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

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:

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.
Lists pathways significantly enriched in each phenotype subtype and their enrichment scores (ES).
Lists top 20 core genes enriched in each significant gene set and their enrichment scores (ES).
Checks if the top core genes are up-regulated or down-regulated.
Checks if the top core genes are high expressed or low expressed.
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.

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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