Mutation Analysis (MutSig v1.5)
Liver Hepatocellular Carcinoma (Primary solid tumor)
15 July 2014  |  analyses__2014_07_15
Maintainer Information
Citation Information
doi:10.7908/C1NS0SNX
Maintained by David Heiman (Broad Institute)
Cite as Broad Institute TCGA Genome Data Analysis Center (2014): Mutation Analysis (MutSig v1.5). Broad Institute of MIT and Harvard. doi:10.7908/C1NS0SNX
Overview
Introduction

This report serves to describe the mutational landscape and properties of a given individual set, as well as rank genes and genesets according to mutational significance. MutSig v1.5 was used to generate the results found in this report.

  • Working with individual set: LIHC-TP

  • Number of patients in set: 201

Input

The input for this pipeline is a set of individuals with the following files associated for each:

  1. An annotated .maf file describing the mutations called for the respective individual, and their properties.

  2. A .wig file that contains information about the coverage of the sample.

Summary

  • MAF used for this analysis:LIHC-TP.final_analysis_set.maf

  • Blacklist used for this analysis: pancan_mutation_blacklist.v14.hg19.txt

  • Significantly mutated genes (q ≤ 0.1): 26

  • Mutations seen in COSMIC: 241

  • Significantly mutated genes in COSMIC territory: 11

  • Significantly mutated genesets: 8

  • Significantly mutated genesets: (excluding sig. mutated genes):0

Mutation Preprocessing

  • Read 202 MAFs of type "Baylor-Illumina"

  • Total number of mutations in input MAFs: 92840

  • After removing 249 mutations outside chr1-24: 92591

  • After removing 1740 blacklisted mutations: 90851

  • After removing 2200 noncoding mutations: 88651

  • After collapsing adjacent/redundant mutations: 88627

Mutation Filtering

  • Number of mutations before filtering: 88627

  • After removing 936 mutations outside patient set: 87691

  • After removing 4112 mutations outside gene set: 83579

  • After removing 286 mutations outside category set: 83293

  • After removing 2 "impossible" mutations in

  • gene-patient-category bins of zero coverage: 77957

Results
Breakdown of Mutations by Type

Table 1.  Get Full Table Table representing breakdown of mutations by type.

type count
Frame_Shift_Del 4324
Frame_Shift_Ins 470
In_Frame_Del 221
In_Frame_Ins 61
Missense_Mutation 49353
Nonsense_Mutation 1474
Silent 25876
Splice_Site 1511
Translation_Start_Site 3
Total 83293
Breakdown of Mutation Rates by Category Type

Table 2.  Get Full Table A breakdown of mutation rates per category discovered for this individual set.

category n N rate rate_per_mb relative_rate exp_ns_s_ratio
*NpG->transit 12488 1314361881 9.5e-06 9.5 1 2.1
*Ap(A/C/T)->G 13012 2111425726 6.2e-06 6.2 0.67 2.4
*Cp(A/C/T)->T 6755 2858728767 2.4e-06 2.4 0.26 1.7
transver 17100 6284516374 2.7e-06 2.7 0.3 5
indel+null 7795 6284516374 1.2e-06 1.2 0.14 NaN
double_null 267 6284516374 4.2e-08 0.042 0.0047 NaN
Total 57417 6284516374 9.1e-06 9.1 1 3.5
Target Coverage for Each Individual

The x axis represents the samples. The y axis represents the exons, one row per exon, and they are sorted by average coverage across samples. For exons with exactly the same average coverage, they are sorted next by the %GC of the exon. (The secondary sort is especially useful for the zero-coverage exons at the bottom). If the figure is unpopulated, then full coverage is assumed (e.g. MutSig CV doesn't use WIGs and assumes full coverage).

Figure 1. 

Distribution of Mutation Counts, Coverage, and Mutation Rates Across Samples

Figure 2.  Patients counts and rates file used to generate this plot: LIHC-TP.patients.counts_and_rates.txt

Lego Plots

The mutation spectrum is depicted in the lego plots below in which the 96 possible mutation types are subdivided into six large blocks, color-coded to reflect the base substitution type. Each large block is further subdivided into the 16 possible pairs of 5' and 3' neighbors, as listed in the 4x4 trinucleotide context legend. The height of each block corresponds to the mutation frequency for that kind of mutation (counts of mutations normalized by the base coverage in a given bin). The shape of the spectrum is a signature for dominant mutational mechanisms in different tumor types.

Figure 3.  Get High-res Image SNV Mutation rate lego plot for entire set. Each bin is normalized by base coverage for that bin. Colors represent the six SNV types on the upper right. The three-base context for each mutation is labeled in the 4x4 legend on the lower right. The fractional breakdown of SNV counts is shown in the pie chart on the upper left. If this figure is blank, not enough information was provided in the MAF to generate it.

Figure 4.  Get High-res Image SNV Mutation rate lego plots for 4 slices of mutation allele fraction (0<=AF<0.1, 0.1<=AF<0.25, 0.25<=AF<0.5, & 0.5<=AF) . The color code and three-base context legends are the same as the previous figure. If this figure is blank, not enough information was provided in the MAF to generate it.

CoMut Plot

Figure 5.  Get High-res Image The matrix in the center of the figure represents individual mutations in patient samples, color-coded by type of mutation, for the significantly mutated genes. The rate of synonymous and non-synonymous mutations is displayed at the top of the matrix. The barplot on the left of the matrix shows the number of mutations in each gene. The percentages represent the fraction of tumors with at least one mutation in the specified gene. The barplot to the right of the matrix displays the q-values for the most significantly mutated genes. The purple boxplots below the matrix (only displayed if required columns are present in the provided MAF) represent the distributions of allelic fractions observed in each sample. The plot at the bottom represents the base substitution distribution of individual samples, using the same categories that were used to calculate significance.

Significantly Mutated Genes

Column Descriptions:

  • N = number of sequenced bases in this gene across the individual set

  • n = number of (nonsilent) mutations in this gene across the individual set

  • npat = number of patients (individuals) with at least one nonsilent mutation

  • nsite = number of unique sites having a non-silent mutation

  • nsil = number of silent mutations in this gene across the individual set

  • n1 = number of nonsilent mutations of type: *NpG->transit

  • n2 = number of nonsilent mutations of type: *Ap(A/C/T)->G

  • n3 = number of nonsilent mutations of type: *Cp(A/C/T)->T

  • n4 = number of nonsilent mutations of type: transver

  • n5 = number of nonsilent mutations of type: indel+null

  • n6 = number of nonsilent mutations of type: double_null

  • p_ns_s = p-value for the observed nonsilent/silent ratio being elevated in this gene

  • p = p-value (overall)

  • q = q-value, False Discovery Rate (Benjamini-Hochberg procedure)

Table 3.  Get Full Table A Ranked List of Significantly Mutated Genes. Number of significant genes found: 26. Number of genes displayed: 35. Click on a gene name to display its stick figure depicting the distribution of mutations and mutation types across the chosen gene (this feature may not be available for all significant genes).

rank gene description N n npat nsite nsil n1 n2 n3 n4 n5 n6 p_ns_s p q
1 CTNNB1 catenin (cadherin-associated protein), beta 1, 88kDa 481249 59 56 28 2 5 8 8 34 3 1 0.000015 1.4e-15 2.7e-11
2 TP53 tumor protein p53 254743 67 65 53 2 8 7 7 22 23 0 6.3e-06 4.9e-15 4.6e-11
3 ALB albumin 377398 24 24 24 3 0 4 2 5 10 3 0.41 2.2e-14 1.4e-10
4 BAGE3 B melanoma antigen family, member 3 48415 8 8 3 0 7 0 1 0 0 0 0.046 1e-11 4.8e-08
5 LCE4A late cornified envelope 4A 60940 9 9 3 1 0 0 1 8 0 0 0.45 5e-10 1.9e-06
6 RB1 retinoblastoma 1 (including osteosarcoma) 529857 19 18 19 1 1 1 0 3 13 1 0.2 1.5e-09 4.8e-06
7 POTEG POTE ankyrin domain family, member G 307096 14 13 10 1 7 0 2 2 3 0 0.074 3e-07 0.00071
8 KIAA0040 KIAA0040 61104 8 6 5 0 0 0 3 3 2 0 0.092 3e-07 0.00071
9 PTEN phosphatase and tensin homolog (mutated in multiple advanced cancers 1) 242698 11 11 11 1 0 1 2 2 5 1 0.46 5.4e-07 0.0011
10 OR2T4 olfactory receptor, family 2, subfamily T, member 4 211163 20 14 8 4 6 8 2 4 0 0 0.2 4.3e-06 0.008
11 BAP1 BRCA1 associated protein-1 (ubiquitin carboxy-terminal hydrolase) 444656 12 12 12 1 0 0 0 3 9 0 0.43 5.6e-06 0.0095
12 EEF1A1 eukaryotic translation elongation factor 1 alpha 1 224980 10 9 6 1 0 3 5 2 0 0 0.13 7e-06 0.011
13 PPIAL4G peptidylprolyl isomerase A (cyclophilin A)-like 4G 88420 9 7 3 0 1 7 1 0 0 0 0.045 8.5e-06 0.012
14 GPATCH4 G patch domain containing 4 223129 10 10 1 1 0 0 0 10 0 0 0.52 0.000011 0.014
15 FAM104B family with sequence similarity 104, member B 66477 5 5 4 1 0 1 1 0 3 0 0.41 0.000016 0.02
16 ZNF676 zinc finger protein 676 330539 14 12 13 0 0 3 4 5 2 0 0.038 0.000025 0.029
17 OR2J3 olfactory receptor, family 2, subfamily J, member 3 188727 10 9 8 0 4 1 1 4 0 0 0.035 0.000029 0.032
18 HOXA4 homeobox A4 92992 6 6 3 0 4 0 1 0 1 0 0.16 0.000034 0.036
19 HTR7 5-hydroxytryptamine (serotonin) receptor 7 (adenylate cyclase-coupled) 261673 10 10 10 1 3 4 0 1 2 0 0.25 0.000036 0.036
20 TRIM41 tripartite motif-containing 41 362704 14 14 13 0 3 2 3 3 3 0 0.028 0.000038 0.036
21 KIF19 kinesin family member 19 509360 15 14 15 1 7 1 1 4 2 0 0.12 0.000053 0.047
22 LILRA2 leukocyte immunoglobulin-like receptor, subfamily A (with TM domain), member 2 296455 11 11 9 0 2 1 1 6 1 0 0.066 0.000061 0.052
23 AXIN1 axin 1 444607 14 12 14 2 1 0 0 3 10 0 0.54 0.000066 0.054
24 BCLAF1 BCL2-associated transcription factor 1 555001 14 14 12 1 1 0 2 8 3 0 0.18 0.0001 0.08
25 ARID1A AT rich interactive domain 1A (SWI-like) 1161244 25 25 23 4 1 3 0 4 16 1 0.56 0.00011 0.08
26 LCE1F late cornified envelope 1F 70083 4 4 4 0 0 2 0 2 0 0 0.37 0.00013 0.091
27 PRH2 proline-rich protein HaeIII subfamily 2 103113 6 6 3 0 0 3 1 2 0 0 0.075 0.00018 0.11
28 TLX3 T-cell leukemia homeobox 3 125600 6 6 6 0 0 1 0 3 2 0 0.23 0.00018 0.11
29 HNF1A HNF1 homeobox A 364300 13 9 13 0 3 1 1 4 3 1 0.046 0.00018 0.11
30 OR2M7 olfactory receptor, family 2, subfamily M, member 7 189342 10 8 10 0 2 2 0 6 0 0 0.084 0.00018 0.11
31 BBS9 Bardet-Biedl syndrome 9 547586 14 14 14 1 3 6 0 1 4 0 0.022 0.00024 0.13
32 KRTAP5-11 keratin associated protein 5-11 94785 5 5 3 0 1 0 0 0 4 0 0.87 0.00025 0.13
33 CSAG1 chondrosarcoma associated gene 1 50049 4 4 3 0 0 2 0 2 0 0 0.31 0.00025 0.13
34 LRRC69 leucine rich repeat containing 69 205719 7 7 6 1 0 3 3 0 1 0 0.2 0.00025 0.13
35 CDKN1A cyclin-dependent kinase inhibitor 1A (p21, Cip1) 89050 6 5 6 0 0 0 0 5 1 0 0.32 0.00026 0.13
COSMIC analyses

In this analysis, COSMIC is used as a filter to increase power by restricting the territory of each gene. Cosmic version: v48.

Table 4.  Get Full Table Significantly mutated genes (COSMIC territory only). To access the database please go to: COSMIC. Number of significant genes found: 11. Number of genes displayed: 10

rank gene description n cos n_cos N_cos cos_ev p q
1 CTNNB1 catenin (cadherin-associated protein), beta 1, 88kDa 59 138 46 27738 12418 0 0
2 TP53 tumor protein p53 67 356 60 71556 10416 0 0
3 RB1 retinoblastoma 1 (including osteosarcoma) 19 267 13 53667 23 0 0
4 IDH1 isocitrate dehydrogenase 1 (NADP+), soluble 7 5 4 1005 4479 2.9e-10 3.3e-07
5 PTEN phosphatase and tensin homolog (mutated in multiple advanced cancers 1) 11 767 11 154167 93 3e-07 0.00026
6 GNAS GNAS complex locus 9 7 3 1407 630 3.5e-07 0.00026
7 CYLC1 cylicin, basic protein of sperm head cytoskeleton 1 12 1 2 201 2 1.7e-06 0.0011
8 KDR kinase insert domain receptor (a type III receptor tyrosine kinase) 13 16 3 3216 3 4.1e-06 0.0023
9 IDH2 isocitrate dehydrogenase 2 (NADP+), mitochondrial 5 6 2 1206 166 6e-05 0.029
10 PIK3CA phosphoinositide-3-kinase, catalytic, alpha polypeptide 10 220 5 44220 2949 0.000064 0.029

Note:

n - number of (nonsilent) mutations in this gene across the individual set.

cos = number of unique mutated sites in this gene in COSMIC

n_cos = overlap between n and cos.

N_cos = number of individuals times cos.

cos_ev = total evidence: number of reports in COSMIC for mutations seen in this gene.

p = p-value for seeing the observed amount of overlap in this gene)

q = q-value, False Discovery Rate (Benjamini-Hochberg procedure)

Geneset Analyses

Table 5.  Get Full Table A Ranked List of Significantly Mutated Genesets. (Source: MSigDB GSEA Cannonical Pathway Set).Number of significant genesets found: 8. Number of genesets displayed: 10

rank geneset description genes N_genes mut_tally N n npat nsite nsil n1 n2 n3 n4 n5 n6 p_ns_s p q
1 SA_G1_AND_S_PHASES Cdk2, 4, and 6 bind cyclin D in G1, while cdk2/cyclin E promotes the G1/S transition. ARF1, ARF3, CCND1, CDK2, CDK4, CDKN1A, CDKN1B, CDKN2A, CFL1, E2F1, E2F2, MDM2, NXT1, PRB1, TP53 15 ARF1(2), ARF3(1), CCND1(1), CDKN1A(6), CDKN1B(2), CDKN2A(3), CFL1(3), E2F1(2), MDM2(2), PRB1(2), TP53(67) 2450400 91 77 77 10 14 8 7 33 29 0 0.0011 3.3e-15 2e-12
2 TERTPATHWAY hTERC, the RNA subunit of telomerase, and hTERT, the catalytic protein subunit, are required for telomerase activity and are overexpressed in many cancers. HDAC1, MAX, MYC, SP1, SP3, TP53, WT1, ZNF42 7 MYC(2), SP1(2), SP3(3), TP53(67), WT1(6) 2114891 80 74 66 7 12 11 8 25 24 0 0.00016 7.9e-15 2.4e-12
3 RNAPATHWAY dsRNA-activated protein kinase phosphorylates elF2a, which generally inhibits translation, and activates NF-kB to provoke inflammation. CHUK, DNAJC3, EIF2S1, EIF2S2, MAP3K14, NFKB1, NFKBIA, PRKR, RELA, TP53 9 CHUK(9), DNAJC3(3), EIF2S1(1), EIF2S2(1), MAP3K14(2), NFKB1(7), NFKBIA(2), RELA(4), TP53(67) 3064238 96 82 82 16 13 11 12 30 30 0 0.011 5e-08 1e-05
4 RBPATHWAY The ATM protein kinase recognizes DNA damage and blocks cell cycle progression by phosphorylating chk1 and p53, which normally inhibits Rb to allow G1/S transitions. ATM, CDC2, CDC25A, CDC25B, CDC25C, CDK2, CDK4, CHEK1, MYT1, RB1, TP53, WEE1, YWHAH 12 ATM(15), CDC25A(2), CDC25B(4), CDC25C(1), CHEK1(7), MYT1(6), RB1(19), TP53(67), WEE1(4), YWHAH(1) 5295129 126 97 112 21 17 16 9 42 41 1 0.016 3.4e-06 0.00052
5 PMLPATHWAY Ring-shaped PML nuclear bodies regulate transcription and are required co-activators in p53- and DAXX-mediated apoptosis. CREBBP, DAXX, HRAS, PAX3, PML, PRAM-1, RARA, RB1, SIRT1, SP100, TNF, TNFRSF1A, TNFRSF1B, TNFRSF6, TNFSF6, TP53, UBL1 13 CREBBP(12), DAXX(1), PAX3(6), PML(5), RARA(2), RB1(19), SIRT1(5), SP100(3), TNF(2), TNFRSF1A(2), TNFRSF1B(3), TP53(67) 5618548 127 95 113 21 16 25 12 35 38 1 0.0077 0.000023 0.0028
6 TIDPATHWAY On ligand binding, interferon gamma receptors stimulate JAK2 kinase to phosphorylate STAT transcription factors, which promote expression of interferon responsive genes. DNAJA3, HSPA1A, IFNG, IFNGR1, IFNGR2, IKBKB, JAK2, LIN7A, NFKB1, NFKBIA, RB1, RELA, TIP-1, TNF, TNFRSF1A, TNFRSF1B, TP53, USH1C, WT1 18 DNAJA3(1), IFNG(3), IFNGR1(5), IFNGR2(2), IKBKB(6), JAK2(9), LIN7A(1), NFKB1(7), NFKBIA(2), RB1(19), RELA(4), TNF(2), TNFRSF1A(2), TNFRSF1B(3), TP53(67), USH1C(5), WT1(6) 5765477 144 100 130 23 22 21 14 44 42 1 0.0033 0.000094 0.0096
7 P53PATHWAY p53 induces cell cycle arrest or apoptosis under conditions of DNA damage. APAF1, ATM, BAX, BCL2, CCND1, CCNE1, CDK2, CDK4, CDKN1A, E2F1, GADD45A, MDM2, PCNA, RB1, TIMP3, TP53 16 APAF1(10), ATM(15), BAX(1), BCL2(1), CCND1(1), CCNE1(2), CDKN1A(6), E2F1(2), GADD45A(1), MDM2(2), RB1(19), TP53(67) 5400786 127 92 113 22 16 13 9 47 41 1 0.025 0.00017 0.015
8 ARFPATHWAY Cyclin-dependent kinase inhibitor 2A is a tumor suppressor that induces G1 arrest and can activate the p53 pathway, leading to G2/M arrest. ABL1, CDKN2A, E2F1, MDM2, MYC, PIK3CA, PIK3R1, POLR1A, POLR1B, POLR1C, POLR1D, RAC1, RB1, TBX2, TP53, TWIST1 16 ABL1(1), CDKN2A(3), E2F1(2), MDM2(2), MYC(2), PIK3CA(10), PIK3R1(5), POLR1A(10), POLR1B(3), POLR1C(1), POLR1D(1), RAC1(1), RB1(19), TBX2(4), TP53(67) 5956904 131 97 115 23 17 17 12 41 43 1 0.022 0.00039 0.03
9 PLK3PATHWAY Active Plk3 phosphorylates CDC25c, blocking the G2/M transition, and phosphorylates p53 to induce apoptosis. ATM, ATR, CDC25C, CHEK1, CHEK2, CNK, TP53, YWHAH 7 ATM(15), ATR(14), CDC25C(1), CHEK1(7), CHEK2(6), TP53(67), YWHAH(1) 4722879 111 86 97 21 17 13 10 40 30 1 0.031 0.0065 0.44
10 FOSBPATHWAY FOSB gene expression and drug abuse CDK5, FOSB, GRIA2, JUND, PPP1R1B 5 CDK5(1), FOSB(1), GRIA2(10), JUND(2), PPP1R1B(2) 1119909 16 15 16 1 5 4 2 3 2 0 0.045 0.01 0.62

Table 6.  Get Full Table A Ranked List of Significantly Mutated Genesets (Excluding Significantly Mutated Genes). Number of significant genesets found: 0. Number of genesets displayed: 10

rank geneset description genes N_genes mut_tally N n npat nsite nsil n1 n2 n3 n4 n5 n6 p_ns_s p q
1 FOSBPATHWAY FOSB gene expression and drug abuse CDK5, FOSB, GRIA2, JUND, PPP1R1B 5 CDK5(1), FOSB(1), GRIA2(10), JUND(2), PPP1R1B(2) 1119909 16 15 16 1 5 4 2 3 2 0 0.045 0.01 1
2 HSA00472_D_ARGININE_AND_D_ORNITHINE_METABOLISM Genes involved in D-arginine and D-ornithine metabolism DAO 1 DAO(7) 210646 7 7 7 2 1 2 1 3 0 0 0.62 0.02 1
3 STILBENE_COUMARINE_AND_LIGNIN_BIOSYNTHESIS EPX, GBA3, LPO, MPO, PRDX1, PRDX2, PRDX5, PRDX6, TPO, TYR 10 EPX(8), LPO(8), MPO(11), PRDX1(1), PRDX2(2), PRDX5(3), PRDX6(1), TPO(11), TYR(6) 2928607 51 43 51 9 11 8 9 15 8 0 0.031 0.19 1
4 HSA00627_1,4_DICHLOROBENZENE_DEGRADATION Genes involved in 1,4-dichlorobenzene degradation CMBL 1 CMBL(2) 151093 2 2 2 1 0 0 0 1 1 0 0.94 0.36 1
5 ARENRF2PATHWAY Nrf1 and nrf2 are transcription factors that bind to antioxidant response elements (AREs), promoters of genes involved in oxidative damage control. CREB1, FOS, FXYD2, JUN, KEAP1, MAFF, MAFG, MAFK, MAPK1, MAPK14, MAPK8, NFE2L2, PRKCA, PRKCB1 13 CREB1(1), FOS(2), JUN(1), KEAP1(9), MAFG(1), MAPK1(3), MAPK14(4), NFE2L2(5), PRKCA(2) 2741845 28 25 28 3 5 5 4 9 5 0 0.062 0.38 1
6 HSA00031_INOSITOL_METABOLISM Genes involved in inositol metabolism ALDH6A1, TPI1 2 ALDH6A1(6) 501887 6 5 6 0 1 1 2 1 1 0 0.12 0.45 1
7 METHIONINEPATHWAY Catabolic Pathways for Methionine, Isoleucine, Threonine and Valine BCKDHB, BCKDK, CBS, CTH, MUT 5 BCKDHB(2), BCKDK(3), CBS(5), CTH(3), MUT(4) 1474395 17 14 17 2 3 4 0 3 7 0 0.2 0.49 1
8 HSA00471_D_GLUTAMINE_AND_D_GLUTAMATE_METABOLISM Genes involved in D-glutamine and D-glutamate metabolism GLS, GLS2, GLUD1, GLUD2 4 GLS(4), GLS2(3), GLUD1(3), GLUD2(3) 1320815 13 13 13 2 1 6 3 1 2 0 0.21 0.56 1
9 HSA00550_PEPTIDOGLYCAN_BIOSYNTHESIS Genes involved in peptidoglycan biosynthesis GLUL, PGLYRP2 2 GLUL(3), PGLYRP2(1) 518233 4 4 4 1 0 2 0 1 1 0 0.75 0.61 1
10 HSA00940_PHENYLPROPANOID_BIOSYNTHESIS Genes involved in phenylpropanoid biosynthesis EPX, GBA, GBA3, LPO, MPO, PRDX6, TPO 7 EPX(8), GBA(1), LPO(8), MPO(11), PRDX6(1), TPO(11) 2527768 40 34 40 9 10 7 8 10 5 0 0.11 0.64 1
Methods & Data
Methods

In brief, we tabulate the number of mutations and the number of covered bases for each gene. The counts are broken down by mutation context category: four context categories that are discovered by MutSig, and one for indel and 'null' mutations, which include indels, nonsense mutations, splice-site mutations, and non-stop (read-through) mutations. For each gene, we calculate the probability of seeing the observed constellation of mutations, i.e. the product P1 x P2 x ... x Pm, or a more extreme one, given the background mutation rates calculated across the dataset. [1]

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] TCGA, Integrated genomic analyses of ovarian carcinoma, Nature 474:609 - 615 (2011)
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