | 245 | 0.53 | 0.25 | YES
4 | UGT2B7 | UGT2B7 | UGT2B7 | 367 | 0.48 | 0.31 | YES
5 | CES7 | CES7 | CES7 | 612 | 0.41 | 0.36 | YES
6 | UGT2B11 | UGT2B11 | UGT2B11 | 678 | 0.4 | 0.41 | YES
7 | CYP3A5 | CYP3A5 | CYP3A5 | 832 | 0.37 | 0.45 | YES
8 | UGT1A6 | UGT1A6 | UGT1A6 | 1158 | 0.33 | 0.48 | YES
9 | CES1 | CES1 | CES1 | 1250 | 0.32 | 0.52 | YES
10 | DPYD | DPYD | DPYD | 1534 | 0.29 | 0.55 | YES
11 | CYP3A7 | CYP3A7 | CYP3A7 | 2445 | 0.21 | 0.53 | NO
12 | UGT1A1 | UGT1A1 | UGT1A1 | 3717 | 0.15 | 0.48 | NO
13 | CYP2A13 | CYP2A13 | CYP2A13 | 4212 | 0.13 | 0.47 | NO
14 | CDA | CDA | CDA | 4395 | 0.12 | 0.48 | NO
15 | UGT1A9 | UGT1A9 | UGT1A9 | 4541 | 0.12 | 0.49 | NO
16 | TK2 | TK2 | TK2 | 4889 | 0.11 | 0.48 | NO
17 | UCKL1 | UCKL1 | UCKL1 | 5277 | 0.098 | 0.48 | NO
18 | CYP3A43 | CYP3A43 | CYP3A43 | 5409 | 0.095 | 0.48 | NO
19 | CES2 | CES2 | CES2 | 6282 | 0.074 | 0.45 | NO
20 | UPP1 | UPP1 | UPP1 | 7507 | 0.049 | 0.39 | NO
21 | UGT2B4 | UGT2B4 | UGT2B4 | 8093 | 0.039 | 0.36 | NO
22 | NAT2 | NAT2 | NAT2 | 8355 | 0.035 | 0.35 | NO
23 | ITPA | ITPA | ITPA | 8616 | 0.031 | 0.34 | NO
24 | UPB1 | UPB1 | UPB1 | 8676 | 0.03 | 0.34 | NO
25 | TK1 | TK1 | TK1 | 9306 | 0.02 | 0.31 | NO
26 | TPMT | TPMT | TPMT | 10748 | -0.0011 | 0.24 | NO
27 | UPP2 | UPP2 | UPP2 | 12737 | -0.033 | 0.13 | NO
28 | GUSB | GUSB | GUSB | 13061 | -0.038 | 0.12 | NO
29 | UCK1 | UCK1 | UCK1 | 13118 | -0.04 | 0.12 | NO
30 | NAT1 | NAT1 | NAT1 | 13801 | -0.053 | 0.095 | NO
31 | UMPS | UMPS | UMPS | 14070 | -0.059 | 0.089 | NO
32 | UCK2 | UCK2 | UCK2 | 14355 | -0.065 | 0.083 | NO
33 | IMPDH2 | IMPDH2 | IMPDH2 | 14715 | -0.073 | 0.074 | NO
34 | IMPDH1 | IMPDH1 | IMPDH1 | 15256 | -0.087 | 0.057 | NO
35 | CYP2A6 | CYP2A6 | CYP2A6 | 15304 | -0.088 | 0.067 | NO
36 | TYMP | TYMP | TYMP | 15536 | -0.096 | 0.068 | NO
37 | HPRT1 | HPRT1 | HPRT1 | 16026 | -0.11 | 0.058 | NO
38 | XDH | XDH | XDH | 16204 | -0.12 | 0.065 | NO
39 | GMPS | GMPS | GMPS | 16615 | -0.14 | 0.062 | NO
40 | DPYS | DPYS | DPYS | 16702 | -0.15 | 0.078 | NO
41 | UGT2A1 | UGT2A1 | UGT2A1 | 17251 | -0.19 | 0.075 | 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 DRUG METABOLISM OTHER ENZYMES.

Figure S60. Get High-res Image For the top 5 core enriched genes in the pathway: KEGG DRUG METABOLISM OTHER ENZYMES, 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

- up-regulated, please check the list of up-regulated genes

- down-regulated, please check the list of down-regulated genes

Expression level

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

- highly expressed genes, please check the list of high (top 30%) expressed genes

- low expressed genes, please check the list of low (bottom 30%) expressed genes

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

- significantly differently expressed genes by eBayes lm fit, please check the list of significant genes

Subtype clus4 enriched pathways

Table 6. Get Full Table This table shows top 10 pathways which are significantly enriched in cluster clus4. 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 ALK PATHWAY | 35 | genes.ES.table | 0.24 | 0.69 | 0.89 | 0.88 | 1 | 0.14 | 0.091 | 0.13 | 0.89 | 0.072
BIOCARTA G1 PATHWAY | 27 | genes.ES.table | 0.18 | 0.58 | 0.95 | 0.94 | 1 | 0.44 | 0.28 | 0.32 | 0.95 | 0.032
KEGG CITRATE CYCLE TCA CYCLE | 29 | genes.ES.table | 0.28 | 0.97 | 0.48 | 0.59 | 1 | 1 | 0.72 | 0.28 | 0.57 | 0.038
KEGG PYRIMIDINE METABOLISM | 97 | genes.ES.table | 0.27 | 1.2 | 0.2 | 0.33 | 0.99 | 0.29 | 0.21 | 0.23 | 0.28 | 0.014
KEGG LYSINE DEGRADATION | 43 | genes.ES.table | 0.27 | 1.3 | 0.17 | 0.34 | 0.98 | 0.21 | 0.16 | 0.18 | 0.28 | 0.021
KEGG AMINOACYL TRNA BIOSYNTHESIS | 40 | genes.ES.table | 0.24 | 0.88 | 0.54 | 0.7 | 1 | 0.48 | 0.31 | 0.33 | 0.7 | 0.064
KEGG RNA DEGRADATION | 56 | genes.ES.table | 0.35 | 1.7 | 0.059 | 0.12 | 0.57 | 0.29 | 0.22 | 0.22 | 0.057 | 0.012
KEGG RNA POLYMERASE | 28 | genes.ES.table | 0.43 | 1.4 | 0.17 | 0.27 | 0.94 | 0.61 | 0.34 | 0.4 | 0.2 | 0.018
KEGG BASAL TRANSCRIPTION FACTORS | 34 | genes.ES.table | 0.54 | 1.8 | 0.011 | 0.17 | 0.34 | 0.65 | 0.32 | 0.44 | 0 | 0.032
KEGG DNA REPLICATION | 35 | genes.ES.table | 0.51 | 1.5 | 0.1 | 0.22 | 0.8 | 0.6 | 0.29 | 0.43 | 0.14 | 0.024

genes ES table in pathway: BIOCARTA ALK PATHWAY

Table S31. 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 | TAF7L | TAF7L | TAF7L | 1129 | 0.18 | 0.042 | YES
2 | TAF12 | TAF12 | TAF12 | 1350 | 0.16 | 0.12 | YES
3 | TAF5 | TAF5 | TAF5 | 1900 | 0.13 | 0.16 | YES
4 | TAF9B | TAF9B | TAF9B | 2165 | 0.11 | 0.21 | YES
5 | TBPL1 | TBPL1 | TBPL1 | 2566 | 0.096 | 0.25 | YES
6 | TAF6 | TAF6 | TAF6 | 3166 | 0.077 | 0.26 | YES
7 | TBP | TBP | TBP | 3176 | 0.077 | 0.3 | YES
8 | GTF2H1 | GTF2H1 | GTF2H1 | 3348 | 0.073 | 0.33 | YES
9 | STON1 | STON1 | STON1 | 3397 | 0.072 | 0.37 | YES
10 | GTF2A2 | GTF2A2 | GTF2A2 | 3505 | 0.069 | 0.4 | YES
11 | TAF2 | TAF2 | TAF2 | 4175 | 0.055 | 0.4 | YES
12 | GTF2H4 | GTF2H4 | GTF2H4 | 4445 | 0.05 | 0.41 | YES
13 | TAF6L | TAF6L | TAF6L | 4491 | 0.049 | 0.44 | YES
14 | GTF2A1 | GTF2A1 | GTF2A1 | 4567 | 0.048 | 0.46 | YES
15 | GTF2H3 | GTF2H3 | GTF2H3 | 4570 | 0.048 | 0.49 | YES
16 | GTF2E2 | GTF2E2 | GTF2E2 | 5117 | 0.039 | 0.48 | YES
17 | GTF2H2 | GTF2H2 | GTF2H2 | 5236 | 0.037 | 0.5 | YES
18 | TAF4B | TAF4B | TAF4B | 5427 | 0.034 | 0.5 | YES
19 | TAF10 | TAF10 | TAF10 | 5658 | 0.03 | 0.51 | YES
20 | TAF5L | TAF5L | TAF5L | 5824 | 0.027 | 0.52 | YES
21 | TAF11 | TAF11 | TAF11 | 5862 | 0.027 | 0.53 | YES
22 | TAF4 | TAF4 | TAF4 | 5990 | 0.025 | 0.54 | YES
23 | TAF1L | TAF1L | TAF1L | 6406 | 0.019 | 0.52 | NO
24 | TAF1 | TAF1 | TAF1 | 7079 | 0.01 | 0.5 | NO
25 | GTF2F1 | GTF2F1 | GTF2F1 | 7158 | 0.009 | 0.5 | NO
26 | TAF7 | TAF7 | TAF7 | 7368 | 0.0064 | 0.49 | NO
27 | GTF2E1 | GTF2E1 | GTF2E1 | 7830 | 0.00027 | 0.46 | NO
28 | TAF9 | TAF9 | TAF9 | 7900 | -0.00072 | 0.46 | NO
29 | GTF2B | GTF2B | GTF2B | 9351 | -0.021 | 0.39 | NO
30 | GTF2IRD1 | GTF2IRD1 | GTF2IRD1 | 9507 | -0.022 | 0.4 | NO
31 | GTF2F2 | GTF2F2 | GTF2F2 | 9672 | -0.025 | 0.4 | NO
32 | GTF2I | GTF2I | GTF2I | 10375 | -0.036 | 0.39 | NO
33 | TAF13 | TAF13 | TAF13 | 10734 | -0.042 | 0.39 | NO
34 | GTF2A1L | GTF2A1L | GTF2A1L | 11633 | -0.06 | 0.38 | NO

Figure S61. 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 S62. 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 G1 PATHWAY

Table S32. 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 | CDKN2C | CDKN2C | CDKN2C | 65 | 0.48 | 0.046 | YES
2 | CCNB3 | CCNB3 | CCNB3 | 458 | 0.28 | 0.054 | YES
3 | CCNE2 | CCNE2 | CCNE2 | 470 | 0.28 | 0.082 | YES
4 | CDC45 | CDC45 | CDC45 | 976 | 0.2 | 0.075 | YES
5 | CCNA2 | CCNA2 | CCNA2 | 1120 | 0.18 | 0.086 | YES
6 | ANAPC10 | ANAPC10 | ANAPC10 | 1300 | 0.16 | 0.094 | YES
7 | TGFB1 | TGFB1 | TGFB1 | 1341 | 0.16 | 0.11 | YES
8 | SMC1A | SMC1A | SMC1A | 1490 | 0.15 | 0.12 | YES
9 | ORC6L | ORC6L | ORC6L | 1652 | 0.14 | 0.12 | YES
10 | TGFB3 | TGFB3 | TGFB3 | 1674 | 0.14 | 0.14 | YES
11 | CDC20 | CDC20 | CDC20 | 1701 | 0.14 | 0.15 | YES
12 | MAD2L1 | MAD2L1 | MAD2L1 | 1712 | 0.14 | 0.16 | YES
13 | CDKN1B | CDKN1B | CDKN1B | 1895 | 0.13 | 0.16 | YES
14 | PLK1 | PLK1 | PLK1 | 1925 | 0.12 | 0.18 | YES
15 | CCNB2 | CCNB2 | CCNB2 | 1956 | 0.12 | 0.19 | YES
16 | CDC6 | CDC6 | CDC6 | 2155 | 0.11 | 0.19 | YES
17 | MAD2L2 | MAD2L2 | MAD2L2 | 2180 | 0.11 | 0.2 | YES
18 | RBL1 | RBL1 | RBL1 | 2243 | 0.11 | 0.21 | YES
19 | TTK | TTK | TTK | 2407 | 0.1 | 0.21 | YES
20 | CDK2 | CDK2 | CDK2 | 2417 | 0.1 | 0.22 | YES
21 | BUB1 | BUB1 | BUB1 | 2462 | 0.1 | 0.23 | YES
22 | SMC3 | SMC3 | SMC3 | 2558 | 0.097 | 0.23 | YES
23 | CDKN2D | CDKN2D | CDKN2D | 2571 | 0.096 | 0.24 | YES
24 | BUB3 | BUB3 | BUB3 | 2599 | 0.095 | 0.25 | YES
25 | SMC1B | SMC1B | SMC1B | 2625 | 0.094 | 0.26 | YES
26 | PCNA | PCNA | PCNA | 2627 | 0.094 | 0.27 | YES
27 | CDC25C | CDC25C | CDC25C | 2678 | 0.092 | 0.28 | YES
28 | TP53 | TP53 | TP53 | 2679 | 0.092 | 0.28 | YES
29 | ESPL1 | ESPL1 | ESPL1 | 2684 | 0.092 | 0.29 | YES
30 | CCNB1 | CCNB1 | CCNB1 | 2765 | 0.09 | 0.3 | YES
31 | FZR1 | FZR1 | FZR1 | 2954 | 0.084 | 0.3 | YES
32 | CDC25B | CDC25B | CDC25B | 3015 | 0.082 | 0.3 | YES
33 | GADD45B | GADD45B | GADD45B | 3037 | 0.081 | 0.31 | YES
34 | PTTG1 | PTTG1 | PTTG1 | 3056 | 0.08 | 0.32 | YES
35 | RAD21 | RAD21 | RAD21 | 3182 | 0.077 | 0.32 | YES
36 | CDC26 | CDC26 | CDC26 | 3241 | 0.076 | 0.32 | YES
37 | MCM6 | MCM6 | MCM6 | 3408 | 0.072 | 0.32 | YES
38 | E2F1 | E2F1 | E2F1 | 3417 | 0.071 | 0.33 | YES
39 | CDKN2A | CDKN2A | CDKN2A | 3506 | 0.069 | 0.33 | YES
40 | BUB1B | BUB1B | BUB1B | 3511 | 0.069 | 0.34 | YES
41 | ORC1L | ORC1L | ORC1L | 3682 | 0.065 | 0.34 | YES
42 | HDAC2 | HDAC2 | HDAC2 | 3707 | 0.064 | 0.34 | YES
43 | MAD1L1 | MAD1L1 | MAD1L1 | 3960 | 0.059 | 0.33 | YES
44 | ANAPC2 | ANAPC2 | ANAPC2 | 3970 | 0.059 | 0.34 | YES
45 | TFDP1 | TFDP1 | TFDP1 | 4036 | 0.057 | 0.34 | YES
46 | CDK4 | CDK4 | CDK4 | 4159 | 0.055 | 0.34 | YES
47 | E2F4 | E2F4 | E2F4 | 4220 | 0.054 | 0.34 | YES
48 | CHEK2 | CHEK2 | CHEK2 | 4236 | 0.053 | 0.35 | YES
49 | CDC7 | CDC7 | CDC7 | 4256 | 0.053 | 0.35 | YES
50 | SMAD2 | SMAD2 | SMAD2 | 4498 | 0.049 | 0.34 | YES
51 | STAG2 | STAG2 | STAG2 | 4520 | 0.049 | 0.35 | YES
52 | MDM2 | MDM2 | MDM2 | 4554 | 0.048 | 0.35 | YES
53 | ABL1 | ABL1 | ABL1 | 4573 | 0.048 | 0.36 | YES
54 | GADD45A | GADD45A | GADD45A | 4623 | 0.047 | 0.36 | YES
55 | WEE2 | WEE2 | WEE2 | 4641 | 0.047 | 0.36 | YES
56 | CDK1 | CDK1 | CDK1 | 4757 | 0.045 | 0.36 | NO
57 | E2F3 | E2F3 | E2F3 | 4980 | 0.041 | 0.35 | NO
58 | MCM5 | MCM5 | MCM5 | 5062 | 0.04 | 0.35 | NO
59 | STAG1 | STAG1 | STAG1 | 5257 | 0.036 | 0.34 | NO
60 | TGFB2 | TGFB2 | TGFB2 | 5279 | 0.036 | 0.35 | NO
61 | CDC27 | CDC27 | CDC27 | 5335 | 0.035 | 0.35 | NO
62 | ZBTB17 | ZBTB17 | ZBTB17 | 5392 | 0.034 | 0.35 | NO
63 | MCM3 | MCM3 | MCM3 | 5411 | 0.034 | 0.35 | NO
64 | ANAPC7 | ANAPC7 | ANAPC7 | 5416 | 0.034 | 0.36 | NO
65 | YWHAH | YWHAH | YWHAH | 5454 | 0.033 | 0.36 | NO
66 | PTTG2 | PTTG2 | PTTG2 | 5549 | 0.032 | 0.35 | NO
67 | YWHAG | YWHAG | YWHAG | 5747 | 0.028 | 0.35 | NO
68 | ORC5L | ORC5L | ORC5L | 5797 | 0.028 | 0.35 | NO
69 | CDC25A | CDC25A | CDC25A | 5910 | 0.026 | 0.34 | NO
70 | SMAD4 | SMAD4 | SMAD4 | 6127 | 0.023 | 0.33 | NO
71 | PRKDC | PRKDC | PRKDC | 6290 | 0.021 | 0.33 | NO
72 | YWHAB | YWHAB | YWHAB | 6462 | 0.018 | 0.32 | NO
73 | MCM7 | MCM7 | MCM7 | 6477 | 0.018 | 0.32 | NO
74 | CREBBP | CREBBP | CREBBP | 6557 | 0.017 | 0.32 | NO
75 | RBX1 | RBX1 | RBX1 | 6704 | 0.015 | 0.31 | NO
76 | CCNH | CCNH | CCNH | 6765 | 0.014 | 0.31 | NO
77 | CDC16 | CDC16 | CDC16 | 6836 | 0.013 | 0.31 | NO
78 | ANAPC5 | ANAPC5 | ANAPC5 | 6851 | 0.013 | 0.31 | NO
79 | ANAPC4 | ANAPC4 | ANAPC4 | 7050 | 0.01 | 0.3 | NO
80 | YWHAE | YWHAE | YWHAE | 7073 | 0.01 | 0.3 | NO
81 | ATR | ATR | ATR | 7541 | 0.0041 | 0.27 | NO
82 | CUL1 | CUL1 | CUL1 | 7660 | 0.0024 | 0.27 | NO
83 | SMAD3 | SMAD3 | SMAD3 | 7766 | 0.0011 | 0.26 | NO
84 | ORC3L | ORC3L | ORC3L | 7862 | -0.00022 | 0.26 | NO
85 | ANAPC13 | ANAPC13 | ANAPC13 | 7890 | -0.00052 | 0.26 | NO
86 | CDC23 | CDC23 | CDC23 | 8177 | -0.0046 | 0.24 | NO
87 | PKMYT1 | PKMYT1 | PKMYT1 | 8331 | -0.0066 | 0.23 | NO
88 | RBL2 | RBL2 | RBL2 | 8385 | -0.0074 | 0.23 | NO
89 | MCM4 | MCM4 | MCM4 | 8629 | -0.011 | 0.22 | NO
90 | SKP2 | SKP2 | SKP2 | 8741 | -0.012 | 0.22 | NO
91 | SKP1 | SKP1 | SKP1 | 8800 | -0.013 | 0.21 | NO
92 | GSK3B | GSK3B | GSK3B | 8865 | -0.014 | 0.21 | NO
93 | CDC14B | CDC14B | CDC14B | 8977 | -0.015 | 0.21 | NO
94 | ORC2L | ORC2L | ORC2L | 9325 | -0.02 | 0.19 | NO
95 | MCM2 | MCM2 | MCM2 | 9400 | -0.021 | 0.19 | NO
96 | CCNE1 | CCNE1 | CCNE1 | 9436 | -0.022 | 0.19 | NO
97 | E2F2 | E2F2 | E2F2 | 9462 | -0.022 | 0.19 | NO
98 | HDAC1 | HDAC1 | HDAC1 | 9638 | -0.024 | 0.18 | NO
99 | EP300 | EP300 | EP300 | 9966 | -0.029 | 0.17 | NO
100 | ANAPC11 | ANAPC11 | ANAPC11 | 10134 | -0.032 | 0.16 | NO
101 | SFN | SFN | SFN | 10352 | -0.035 | 0.15 | NO
102 | CCND3 | CCND3 | CCND3 | 10524 | -0.038 | 0.15 | NO
103 | ANAPC1 | ANAPC1 | ANAPC1 | 10769 | -0.043 | 0.14 | NO
104 | YWHAQ | YWHAQ | YWHAQ | 10799 | -0.044 | 0.14 | NO
105 | YWHAZ | YWHAZ | YWHAZ | 10872 | -0.045 | 0.14 | NO
106 | CHEK1 | CHEK1 | CHEK1 | 11466 | -0.057 | 0.12 | NO
107 | CDKN2B | CDKN2B | CDKN2B | 11475 | -0.057 | 0.12 | NO
108 | TFDP2 | TFDP2 | TFDP2 | 11626 | -0.06 | 0.12 | NO
109 | WEE1 | WEE1 | WEE1 | 12669 | -0.086 | 0.074 | NO
110 | CDK6 | CDK6 | CDK6 | 12775 | -0.089 | 0.078 | NO
111 | CDKN1A | CDKN1A | CDKN1A | 12817 | -0.091 | 0.085 | NO
112 | CDK7 | CDK7 | CDK7 | 12853 | -0.091 | 0.092 | NO
113 | ORC4L | ORC4L | ORC4L | 13108 | -0.099 | 0.089 | NO
114 | ATM | ATM | ATM | 13769 | -0.12 | 0.066 | NO
115 | MYC | MYC | MYC | 13843 | -0.12 | 0.075 | NO
116 | CDKN1C | CDKN1C | CDKN1C | 14388 | -0.15 | 0.061 | NO
117 | RB1 | RB1 | RB1 | 14800 | -0.17 | 0.056 | NO
118 | E2F5 | E2F5 | E2F5 | 15580 | -0.21 | 0.035 | NO
119 | CDC14A | CDC14A | CDC14A | 15599 | -0.21 | 0.056 | NO
120 | CCNA1 | CCNA1 | CCNA1 | 15955 | -0.23 | 0.061 | NO
121 | CCND2 | CCND2 | CCND2 | 16210 | -0.25 | 0.073 | NO
122 | CCND1 | CCND1 | CCND1 | 16421 | -0.26 | 0.089 | NO
123 | GADD45G | GADD45G | GADD45G | 16884 | -0.3 | 0.095 | NO

Figure S63. 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 S64. 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: KEGG CITRATE CYCLE TCA CYCLE

Table S33. 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 | ENO2 | ENO2 | ENO2 | 644 | 0.24 | 0.048 | YES
2 | PAPOLB | PAPOLB | PAPOLB | 1150 | 0.18 | 0.082 | YES
3 | LSM6 | LSM6 | LSM6 | 1503 | 0.15 | 0.11 | YES
4 | EXOSC9 | EXOSC9 | EXOSC9 | 1939 | 0.12 | 0.13 | YES
5 | EXOSC6 | EXOSC6 | EXOSC6 | 1983 | 0.12 | 0.17 | YES
6 | ZCCHC7 | ZCCHC7 | ZCCHC7 | 2393 | 0.1 | 0.18 | YES
7 | EXOSC3 | EXOSC3 | EXOSC3 | 2481 | 0.1 | 0.21 | YES
8 | PAPD7 | PAPD7 | PAPD7 | 2630 | 0.094 | 0.24 | YES
9 | CNOT10 | CNOT10 | CNOT10 | 2790 | 0.089 | 0.26 | YES
10 | LSM7 | LSM7 | LSM7 | 2986 | 0.082 | 0.28 | YES
11 | EXOSC10 | EXOSC10 | EXOSC10 | 3044 | 0.081 | 0.3 | YES
12 | EXOSC2 | EXOSC2 | EXOSC2 | 3271 | 0.075 | 0.31 | YES
13 | ENO1 | ENO1 | ENO1 | 3385 | 0.072 | 0.33 | YES
14 | PATL1 | PATL1 | PATL1 | 3761 | 0.063 | 0.33 | YES
15 | LSM2 | LSM2 | LSM2 | 3992 | 0.058 | 0.34 | YES
16 | LSM1 | LSM1 | LSM1 | 4054 | 0.057 | 0.36 | YES
17 | LSM3 | LSM3 | LSM3 | 4589 | 0.048 | 0.34 | NO
18 | RQCD1 | RQCD1 | RQCD1 | 5035 | 0.04 | 0.33 | NO
19 | EXOSC1 | EXOSC1 | EXOSC1 | 5261 | 0.036 | 0.33 | NO
20 | XRN2 | XRN2 | XRN2 | 5332 | 0.035 | 0.34 | NO
21 | LSM5 | LSM5 | LSM5 | 5340 | 0.035 | 0.35 | NO
22 | PAPOLA | PAPOLA | PAPOLA | 5572 | 0.031 | 0.35 | NO
23 | CNOT2 | CNOT2 | CNOT2 | 6259 | 0.021 | 0.32 | NO
24 | HSPA9 | HSPA9 | HSPA9 | 6294 | 0.021 | 0.32 | NO
25 | PNPT1 | PNPT1 | PNPT1 | 6368 | 0.02 | 0.33 | NO
26 | PARN | PARN | PARN | 6520 | 0.018 | 0.33 | NO
27 | C1D | C1D | C1D | 6565 | 0.017 | 0.33 | NO
28 | MPHOSPH6 | MPHOSPH6 | MPHOSPH6 | 6901 | 0.012 | 0.32 | NO
29 | EDC3 | EDC3 | EDC3 | 6905 | 0.012 | 0.32 | NO
30 | CNOT1 | CNOT1 | CNOT1 | 7000 | 0.011 | 0.32 | NO
31 | XRN1 | XRN1 | XRN1 | 7020 | 0.011 | 0.32 | NO
32 | EDC4 | EDC4 | EDC4 | 7023 | 0.011 | 0.32 | NO
33 | EXOSC5 | EXOSC5 | EXOSC5 | 7078 | 0.01 | 0.32 | NO
34 | DCP1B | DCP1B | DCP1B | 7117 | 0.0095 | 0.32 | NO
35 | CNOT6 | CNOT6 | CNOT6 | 7232 | 0.0082 | 0.32 | NO
36 | DCP1A | DCP1A | DCP1A | 7357 | 0.0065 | 0.32 | NO
37 | EXOSC7 | EXOSC7 | EXOSC7 | 7659 | 0.0024 | 0.3 | NO
38 | PAPOLG | PAPOLG | PAPOLG | 7776 | 0.00093 | 0.3 | NO
39 | SKIV2L2 | SKIV2L2 | SKIV2L2 | 7928 | -0.0011 | 0.29 | NO
40 | EXOSC4 | EXOSC4 | EXOSC4 | 8008 | -0.0023 | 0.28 | NO
41 | HSPD1 | HSPD1 | HSPD1 | 8954 | -0.015 | 0.24 | NO
42 | DDX6 | DDX6 | DDX6 | 8958 | -0.015 | 0.24 | NO
43 | SKIV2L | SKIV2L | SKIV2L | 9019 | -0.016 | 0.25 | NO
44 | DCP2 | DCP2 | DCP2 | 9057 | -0.016 | 0.25 | NO
45 | NAA38 | NAA38 | NAA38 | 9065 | -0.016 | 0.26 | NO
46 | DCPS | DCPS | DCPS | 9550 | -0.023 | 0.24 | NO
47 | TTC37 | TTC37 | TTC37 | 10117 | -0.031 | 0.22 | NO
48 | CNOT3 | CNOT3 | CNOT3 | 10171 | -0.032 | 0.22 | NO
49 | WDR61 | WDR61 | WDR61 | 10586 | -0.039 | 0.22 | NO
50 | CNOT7 | CNOT7 | CNOT7 | 10603 | -0.04 | 0.23 | NO
51 | CNOT4 | CNOT4 | CNOT4 | 10661 | -0.041 | 0.24 | NO
52 | DIS3 | DIS3 | DIS3 | 10952 | -0.046 | 0.24 | NO
53 | LSM4 | LSM4 | LSM4 | 11718 | -0.062 | 0.22 | NO
54 | CNOT6L | CNOT6L | CNOT6L | 12568 | -0.083 | 0.2 | NO
55 | EXOSC8 | EXOSC8 | EXOSC8 | 12831 | -0.091 | 0.22 | NO
56 | ENO3 | ENO3 | ENO3 | 16657 | -0.28 | 0.11 | NO

Figure S65. 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 CITRATE CYCLE TCA CYCLE.

Figure S66. Get High-res Image For the top 5 core enriched genes in the pathway: KEGG CITRATE CYCLE TCA CYCLE, 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 S34. 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 | PRIM1 | PRIM1 | PRIM1 | 479 | 0.28 | 0.1 | YES
2 | RPA4 | RPA4 | RPA4 | 666 | 0.24 | 0.2 | YES
3 | POLE2 | POLE2 | POLE2 | 1091 | 0.18 | 0.26 | YES
4 | PCNA | PCNA | PCNA | 2627 | 0.094 | 0.23 | YES
5 | FEN1 | FEN1 | FEN1 | 2781 | 0.089 | 0.26 | YES
6 | PRIM2 | PRIM2 | PRIM2 | 2957 | 0.084 | 0.29 | YES
7 | RPA3 | RPA3 | RPA3 | 3032 | 0.081 | 0.32 | YES
8 | MCM6 | MCM6 | MCM6 | 3408 | 0.072 | 0.34 | YES
9 | POLE | POLE | POLE | 3545 | 0.068 | 0.36 | YES
10 | RPA2 | RPA2 | RPA2 | 3583 | 0.067 | 0.39 | YES
11 | RFC2 | RFC2 | RFC2 | 3857 | 0.061 | 0.4 | YES
12 | RNASEH2C | RNASEH2C | RNASEH2C | 4308 | 0.052 | 0.4 | YES
13 | RFC1 | RFC1 | RFC1 | 4371 | 0.051 | 0.42 | YES
14 | RNASEH2B | RNASEH2B | RNASEH2B | 4606 | 0.047 | 0.43 | YES
15 | RFC4 | RFC4 | RFC4 | 4607 | 0.047 | 0.45 | YES
16 | MCM5 | MCM5 | MCM5 | 5062 | 0.04 | 0.45 | YES
17 | RNASEH2A | RNASEH2A | RNASEH2A | 5071 | 0.039 | 0.46 | YES
18 | RFC5 | RFC5 | RFC5 | 5113 | 0.039 | 0.48 | YES
19 | SSBP1 | SSBP1 | SSBP1 | 5182 | 0.038 | 0.49 | YES
20 | POLD1 | POLD1 | POLD1 | 5328 | 0.035 | 0.5 | YES
21 | MCM3 | MCM3 | MCM3 | 5411 | 0.034 | 0.51 | YES
22 | POLA2 | POLA2 | POLA2 | 6250 | 0.021 | 0.48 | NO
23 | MCM7 | MCM7 | MCM7 | 6477 | 0.018 | 0.48 | NO
24 | RPA1 | RPA1 | RPA1 | 6589 | 0.017 | 0.48 | NO
25 | POLD2 | POLD2 | POLD2 | 8307 | -0.0063 | 0.39 | NO
26 | DNA2 | DNA2 | DNA2 | 8475 | -0.0088 | 0.38 | NO
27 | POLE3 | POLE3 | POLE3 | 8556 | -0.01 | 0.38 | NO
28 | MCM4 | MCM4 | MCM4 | 8629 | -0.011 | 0.38 | NO
29 | POLD3 | POLD3 | POLD3 | 8866 | -0.014 | 0.38 | NO
30 | MCM2 | MCM2 | MCM2 | 9400 | -0.021 | 0.36 | NO
31 | LIG1 | LIG1 | LIG1 | 9768 | -0.026 | 0.35 | NO
32 | RNASEH1 | RNASEH1 | RNASEH1 | 10329 | -0.035 | 0.34 | NO
33 | POLE4 | POLE4 | POLE4 | 11484 | -0.057 | 0.3 | NO
34 | RFC3 | RFC3 | RFC3 | 12200 | -0.074 | 0.3 | NO
35 | POLD4 | POLD4 | POLD4 | 13290 | -0.1 | 0.29 | NO

Figure S67. 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 S68. 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 LYSINE DEGRADATION

Table S35. 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 | RPA4 | RPA4 | RPA4 | 666 | 0.24 | 0.063 | YES
2 | POLE2 | POLE2 | POLE2 | 1091 | 0.18 | 0.12 | YES
3 | DDB2 | DDB2 | DDB2 | 1538 | 0.15 | 0.15 | YES
4 | PCNA | PCNA | PCNA | 2627 | 0.094 | 0.13 | YES
5 | RPA3 | RPA3 | RPA3 | 3032 | 0.081 | 0.14 | YES
6 | GTF2H1 | GTF2H1 | GTF2H1 | 3348 | 0.073 | 0.16 | YES
7 | POLE | POLE | POLE | 3545 | 0.068 | 0.17 | YES
8 | XPA | XPA | XPA | 3547 | 0.068 | 0.2 | YES
9 | RPA2 | RPA2 | RPA2 | 3583 | 0.067 | 0.23 | YES
10 | GTF2H5 | GTF2H5 | GTF2H5 | 3596 | 0.067 | 0.26 | YES
11 | ERCC5 | ERCC5 | ERCC5 | 3624 | 0.066 | 0.28 | YES
12 | RFC2 | RFC2 | RFC2 | 3857 | 0.061 | 0.29 | YES
13 | RFC1 | RFC1 | RFC1 | 4371 | 0.051 | 0.29 | YES
14 | GTF2H4 | GTF2H4 | GTF2H4 | 4445 | 0.05 | 0.3 | YES
15 | GTF2H3 | GTF2H3 | GTF2H3 | 4570 | 0.048 | 0.32 | YES
16 | RFC4 | RFC4 | RFC4 | 4607 | 0.047 | 0.33 | YES
17 | XPC | XPC | XPC | 4611 | 0.047 | 0.35 | YES
18 | RFC5 | RFC5 | RFC5 | 5113 | 0.039 | 0.34 | YES
19 | GTF2H2 | GTF2H2 | GTF2H2 | 5236 | 0.037 | 0.35 | YES
20 | POLD1 | POLD1 | POLD1 | 5328 | 0.035 | 0.36 | YES
21 | CUL4B | CUL4B | CUL4B | 5385 | 0.034 | 0.37 | YES
22 | RPA1 | RPA1 | RPA1 | 6589 | 0.017 | 0.31 | NO
23 | RBX1 | RBX1 | RBX1 | 6704 | 0.015 | 0.31 | NO
24 | CCNH | CCNH | CCNH | 6765 | 0.014 | 0.32 | NO
25 | RAD23A | RAD23A | RAD23A | 6923 | 0.012 | 0.31 | NO
26 | ERCC4 | ERCC4 | ERCC4 | 7719 | 0.0016 | 0.27 | NO
27 | CUL4A | CUL4A | CUL4A | 7839 | 0.00021 | 0.26 | NO
28 | ERCC1 | ERCC1 | ERCC1 | 8115 | -0.0038 | 0.25 | NO
29 | ERCC3 | ERCC3 | ERCC3 | 8155 | -0.0043 | 0.25 | NO
30 | POLD2 | POLD2 | POLD2 | 8307 | -0.0063 | 0.24 | NO
31 | POLE3 | POLE3 | POLE3 | 8556 | -0.01 | 0.24 | NO
32 | ERCC2 | ERCC2 | ERCC2 | 8828 | -0.013 | 0.23 | NO
33 | POLD3 | POLD3 | POLD3 | 8866 | -0.014 | 0.23 | NO
34 | DDB1 | DDB1 | DDB1 | 9307 | -0.02 | 0.21 | NO
35 | MNAT1 | MNAT1 | MNAT1 | 9698 | -0.025 | 0.2 | NO
36 | LIG1 | LIG1 | LIG1 | 9768 | -0.026 | 0.21 | NO
37 | POLE4 | POLE4 | POLE4 | 11484 | -0.057 | 0.14 | NO
38 | CETN2 | CETN2 | CETN2 | 11688 | -0.061 | 0.16 | NO
39 | RFC3 | RFC3 | RFC3 | 12200 | -0.074 | 0.16 | NO
40 | ERCC8 | ERCC8 | ERCC8 | 12778 | -0.089 | 0.16 | NO
41 | CDK7 | CDK7 | CDK7 | 12853 | -0.091 | 0.2 | NO
42 | POLD4 | POLD4 | POLD4 | 13290 | -0.1 | 0.22 | NO
43 | ERCC6 | ERCC6 | ERCC6 | 14917 | -0.17 | 0.2 | NO

Figure S69. 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 LYSINE DEGRADATION.

Figure S70. Get High-res Image For the top 5 core enriched genes in the pathway: KEGG LYSINE 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 AMINOACYL TRNA BIOSYNTHESIS

Table S36. 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 | LSM6 | LSM6 | LSM6 | 1503 | 0.15 | -0.051 | YES
2 | MAGOHB | MAGOHB | MAGOHB | 2173 | 0.11 | -0.064 | YES
3 | PPIL1 | PPIL1 | PPIL1 | 2419 | 0.1 | -0.057 | YES
4 | CDC40 | CDC40 | CDC40 | 2608 | 0.095 | -0.048 | YES
5 | TXNL4A | TXNL4A | TXNL4A | 2611 | 0.095 | -0.028 | YES
6 | SNRPD3 | SNRPD3 | SNRPD3 | 2668 | 0.093 | -0.013 | YES
7 | SNRPD1 | SNRPD1 | SNRPD1 | 2818 | 0.088 | -0.0029 | YES
8 | SF3B3 | SF3B3 | SF3B3 | 2878 | 0.086 | 0.011 | YES
9 | CDC5L | CDC5L | CDC5L | 2911 | 0.085 | 0.027 | YES
10 | LSM7 | LSM7 | LSM7 | 2986 | 0.082 | 0.04 | YES
11 | PRPF4 | PRPF4 | PRPF4 | 3128 | 0.078 | 0.048 | YES
12 | SFRS4 | SFRS4 | SFRS4 | 3169 | 0.077 | 0.061 | YES
13 | PPIH | PPIH | PPIH | 3189 | 0.077 | 0.076 | YES
14 | DHX8 | DHX8 | DHX8 | 3404 | 0.072 | 0.079 | YES
15 | SNRPG | SNRPG | SNRPG | 3423 | 0.071 | 0.092 | YES
16 | SNRPB | SNRPB | SNRPB | 3808 | 0.062 | 0.084 | YES
17 | PLRG1 | PLRG1 | PLRG1 | 3904 | 0.06 | 0.091 | YES
18 | DHX38 | DHX38 | DHX38 | 3958 | 0.059 | 0.1 | YES
19 | SNRNP40 | SNRNP40 | SNRNP40 | 3962 | 0.059 | 0.11 | YES
20 | SF3B14 | SF3B14 | SF3B14 | 3983 | 0.058 | 0.12 | YES
21 | LSM2 | LSM2 | LSM2 | 3992 | 0.058 | 0.13 | YES
22 | U2AF1 | U2AF1 | U2AF1 | 4015 | 0.058 | 0.14 | YES
23 | SFRS9 | SFRS9 | SFRS9 | 4047 | 0.057 | 0.15 | YES
24 | DHX16 | DHX16 | DHX16 | 4180 | 0.055 | 0.16 | YES
25 | PQBP1 | PQBP1 | PQBP1 | 4211 | 0.054 | 0.17 | YES
26 | SNRPB2 | SNRPB2 | SNRPB2 | 4250 | 0.053 | 0.18 | YES
27 | SF3A1 | SF3A1 | SF3A1 | 4293 | 0.052 | 0.18 | YES
28 | CRNKL1 | CRNKL1 | CRNKL1 | 4322 | 0.052 | 0.19 | YES
29 | THOC4 | THOC4 | THOC4 | 4329 | 0.052 | 0.2 | YES
30 | SFRS3 | SFRS3 | SFRS3 | 4339 | 0.051 | 0.21 | YES
31 | SNRPA1 | SNRPA1 | SNRPA1 | 4340 | 0.051 | 0.22 | YES
32 | SART1 | SART1 | SART1 | 4413 | 0.05 | 0.23 | YES
33 | MAGOH | MAGOH | MAGOH | 4529 | 0.048 | 0.23 | YES
34 | ISY1 | ISY1 | ISY1 | 4551 | 0.048 | 0.24 | YES
35 | LSM3 | LSM3 | LSM3 | 4589 | 0.048 | 0.25 | YES
36 | SNW1 | SNW1 | SNW1 | 4716 | 0.045 | 0.25 | YES
37 | SNRPE | SNRPE | SNRPE | 4764 | 0.044 | 0.26 | YES
38 | SF3A3 | SF3A3 | SF3A3 | 4852 | 0.043 | 0.26 | YES
39 | SF3B2 | SF3B2 | SF3B2 | 4891 | 0.042 | 0.27 | YES
40 | SNRPC | SNRPC | SNRPC | 5102 | 0.039 | 0.27 | YES
41 | SFRS13A | SFRS13A | SFRS13A | 5181 | 0.038 | 0.27 | YES
42 | PPIE | PPIE | PPIE | 5265 | 0.036 | 0.27 | YES
43 | CCDC12 | CCDC12 | CCDC12 | 5272 | 0.036 | 0.28 | YES
44 | LSM5 | LSM5 | LSM5 | 5340 | 0.035 | 0.28 | YES
45 | SFRS1 | SFRS1 | SFRS1 | 5351 | 0.035 | 0.29 | YES
46 | TRA2A | TRA2A | TRA2A | 5380 | 0.035 | 0.3 | YES
47 | SNRPA | SNRPA | SNRPA | 5404 | 0.034 | 0.3 | YES
48 | SNRPF | SNRPF | SNRPF | 5599 | 0.031 | 0.3 | YES
49 | PRPF19 | PRPF19 | PRPF19 | 5602 | 0.031 | 0.3 | YES
50 | PRPF8 | PRPF8 | PRPF8 | 5614 | 0.031 | 0.31 | YES
51 | SFRS7 | SFRS7 | SFRS7 | 5725 | 0.029 | 0.31 | YES
52 | HNRNPK | HNRNPK | HNRNPK | 5816 | 0.027 | 0.31 | YES
53 | SR140 | SR140 | SR140 | 5826 | 0.027 | 0.31 | YES
54 | SMNDC1 | SMNDC1 | SMNDC1 | 5852 | 0.027 | 0.32 | YES
55 | SF3A2 | SF3A2 | SF3A2 | 5891 | 0.026 | 0.32 | YES
56 | BAT1 | BAT1 | BAT1 | 5904 | 0.026 | 0.32 | YES
57 | SF3B5 | SF3B5 | SF3B5 | 5935 | 0.026 | 0.33 | YES
58 | PRPF18 | PRPF18 | PRPF18 | 5938 | 0.026 | 0.33 | YES
59 | NCBP1 | NCBP1 | NCBP1 | 5946 | 0.025 | 0.34 | YES
60 | BCAS2 | BCAS2 | BCAS2 | 6056 | 0.024 | 0.34 | YES
61 | U2AF2 | U2AF2 | U2AF2 | 6066 | 0.024 | 0.34 | YES
62 | TRA2B | TRA2B | TRA2B | 6083 | 0.024 | 0.35 | YES
63 | SFRS2 | SFRS2 | SFRS2 | 6183 | 0.022 | 0.34 | YES
64 | HNRNPU | HNRNPU | HNRNPU | 6193 | 0.022 | 0.35 | YES
65 | HSPA1A | HSPA1A | HSPA1A | 6284 | 0.021 | 0.35 | YES
66 | SNRNP200 | SNRNP200 | SNRNP200 | 6396 | 0.019 | 0.35 | YES
67 | RBMX | RBMX | RBMX | 6399 | 0.019 | 0.35 | YES
68 | ACIN1 | ACIN1 | ACIN1 | 6421 | 0.019 | 0.35 | YES
69 | EFTUD2 | EFTUD2 | EFTUD2 | 6437 | 0.019 | 0.36 | YES
70 | DDX23 | DDX23 | DDX23 | 6469 | 0.018 | 0.36 | YES
71 | HNRNPC | HNRNPC | HNRNPC | 6482 | 0.018 | 0.36 | YES
72 | HNRNPA1L2 | HNRNPA1L2 | HNRNPA1L2 | 6549 | 0.017 | 0.36 | YES
73 | PHF5A | PHF5A | PHF5A | 6602 | 0.016 | 0.36 | YES
74 | HSPA1B | HSPA1B | HSPA1B | 6661 | 0.016 | 0.36 | YES
75 | HNRNPA1 | HNRNPA1 | HNRNPA1 | 6789 | 0.014 | 0.36 | YES
76 | DHX15 | DHX15 | DHX15 | 6802 | 0.014 | 0.36 | YES
77 | THOC2 | THOC2 | THOC2 | 6806 | 0.014 | 0.36 | YES
78 | BUD31 | BUD31 | BUD31 | 6883 | 0.012 | 0.36 | NO
79 | USP39 | USP39 | USP39 | 6914 | 0.012 | 0.36 | NO
80 | CTNNBL1 | CTNNBL1 | CTNNBL1 | 7006 | 0.011 | 0.36 | NO
81 | PRPF38A | PRPF38A | PRPF38A | 7033 | 0.011 | 0.36 | NO
82 | DDX46 | DDX46 | DDX46 | 7084 | 0.01 | 0.36 | NO
83 | PRPF3 | PRPF3 | PRPF3 | 7107 | 0.0096 | 0.36 | NO
84 | SNRNP70 | SNRNP70 | SNRNP70 | 7233 | 0.0082 | 0.35 | NO
85 | SNRPD2 | SNRPD2 | SNRPD2 | 7237 | 0.0081 | 0.36 | NO
86 | HNRNPM | HNRNPM | HNRNPM | 7255 | 0.0079 | 0.36 | NO
87 | HSPA2 | HSPA2 | HSPA2 | 7288 | 0.0075 | 0.36 | NO
88 | SNRNP27 | SNRNP27 | SNRNP27 | 7342 | 0.0067 | 0.36 | NO
89 | SYF2 | SYF2 | SYF2 | 7444 | 0.0054 | 0.35 | NO
90 | XAB2 | XAB2 | XAB2 | 7574 | 0.0036 | 0.34 | NO
91 | HNRNPA3 | HNRNPA3 | HNRNPA3 | 7644 | 0.0026 | 0.34 | NO
92 | WBP11 | WBP11 | WBP11 | 8036 | -0.0028 | 0.32 | NO
93 | TCERG1 | TCERG1 | TCERG1 | 8096 | -0.0036 | 0.32 | NO
94 | SLU7 | SLU7 | SLU7 | 8104 | -0.0036 | 0.32 | NO
95 | THOC1 | THOC1 | THOC1 | 8303 | -0.0062 | 0.31 | NO
96 | RBM25 | RBM25 | RBM25 | 8370 | -0.0071 | 0.31 | NO
97 | THOC3 | THOC3 | THOC3 | 8468 | -0.0088 | 0.3 | NO
98 | CHERP | CHERP | CHERP | 8484 | -0.0089 | 0.3 | NO
99 | DDX42 | DDX42 | DDX42 | 8713 | -0.012 | 0.29 | NO
100 | RBM22 | RBM22 | RBM22 | 8730 | -0.012 | 0.3 | NO
101 | SF3B1 | SF3B1 | SF3B1 | 8732 | -0.012 | 0.3 | NO
102 | DDX5 | DDX5 | DDX5 | 8996 | -0.016 | 0.29 | NO
103 | SFRS6 | SFRS6 | SFRS6 | 9024 | -0.016 | 0.29 | NO
104 | SF3B4 | SF3B4 | SF3B4 | 9048 | -0.016 | 0.29 | NO
105 | PCBP1 | PCBP1 | PCBP1 | 9054 | -0.016 | 0.29 | NO
106 | NAA38 | NAA38 | NAA38 | 9065 | -0.016 | 0.3 | NO
107 | SFRS5 | SFRS5 | SFRS5 | 9164 | -0.018 | 0.3 | NO
108 | HSPA8 | HSPA8 | HSPA8 | 9255 | -0.019 | 0.29 | NO
109 | PRPF31 | PRPF31 | PRPF31 | 9281 | -0.02 | 0.3 | NO
110 | CWC15 | CWC15 | CWC15 | 9775 | -0.026 | 0.28 | NO
111 | PRPF38B | PRPF38B | PRPF38B | 9872 | -0.028 | 0.28 | NO
112 | RBM8A | RBM8A | RBM8A | 9997 | -0.03 | 0.28 | NO
113 | AQR | AQR | AQR | 10552 | -0.039 | 0.25 | NO
114 | PRPF6 | PRPF6 | PRPF6 | 10579 | -0.039 | 0.26 | NO
115 | PRPF40A | PRPF40A | PRPF40A | 10606 | -0.04 | 0.27 | NO
116 | RBM17 | RBM17 | RBM17 | 10673 | -0.041 | 0.27 | NO
117 | PUF60 | PUF60 | PUF60 | 10881 | -0.045 | 0.27 | NO
118 | PRPF40B | PRPF40B | PRPF40B | 10972 | -0.047 | 0.27 | NO
119 | HSPA6 | HSPA6 | HSPA6 | 11349 | -0.054 | 0.26 | NO
120 | LSM4 | LSM4 | LSM4 | 11718 | -0.062 | 0.26 | NO
121 | EIF4A3 | EIF4A3 | EIF4A3 | 11734 | -0.062 | 0.27 | NO
122 | NHP2L1 | NHP2L1 | NHP2L1 | 12472 | -0.081 | 0.24 | NO
123 | HSPA1L | HSPA1L | HSPA1L | 12534 | -0.082 | 0.26 | NO
124 | ZMAT2 | ZMAT2 | ZMAT2 | 12597 | -0.084 | 0.27 | NO
125 | SFRS2B | SFRS2B | SFRS2B | 16480 | -0.27 | 0.12 | NO

Figure S71. 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 S72. 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

genes ES table in pathway: KEGG RNA DEGRADATION

Table S37. 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 | POLR2J2 | POLR2J2 | POLR2J2 | 1638 | 0.14 | 0.031 | YES
2 | POLR3G | POLR3G | POLR3G | 2408 | 0.1 | 0.076 | YES
3 | ZNRD1 | ZNRD1 | ZNRD1 | 2635 | 0.094 | 0.14 | YES
4 | POLR2F | POLR2F | POLR2F | 3065 | 0.08 | 0.19 | YES
5 | POLR2C | POLR2C | POLR2C | 3249 | 0.075 | 0.24 | YES
6 | POLR3F | POLR3F | POLR3F | 3429 | 0.071 | 0.29 | YES
7 | POLR2G | POLR2G | POLR2G | 4478 | 0.049 | 0.27 | YES
8 | POLR3K | POLR3K | POLR3K | 4598 | 0.047 | 0.31 | YES
9 | POLR1E | POLR1E | POLR1E | 5308 | 0.036 | 0.3 | YES
10 | POLR2A | POLR2A | POLR2A | 5320 | 0.036 | 0.33 | YES
11 | POLR3GL | POLR3GL | POLR3GL | 5442 | 0.034 | 0.35 | YES
12 | POLR2J | POLR2J | POLR2J | 5704 | 0.029 | 0.36 | YES
13 | POLR2B | POLR2B | POLR2B | 5754 | 0.028 | 0.38 | YES
14 | POLR2D | POLR2D | POLR2D | 6071 | 0.024 | 0.38 | YES
15 | POLR2E | POLR2E | POLR2E | 6113 | 0.023 | 0.4 | YES
16 | POLR2K | POLR2K | POLR2K | 6245 | 0.021 | 0.41 | YES
17 | POLR2I | POLR2I | POLR2I | 6299 | 0.021 | 0.43 | YES
18 | POLR3B | POLR3B | POLR3B | 6664 | 0.016 | 0.42 | NO
19 | POLR2L | POLR2L | POLR2L | 6819 | 0.013 | 0.42 | NO
20 | POLR1B | POLR1B | POLR1B | 7843 | 0.00015 | 0.37 | NO
21 | POLR1C | POLR1C | POLR1C | 8098 | -0.0036 | 0.36 | NO
22 | POLR3C | POLR3C | POLR3C | 8176 | -0.0046 | 0.36 | NO
23 | POLR1A | POLR1A | POLR1A | 8773 | -0.013 | 0.34 | NO
24 | POLR2J3 | POLR2J3 | POLR2J3 | 9913 | -0.029 | 0.3 | NO
25 | POLR3D | POLR3D | POLR3D | 10415 | -0.036 | 0.3 | NO
26 | POLR3A | POLR3A | POLR3A | 10684 | -0.041 | 0.32 | NO
27 | POLR3H | POLR3H | POLR3H | 11114 | -0.05 | 0.34 | NO
28 | POLR1D | POLR1D | POLR1D | 12230 | -0.075 | 0.34 | NO

Figure S73. 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 RNA DEGRADATION.

Figure S74. Get High-res Image For the top 5 core enriched genes in the pathway: KEGG RNA 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 RNA POLYMERASE

Table S38. 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 | FBXO43 | FBXO43 | FBXO43 | 50 | 0.51 | 0.045 | YES
2 | STAG3 | STAG3 | STAG3 | 86 | 0.45 | 0.085 | YES
3 | CPEB1 | CPEB1 | CPEB1 | 196 | 0.38 | 0.11 | YES
4 | CCNE2 | CCNE2 | CCNE2 | 470 | 0.28 | 0.12 | YES
5 | MAPK12 | MAPK12 | MAPK12 | 731 | 0.23 | 0.13 | YES
6 | RPS6KA6 | RPS6KA6 | RPS6KA6 | 973 | 0.2 | 0.14 | YES
7 | FBXO5 | FBXO5 | FBXO5 | 977 | 0.2 | 0.16 | YES
8 | SGOL1 | SGOL1 | SGOL1 | 997 | 0.2 | 0.17 | YES
9 | ANAPC10 | ANAPC10 | ANAPC10 | 1300 | 0.16 | 0.17 | YES
10 | SMC1A | SMC1A | SMC1A | 1490 | 0.15 | 0.18 | YES
11 | PPP2R5B | PPP2R5B | PPP2R5B | 1620 | 0.14 | 0.18 | YES
12 | CDC20 | CDC20 | CDC20 | 1701 | 0.14 | 0.19 | YES
13 | MAD2L1 | MAD2L1 | MAD2L1 | 1712 | 0.14 | 0.2 | YES
14 | AURKA | AURKA | AURKA | 1793 | 0.13 | 0.21 | YES
15 | PLK1 | PLK1 | PLK1 | 1925 | 0.12 | 0.22 | YES
16 | CCNB2 | CCNB2 | CCNB2 | 1956 | 0.12 | 0.23 | YES
17 | PPP3R2 | PPP3R2 | PPP3R2 | 2115 | 0.12 | 0.23 | YES
18 | CHP2 | CHP2 | CHP2 | 2126 | 0.12 | 0.24 | YES
19 | MAD2L2 | MAD2L2 | MAD2L2 | 2180 | 0.11 | 0.25 | YES
20 | PPP3CC | PPP3CC | PPP3CC | 2280 | 0.11 | 0.25 | YES
21 | CDK2 | CDK2 | CDK2 | 2417 | 0.1 | 0.25 | YES
22 | BUB1 | BUB1 | BUB1 | 2462 | 0.1 | 0.26 | YES
23 | PPP2R5D | PPP2R5D | PPP2R5D | 2538 | 0.097 | 0.26 | YES
24 | SMC3 | SMC3 | SMC3 | 2558 | 0.097 | 0.27 | YES
25 | SMC1B | SMC1B | SMC1B | 2625 | 0.094 | 0.28 | YES
26 | CDC25C | CDC25C | CDC25C | 2678 | 0.092 | 0.28 | YES
27 | ESPL1 | ESPL1 | ESPL1 | 2684 | 0.092 | 0.29 | YES
28 | CCNB1 | CCNB1 | CCNB1 | 2765 | 0.09 | 0.3 | YES
29 | PTTG1 | PTTG1 | PTTG1 | 3056 | 0.08 | 0.29 | NO
30 | CDC26 | CDC26 | CDC26 | 3241 | 0.076 | 0.28 | NO
31 | ANAPC2 | ANAPC2 | ANAPC2 | 3970 | 0.059 | 0.25 | NO
32 | MAPK3 | MAPK3 | MAPK3 | 4321 | 0.052 | 0.24 | NO
33 | MOS | MOS | MOS | 4417 | 0.05 | 0.24 | NO
34 | CALML3 | CALML3 | CALML3 | 4486 | 0.049 | 0.24 | NO
35 | PPP1CC | PPP1CC | PPP1CC | 4666 | 0.046 | 0.23 | NO
36 | PRKACB | PRKACB | PRKACB | 4707 | 0.046 | 0.23 | NO
37 | CDK1 | CDK1 | CDK1 | 4757 | 0.045 | 0.24 | NO
38 | MAPK1 | MAPK1 | MAPK1 | 4790 | 0.044 | 0.24 | NO
39 | PPP2CA | PPP2CA | PPP2CA | 4986 | 0.041 | 0.23 | NO
40 | ITPR2 | ITPR2 | ITPR2 | 5212 | 0.037 | 0.22 | NO
41 | PRKACA | PRKACA | PRKACA | 5244 | 0.037 | 0.22 | NO
42 | RPS6KA3 | RPS6KA3 | RPS6KA3 | 5252 | 0.036 | 0.23 | NO
43 | PPP2R5C | PPP2R5C | PPP2R5C | 5305 | 0.036 | 0.23 | NO
44 | CDC27 | CDC27 | CDC27 | 5335 | 0.035 | 0.23 | NO
45 | ANAPC7 | ANAPC7 | ANAPC7 | 5416 | 0.034 | 0.23 | NO
46 | YWHAH | YWHAH | YWHAH | 5454 | 0.033 | 0.23 | NO
47 | ADCY1 | ADCY1 | ADCY1 | 5540 | 0.032 | 0.23 | NO
48 | PTTG2 | PTTG2 | PTTG2 | 5549 | 0.032 | 0.23 | NO
49 | YWHAG | YWHAG | YWHAG | 5747 | 0.028 | 0.22 | NO
50 | CAMK2G | CAMK2G | CAMK2G | 5925 | 0.026 | 0.22 | NO
51 | YWHAB | YWHAB | YWHAB | 6462 | 0.018 | 0.19 | NO
52 | PPP3R1 | PPP3R1 | PPP3R1 | 6507 | 0.018 | 0.19 | NO
53 | RBX1 | RBX1 | RBX1 | 6704 | 0.015 | 0.18 | NO
54 | CDC16 | CDC16 | CDC16 | 6836 | 0.013 | 0.17 | NO
55 | ANAPC5 | ANAPC5 | ANAPC5 | 6851 | 0.013 | 0.17 | NO
56 | ANAPC4 | ANAPC4 | ANAPC4 | 7050 | 0.01 | 0.16 | NO
57 | YWHAE | YWHAE | YWHAE | 7073 | 0.01 | 0.16 | NO
58 | PPP2R5E | PPP2R5E | PPP2R5E | 7410 | 0.0059 | 0.15 | NO
59 | PPP3CB | PPP3CB | PPP3CB | 7466 | 0.0051 | 0.14 | NO
60 | SLK | SLK | SLK | 7515 | 0.0044 | 0.14 | NO
61 | CUL1 | CUL1 | CUL1 | 7660 | 0.0024 | 0.13 | NO
62 | CALM3 | CALM3 | CALM3 | 7794 | 0.00071 | 0.13 | NO
63 | ANAPC13 | ANAPC13 | ANAPC13 | 7890 | -0.00052 | 0.12 | NO
64 | PPP1CA | PPP1CA | PPP1CA | 7953 | -0.0014 | 0.12 | NO
65 | CDC23 | CDC23 | CDC23 | 8177 | -0.0046 | 0.11 | NO
66 | PKMYT1 | PKMYT1 | PKMYT1 | 8331 | -0.0066 | 0.099 | NO
67 | PPP2R1B | PPP2R1B | PPP2R1B | 8389 | -0.0075 | 0.096 | NO
68 | PRKX | PRKX | PRKX | 8673 | -0.012 | 0.082 | NO
69 | ADCY6 | ADCY6 | ADCY6 | 8687 | -0.012 | 0.083 | NO
70 | SKP1 | SKP1 | SKP1 | 8800 | -0.013 | 0.078 | NO
71 | RPS6KA1 | RPS6KA1 | RPS6KA1 | 8983 | -0.015 | 0.069 | NO
72 | MAP2K1 | MAP2K1 | MAP2K1 | 9008 | -0.016 | 0.07 | NO
73 | FBXW11 | FBXW11 | FBXW11 | 9142 | -0.018 | 0.064 | NO
74 | ADCY7 | ADCY7 | ADCY7 | 9260 | -0.019 | 0.06 | NO
75 | CCNE1 | CCNE1 | CCNE1 | 9436 | -0.022 | 0.052 | NO
76 | BTRC | BTRC | BTRC | 9697 | -0.025 | 0.04 | NO
77 | ADCY9 | ADCY9 | ADCY9 | 10056 | -0.03 | 0.024 | NO
78 | CALM2 | CALM2 | CALM2 | 10084 | -0.031 | 0.025 | NO
79 | ITPR1 | ITPR1 | ITPR1 | 10086 | -0.031 | 0.028 | NO
80 | ANAPC11 | ANAPC11 | ANAPC11 | 10134 | -0.032 | 0.029 | NO
81 | PPP1CB | PPP1CB | PPP1CB | 10220 | -0.033 | 0.027 | NO
82 | CALM1 | CALM1 | CALM1 | 10473 | -0.038 | 0.017 | NO
83 | CHP | CHP | CHP | 10739 | -0.042 | 0.0066 | NO
84 | ANAPC1 | ANAPC1 | ANAPC1 | 10769 | -0.043 | 0.0091 | NO
85 | YWHAQ | YWHAQ | YWHAQ | 10799 | -0.044 | 0.012 | NO
86 | PPP2R1A | PPP2R1A | PPP2R1A | 10807 | -0.044 | 0.015 | NO
87 | YWHAZ | YWHAZ | YWHAZ | 10872 | -0.045 | 0.016 | NO
88 | SPDYC | SPDYC | SPDYC | 11009 | -0.047 | 0.013 | NO
89 | PPP2R5A | PPP2R5A | PPP2R5A | 12008 | -0.069 | -0.034 | NO
90 | PPP2CB | PPP2CB | PPP2CB | 12283 | -0.076 | -0.042 | NO
91 | ADCY5 | ADCY5 | ADCY5 | 12412 | -0.079 | -0.042 | NO
92 | CAMK2D | CAMK2D | CAMK2D | 13153 | -0.1 | -0.072 | NO
93 | CALML5 | CALML5 | CALML5 | 13249 | -0.1 | -0.068 | NO
94 | PPP3CA | PPP3CA | PPP3CA | 13547 | -0.11 | -0.073 | NO
95 | ADCY4 | ADCY4 | ADCY4 | 13846 | -0.12 | -0.078 | NO
96 | ADCY2 | ADCY2 | ADCY2 | 14063 | -0.13 | -0.077 | NO
97 | ITPR3 | ITPR3 | ITPR3 | 14772 | -0.16 | -0.1 | NO
98 | IGF1R | IGF1R | IGF1R | 15353 | -0.2 | -0.11 | NO
99 | AR | AR | AR | 15400 | -0.2 | -0.097 | NO
100 | REC8 | REC8 | REC8 | 15405 | -0.2 | -0.079 | NO
101 | RPS6KA2 | RPS6KA2 | RPS6KA2 | 15567 | -0.21 | -0.068 | NO
102 | ADCY8 | ADCY8 | ADCY8 | 15647 | -0.21 | -0.053 | NO
103 | CAMK2B | CAMK2B | CAMK2B | 16146 | -0.25 | -0.057 | NO
104 | SPDYA | SPDYA | SPDYA | 16159 | -0.25 | -0.034 | NO
105 | PGR | PGR | PGR | 17233 | -0.33 | -0.062 | NO
106 | CAMK2A | CAMK2A | CAMK2A | 18180 | -0.45 | -0.071 | NO
107 | IGF1 | IGF1 | IGF1 | 18334 | -0.49 | -0.033 | NO
108 | CALML6 | CALML6 | CALML6 | 18451 | -0.54 | 0.01 | NO

Figure S75. 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 RNA POLYMERASE.

Figure S76. Get High-res Image For the top 5 core enriched genes in the pathway: KEGG RNA POLYMERASE, 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 BASAL TRANSCRIPTION FACTORS

Table S39. 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 | RPA4 | RPA4 | RPA4 | 666 | 0.24 | 0.14 | YES
2 | EME1 | EME1 | EME1 | 1689 | 0.14 | 0.19 | YES
3 | RAD54L | RAD54L | RAD54L | 2676 | 0.092 | 0.2 | YES
4 | RPA3 | RPA3 | RPA3 | 3032 | 0.081 | 0.24 | YES
5 | RPA2 | RPA2 | RPA2 | 3583 | 0.067 | 0.26 | YES
6 | TOP3A | TOP3A | TOP3A | 4019 | 0.058 | 0.28 | YES
7 | TOP3B | TOP3B | TOP3B | 4230 | 0.054 | 0.31 | YES
8 | RAD51 | RAD51 | RAD51 | 4391 | 0.051 | 0.34 | YES
9 | SSBP1 | SSBP1 | SSBP1 | 5182 | 0.038 | 0.32 | YES
10 | SHFM1 | SHFM1 | SHFM1 | 5204 | 0.037 | 0.35 | YES
11 | RAD52 | RAD52 | RAD52 | 5290 | 0.036 | 0.37 | YES
12 | POLD1 | POLD1 | POLD1 | 5328 | 0.035 | 0.4 | YES
13 | RPA1 | RPA1 | RPA1 | 6589 | 0.017 | 0.34 | NO
14 | RAD51L3 | RAD51L3 | RAD51L3 | 7370 | 0.0064 | 0.3 | NO
15 | NBN | NBN | NBN | 7405 | 0.0059 | 0.3 | NO
16 | XRCC2 | XRCC2 | XRCC2 | 7712 | 0.0017 | 0.29 | NO
17 | MUS81 | MUS81 | MUS81 | 7941 | -0.0012 | 0.28 | NO
18 | POLD2 | POLD2 | POLD2 | 8307 | -0.0063 | 0.26 | NO
19 | BLM | BLM | BLM | 8371 | -0.0071 | 0.27 | NO
20 | POLD3 | POLD3 | POLD3 | 8866 | -0.014 | 0.25 | NO
21 | RAD54B | RAD54B | RAD54B | 9178 | -0.018 | 0.25 | NO
22 | RAD50 | RAD50 | RAD50 | 9240 | -0.019 | 0.26 | NO
23 | XRCC3 | XRCC3 | XRCC3 | 10024 | -0.03 | 0.24 | NO
24 | RAD51L1 | RAD51L1 | RAD51L1 | 11588 | -0.059 | 0.2 | NO
25 | MRE11A | MRE11A | MRE11A | 12113 | -0.072 | 0.22 | NO
26 | BRCA2 | BRCA2 | BRCA2 | 12114 | -0.072 | 0.27 | NO
27 | POLD4 | POLD4 | POLD4 | 13290 | -0.1 | 0.29 | NO

Figure S77. 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 BASAL TRANSCRIPTION FACTORS.

Figure S78. Get High-res Image For the top 5 core enriched genes in the pathway: KEGG BASAL TRANSCRIPTION FACTORS, 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 DNA REPLICATION

Table S40. 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 | AADAT | AADAT | AADAT | 295 | 0.33 | 0.088 | YES
2 | PLOD3 | PLOD3 | PLOD3 | 1176 | 0.18 | 0.097 | YES
3 | AASS | AASS | AASS | 1333 | 0.16 | 0.14 | YES
4 | PLOD2 | PLOD2 | PLOD2 | 1500 | 0.15 | 0.18 | YES
5 | ACAT2 | ACAT2 | ACAT2 | 1639 | 0.14 | 0.22 | YES
6 | PLOD1 | PLOD1 | PLOD1 | 1844 | 0.13 | 0.25 | YES
7 | SETD8 | SETD8 | SETD8 | 2460 | 0.1 | 0.24 | YES
8 | SUV39H1 | SUV39H1 | SUV39H1 | 2925 | 0.085 | 0.25 | YES
9 | SETD1A | SETD1A | SETD1A | 2936 | 0.084 | 0.27 | YES
10 | ALDH2 | ALDH2 | ALDH2 | 4270 | 0.053 | 0.22 | NO
11 | WHSC1L1 | WHSC1L1 | WHSC1L1 | 4311 | 0.052 | 0.23 | NO
12 | EHMT2 | EHMT2 | EHMT2 | 4541 | 0.048 | 0.24 | NO
13 | SUV420H1 | SUV420H1 | SUV420H1 | 5348 | 0.035 | 0.2 | NO
14 | DOT1L | DOT1L | DOT1L | 5459 | 0.033 | 0.21 | NO
15 | WHSC1 | WHSC1 | WHSC1 | 5533 | 0.032 | 0.22 | NO
16 | EHMT1 | EHMT1 | EHMT1 | 6160 | 0.023 | 0.19 | NO
17 | ASH1L | ASH1L | ASH1L | 6254 | 0.021 | 0.19 | NO
18 | OGDH | OGDH | OGDH | 6541 | 0.017 | 0.18 | NO
19 | ALDH7A1 | ALDH7A1 | ALDH7A1 | 6850 | 0.013 | 0.17 | NO
20 | SETD2 | SETD2 | SETD2 | 6900 | 0.012 | 0.17 | NO
21 | SETMAR | SETMAR | SETMAR | 6954 | 0.012 | 0.17 | NO
22 | NSD1 | NSD1 | NSD1 | 7542 | 0.0041 | 0.14 | NO
23 | HADH | HADH | HADH | 7650 | 0.0025 | 0.13 | NO
24 | ECHS1 | ECHS1 | ECHS1 | 7919 | -0.001 | 0.12 | NO
25 | ALDH9A1 | ALDH9A1 | ALDH9A1 | 8572 | -0.01 | 0.088 | NO
26 | AASDH | AASDH | AASDH | 8647 | -0.011 | 0.088 | NO
27 | HADHA | HADHA | HADHA | 8663 | -0.011 | 0.091 | NO
28 | SUV39H2 | SUV39H2 | SUV39H2 | 9107 | -0.017 | 0.072 | NO
29 | SETD1B | SETD1B | SETD1B | 9303 | -0.02 | 0.068 | NO
30 | ACAT1 | ACAT1 | ACAT1 | 9847 | -0.028 | 0.048 | NO
31 | GCDH | GCDH | GCDH | 9909 | -0.029 | 0.054 | NO
32 | DLST | DLST | DLST | 9939 | -0.029 | 0.061 | NO
33 | TMLHE | TMLHE | TMLHE | 10063 | -0.03 | 0.064 | NO
34 | ALDH1B1 | ALDH1B1 | ALDH1B1 | 11160 | -0.05 | 0.021 | NO
35 | OGDHL | OGDHL | OGDHL | 11183 | -0.051 | 0.036 | NO
36 | SETDB1 | SETDB1 | SETDB1 | 11247 | -0.052 | 0.049 | NO
37 | AASDHPPT | AASDHPPT | AASDHPPT | 13091 | -0.098 | -0.019 | NO
38 | SUV420H2 | SUV420H2 | SUV420H2 | 13316 | -0.1 | 0.0027 | NO
39 | SETD7 | SETD7 | SETD7 | 14120 | -0.14 | 0.0024 | NO
40 | ALDH3A2 | ALDH3A2 | ALDH3A2 | 14541 | -0.15 | 0.028 | NO
41 | SETDB2 | SETDB2 | SETDB2 | 14836 | -0.17 | 0.066 | NO
42 | BBOX1 | BBOX1 | BBOX1 | 15288 | -0.19 | 0.1 | NO
43 | PIPOX | PIPOX | PIPOX | 16173 | -0.25 | 0.13 | NO

Figure S79. 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 DNA REPLICATION.

Figure S80. Get High-res Image For the top 5 core enriched genes in the pathway: KEGG DNA REPLICATION, 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

- up-regulated, please check the list of up-regulated genes

- down-regulated, please check the list of down-regulated genes

Expression level

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

- highly expressed genes, please check the list of high (top 30%) expressed genes

- low expressed genes, please check the list of low (bottom 30%) expressed genes

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

- significantly differently expressed genes by eBayes lm fit, please check the list of significant genes

Methods & Data
Input

- Gene set database = c2.cp.v3.0-2.symbols.gmt

- Expression data file = UCS-TP.uncv2.mRNAseq_RSEM_normalized_log2.txt

- Phenotype data file = UCS-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.

- Analysis Results (MD5 checksum)

- Auxiliary Data (MD5 checksum)

- MAGE-TAB File (MD5 checksum)

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)
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