Mutation Analysis (MutSig v2.0 and MutSigCV v0.9 merged result)
Bladder Urothelial Carcinoma (Primary solid tumor)
16 April 2014  |  analyses__2014_04_16
Maintainer Information
Citation Information
doi:10.7908/C1QC023J
Maintained by Dan DiCara (Broad Institute)
Cite as Broad Institute TCGA Genome Data Analysis Center (2014): Mutation Analysis (MutSig v2.0 and MutSigCV v0.9 merged result). Broad Institute of MIT and Harvard. doi:10.7908/C1QC023J
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 v2.0 and MutSigCV v0.9 merged result was used to generate the results found in this report.

  • Working with individual set: BLCA-TP

  • Number of patients in set: 130

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:BLCA-TP.final_analysis_set.maf

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

  • Significantly mutated genes (q ≤ 0.1): 17

  • Mutations seen in COSMIC: 216

  • Significantly mutated genes in COSMIC territory: 10

  • Significantly mutated genesets: 21

Mutation Preprocessing

  • Read 130 MAFs of type "Broad"

  • Total number of mutations in input MAFs: 39312

  • After removing 613 blacklisted mutations: 38699

Mutation Filtering

  • Number of mutations before filtering: 38699

  • After removing 1 "impossible" mutations in

  • gene-patient-category bins of zero coverage: 38698

Results
Breakdown of Mutations by Type

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

type count
Frame_Shift_Del 512
Frame_Shift_Ins 219
In_Frame_Del 151
In_Frame_Ins 20
Missense_Mutation 24876
Nonsense_Mutation 2214
Nonstop_Mutation 47
Silent 10012
Splice_Site 590
Translation_Start_Site 58
Total 38699
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
Tp*C->(T/G) 14949 505003340 3e-05 30 3.9 3
Tp*C->A 1104 505003340 2.2e-06 2.2 0.29 4
(A/C/G)p*C->mut 5935 1437554646 4.1e-06 4.1 0.55 3.2
A->mut 2944 1865090498 1.6e-06 1.6 0.21 3.9
indel+null 3754 3807648484 9.9e-07 0.99 0.13 NaN
double_null 0 3807648484 0 0 0 NaN
Total 28686 3807648484 7.5e-06 7.5 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: BLCA-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: Tp*C->(T/G)

  • n2 = number of nonsilent mutations of type: Tp*C->A

  • n3 = number of nonsilent mutations of type: (A/C/G)p*C->mut

  • n4 = number of nonsilent mutations of type: A->mut

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

  • n6 = number of nonsilent mutations of type: double_null

  • p_cons = p-value for enrichment of mutations at evolutionarily most-conserved sites in gene

  • p_joint = p-value for clustering + conservation

  • 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: 17. 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_clust p_cons p_joint p_cv p q
1 PIK3CA phosphoinositide-3-kinase, catalytic, alpha polypeptide 423746 26 26 11 1 22 2 0 2 0 0 0 0.00012 0 3.4e-07 0 0
2 TP53 tumor protein p53 158975 75 64 50 1 19 0 34 4 18 0 0 0 0 5e-15 0 0
3 CDKN1A cyclin-dependent kinase inhibitor 1A (p21, Cip1) 63890 18 18 17 0 1 0 2 0 15 0 0.11 0.46 0.18 3.7e-15 2.4e-14 1.5e-10
4 RB1 retinoblastoma 1 (including osteosarcoma) 328495 19 17 17 0 2 1 0 1 15 0 0.36 0.72 0.51 1.9e-14 3.2e-13 1.4e-09
5 ARID1A AT rich interactive domain 1A (SWI-like) 760474 38 32 36 2 10 1 0 1 26 0 0.81 0.72 1 2.3e-14 7.4e-13 2.7e-09
6 MLL2 myeloid/lymphoid or mixed-lineage leukemia 2 1849473 40 36 40 5 10 0 3 2 25 0 0.58 0.46 0.79 9.7e-14 2.4e-12 7.2e-09
7 FBXW7 F-box and WD repeat domain containing 7 317856 16 13 12 0 4 0 5 1 6 0 0.000016 0.023 3e-05 7.4e-09 6.6e-12 1.7e-08
8 KDM6A lysine (K)-specific demethylase 6A 498061 32 31 26 2 2 0 2 0 28 0 0.22 0.098 0.2 2.1e-12 1.2e-11 2.8e-08
9 ELF3 E74-like factor 3 (ets domain transcription factor, epithelial-specific ) 147808 15 11 14 0 3 0 2 1 9 0 0.5 0.37 0.52 2.3e-10 2.8e-09 5.6e-06
10 FGFR3 fibroblast growth factor receptor 3 (achondroplasia, thanatophoric dwarfism) 249631 21 16 11 2 12 0 7 1 1 0 1e-06 0.12 5e-06 0.000061 7e-09 0.000013
11 FOXQ1 forkhead box Q1 48787 7 7 4 1 3 0 0 0 4 0 0.23 0.046 0.11 1.2e-08 2.8e-08 0.000046
12 STAG2 stromal antigen 2 504437 14 14 13 3 2 0 0 0 12 0 0.13 0.28 0.21 4.6e-08 1.9e-07 0.00029
13 NFE2L2 nuclear factor (erythroid-derived 2)-like 2 231964 12 11 9 0 7 0 2 3 0 0 0.0023 0.0052 0.0002 0.00051 1.7e-06 0.0024
14 CDKN2A cyclin-dependent kinase inhibitor 2A (melanoma, p16, inhibits CDK4) 96310 8 7 8 0 2 0 2 0 4 0 0.13 0.0002 0.00067 0.0044 0.000041 0.052
15 KLF5 Kruppel-like factor 5 (intestinal) 146260 11 10 10 2 5 1 2 0 3 0 0.75 0.056 0.21 0.000018 5e-05 0.06
16 ASXL2 additional sex combs like 2 (Drosophila) 550886 11 9 11 0 6 0 1 0 4 0 0.00072 0.0093 0.00028 0.015 0.000057 0.064
17 TSC1 tuberous sclerosis 1 463238 11 11 11 0 2 0 1 0 8 0 0.17 0.11 0.16 0.000034 0.000072 0.076
18 ERCC2 excision repair cross-complementing rodent repair deficiency, complementation group 2 (xeroderma pigmentosum D) 280493 16 16 13 2 4 1 4 7 0 0 0.42 0.019 0.073 0.00011 0.0001 0.1
19 TXNIP thioredoxin interacting protein 157040 12 9 12 2 3 1 2 1 5 0 0.23 0.034 0.11 0.000081 0.00011 0.11
20 EP300 E1A binding protein p300 955361 26 21 26 3 7 2 4 4 9 0 0.065 0.43 0.1 0.00015 0.00019 0.17
21 RXRA retinoid X receptor, alpha 181152 12 12 6 2 6 2 3 1 0 0 0.0059 0.029 0.0027 0.0067 0.00021 0.18
22 FOXA1 forkhead box A1 135106 7 7 7 1 2 0 0 0 5 0 0.45 0.25 0.44 0.000044 0.00023 0.19
23 PHLDA3 pleckstrin homology-like domain, family A, member 3 43621 4 4 3 1 2 0 1 0 1 0 0.014 0.18 0.014 0.0015 0.00025 0.2
24 ERBB3 v-erb-b2 erythroblastic leukemia viral oncogene homolog 3 (avian) 545990 14 14 10 1 5 2 5 2 0 0 0.0006 0.64 0.0018 0.017 0.00035 0.26
25 SCN10A sodium channel, voltage-gated, type X, alpha subunit 772958 7 4 7 2 3 1 0 1 2 0 0.000017 0.065 0.000048 1 0.00052 0.38
26 CX3CL1 chemokine (C-X3-C motif) ligand 1 156672 5 5 5 1 2 0 2 0 1 0 0.02 0.029 0.0044 0.016 0.00075 0.52
27 MIPOL1 mirror-image polydactyly 1 169688 7 7 6 1 5 0 0 0 2 0 0.035 0.23 0.048 0.0016 0.0008 0.53
28 ZFP36L1 zinc finger protein 36, C3H type-like 1 132732 6 6 6 0 0 0 1 2 3 0 0.18 0.81 0.3 0.0003 0.00093 0.6
29 MLL3 myeloid/lymphoid or mixed-lineage leukemia 3 1920318 30 27 30 3 13 1 4 2 10 0 0.42 0.2 0.34 0.00031 0.0011 0.68
30 KCNK2 potassium channel, subfamily K, member 2 174364 5 5 3 0 4 0 1 0 0 0 0.0027 1 0.0039 0.033 0.0013 0.77
31 E2F8 E2F transcription factor 8 343445 5 5 5 1 2 0 0 2 1 0 0.053 0.00024 0.001 0.15 0.0014 0.84
32 RARG retinoic acid receptor, gamma 177817 11 10 11 3 4 0 3 2 2 0 0.013 0.42 0.026 0.0057 0.0015 0.84
33 HORMAD1 HORMA domain containing 1 152773 7 7 7 1 3 1 0 0 3 0 0.43 0.82 0.58 0.00026 0.0015 0.84
34 MBD1 methyl-CpG binding domain protein 1 262475 6 6 6 0 1 0 0 1 4 0 0.048 0.067 0.032 0.0053 0.0016 0.87
35 SPTAN1 spectrin, alpha, non-erythrocytic 1 (alpha-fodrin) 966972 34 15 34 9 20 1 4 0 9 0 0.0001 0.26 0.00022 0.98 0.0021 1
PIK3CA

Figure S1.  This figure depicts the distribution of mutations and mutation types across the PIK3CA significant gene.

TP53

Figure S2.  This figure depicts the distribution of mutations and mutation types across the TP53 significant gene.

CDKN1A

Figure S3.  This figure depicts the distribution of mutations and mutation types across the CDKN1A significant gene.

RB1

Figure S4.  This figure depicts the distribution of mutations and mutation types across the RB1 significant gene.

ARID1A

Figure S5.  This figure depicts the distribution of mutations and mutation types across the ARID1A significant gene.

MLL2

Figure S6.  This figure depicts the distribution of mutations and mutation types across the MLL2 significant gene.

FBXW7

Figure S7.  This figure depicts the distribution of mutations and mutation types across the FBXW7 significant gene.

KDM6A

Figure S8.  This figure depicts the distribution of mutations and mutation types across the KDM6A significant gene.

ELF3

Figure S9.  This figure depicts the distribution of mutations and mutation types across the ELF3 significant gene.

FGFR3

Figure S10.  This figure depicts the distribution of mutations and mutation types across the FGFR3 significant gene.

FOXQ1

Figure S11.  This figure depicts the distribution of mutations and mutation types across the FOXQ1 significant gene.

STAG2

Figure S12.  This figure depicts the distribution of mutations and mutation types across the STAG2 significant gene.

NFE2L2

Figure S13.  This figure depicts the distribution of mutations and mutation types across the NFE2L2 significant gene.

CDKN2A

Figure S14.  This figure depicts the distribution of mutations and mutation types across the CDKN2A significant gene.

KLF5

Figure S15.  This figure depicts the distribution of mutations and mutation types across the KLF5 significant gene.

ASXL2

Figure S16.  This figure depicts the distribution of mutations and mutation types across the ASXL2 significant gene.

TSC1

Figure S17.  This figure depicts the distribution of mutations and mutation types across the TSC1 significant gene.

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: 10. Number of genes displayed: 10

rank gene description n cos n_cos N_cos cos_ev p q
1 FGFR3 fibroblast growth factor receptor 3 (achondroplasia, thanatophoric dwarfism) 21 62 15 8060 10223 0 0
2 TP53 tumor protein p53 75 356 72 46280 19158 0 0
3 PIK3CA phosphoinositide-3-kinase, catalytic, alpha polypeptide 26 220 21 28600 10307 0 0
4 FBXW7 F-box and WD repeat domain containing 7 16 91 8 11830 176 0 0
5 RB1 retinoblastoma 1 (including osteosarcoma) 19 267 10 34710 38 1.9e-14 1.7e-11
6 ERBB2 v-erb-b2 erythroblastic leukemia viral oncogene homolog 2, neuro/glioblastoma derived oncogene homolog (avian) 11 42 5 5460 16 9.5e-10 7.1e-07
7 CDKN2A cyclin-dependent kinase inhibitor 2A (melanoma, p16, inhibits CDK4) 8 332 8 43160 214 2.3e-09 1.5e-06
8 HRAS v-Ha-ras Harvey rat sarcoma viral oncogene homolog 6 19 4 2470 1325 4.9e-09 2.8e-06
9 ATM ataxia telangiectasia mutated 19 245 7 31850 11 7.4e-09 3.7e-06
10 ERBB3 v-erb-b2 erythroblastic leukemia viral oncogene homolog 3 (avian) 14 6 3 780 3 3.4e-08 0.000015

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: 21. 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 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(18), DAXX(1), HRAS(6), PAX3(4), PML(3), RARA(3), RB1(19), SIRT1(1), SP100(6), TNFRSF1B(3), TP53(75) 3649856 139 81 109 8 41 1 51 7 39 0 2.1e-08 <1.00e-15 <3.08e-13
2 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 ARF3(1), CCND1(1), CDK2(1), CDK4(2), CDKN1A(18), CDKN1B(5), CDKN2A(8), E2F1(1), E2F2(1), PRB1(1), TP53(75) 1619397 114 76 88 5 28 0 39 5 42 0 2.5e-07 <1.00e-15 <3.08e-13
3 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 HDAC1(1), MYC(1), SP1(3), SP3(2), TP53(75), WT1(2) 1363520 84 68 59 4 23 1 34 5 21 0 8.7e-06 3.77e-15 7.75e-13
4 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), HSPA1A(2), IFNG(1), IFNGR2(2), IKBKB(4), JAK2(2), NFKB1(1), NFKBIA(2), RB1(19), RELA(2), TNFRSF1B(3), TP53(75), USH1C(1), WT1(2) 3492287 117 73 90 6 33 2 40 5 37 0 1.3e-07 5.11e-15 7.86e-13
5 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(6), DNAJC3(2), MAP3K14(2), NFKB1(1), NFKBIA(2), RELA(2), TP53(75) 1894134 90 67 65 4 27 0 36 4 23 0 5e-06 8.44e-15 1.04e-12
6 FBW7PATHWAY Cyclin E interacts with cell cycle checkpoint kinase cdk2 to allow transcription of genes required for S phase, including transcription of additional cyclin E. CCNE1, CDC34, CDK2, CUL1, E2F1, FBXW7, RB1, SKP1A, TFDP1 8 CDK2(1), CUL1(8), E2F1(1), FBXW7(16), RB1(19) 1585537 45 36 38 1 14 1 6 2 22 0 0.0004 1.35e-13 1.38e-11
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(1), ATM(19), BAX(1), CCND1(1), CDK2(1), CDK4(2), CDKN1A(18), E2F1(1), GADD45A(1), PCNA(1), RB1(19), TP53(75) 3493410 140 87 112 12 36 2 41 8 53 0 0.00029 1.65e-12 1.45e-10
8 CELLCYCLEPATHWAY Cyclins interact with cyclin-dependent kinases to form active kinase complexes that regulate progression through the cell cycle. CCNA1, CCNB1, CCND1, CCND2, CCND3, CCNE1, CCNH, CDC2, CDC25A, CDK2, CDK4, CDK6, CDK7, CDKN1A, CDKN1B, CDKN2A, CDKN2B, CDKN2C, CDKN2D, E2F1, RB1, RBL1, TFDP1 22 CCNA1(1), CCNB1(1), CCND1(1), CCND3(5), CCNH(3), CDC25A(1), CDK2(1), CDK4(2), CDK6(1), CDK7(3), CDKN1A(18), CDKN1B(5), CDKN2A(8), CDKN2B(2), CDKN2D(1), E2F1(1), RB1(19), RBL1(1) 3072916 74 51 71 5 19 2 10 3 40 0 0.0021 5.47e-12 4.21e-10
9 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(4), CDKN2A(8), E2F1(1), MYC(1), PIK3CA(26), PIK3R1(2), POLR1A(5), POLR1B(1), POLR1C(1), POLR1D(2), RAC1(1), RB1(19), TBX2(3), TP53(75) 3902579 149 79 107 12 57 4 40 9 39 0 8e-07 8.37e-12 5.73e-10
10 RACCYCDPATHWAY Ras, Rac, and Rho coordinate to induce cyclin D1 expression and activate cdk2 to promote the G1/S transition. AKT1, ARHA, CCND1, CCNE1, CDK2, CDK4, CDK6, CDKN1A, CDKN1B, E2F1, HRAS, MAPK1, MAPK3, NFKB1, NFKBIA, PAK1, PIK3CA, PIK3R1, RAC1, RAF1, RB1, RELA, TFDP1 22 CCND1(1), CDK2(1), CDK4(2), CDK6(1), CDKN1A(18), CDKN1B(5), E2F1(1), HRAS(6), MAPK3(3), NFKB1(1), NFKBIA(2), PIK3CA(26), PIK3R1(2), RAC1(1), RAF1(1), RB1(19), RELA(2) 3908128 92 64 73 8 40 3 9 5 35 0 0.001 1.05e-09 6.45e-08
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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