Mutation Analysis (MutSig v2.0 and MutSigCV v0.9 merged result)
Pancreatic Adenocarcinoma (Primary solid tumor)
Due to issues with GAF 3.0, we strongly advise caution in the use of these results.
23 September 2013  |  analyses__2013_09_23
Maintainer Information
Citation Information
doi:10.7908/C1TB157J
Maintained by Dan DiCara (Broad Institute)
Cite as Broad Institute TCGA Genome Data Analysis Center (2013): Mutation Analysis (MutSig v2.0 and MutSigCV v0.9 merged result). Broad Institute of MIT and Harvard. doi:10.7908/C1TB157J
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: PAAD-TP

  • Number of patients in set: 57

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:PAAD-TP.final_analysis_set.maf

  • Significantly mutated genes (q ≤ 0.1): 408

  • Mutations seen in COSMIC: 148

  • Significantly mutated genes in COSMIC territory: 10

  • Significantly mutated genesets: 20

Mutation Preprocessing

  • Read 57 MAFs of type "Broad"

  • Total number of mutations in input MAFs: 27745

  • After removing 95 mutations outside chr1-24: 27650

  • After removing 630 noncoding mutations: 27020

  • After collapsing adjacent/redundant mutations: 26916

Mutation Filtering

  • Number of mutations before filtering: 26916

  • After removing 1108 mutations outside gene set: 25808

  • After removing 158 mutations outside category set: 25650

  • After removing 2 "impossible" mutations in

  • gene-patient-category bins of zero coverage: 24382

Results
Breakdown of Mutations by Type

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

type count
Frame_Shift_Del 1629
Frame_Shift_Ins 529
In_Frame_Del 2155
In_Frame_Ins 48
Missense_Mutation 13980
Nonsense_Mutation 870
Nonstop_Mutation 5
Silent 5585
Splice_Site 839
Translation_Start_Site 10
Total 25650
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
*CpG->T 4336 98986159 0.000044 44 3.8 2.1
*Cp(A/C/T)->T 3471 788202097 4.4e-06 4.4 0.38 1.7
C->(G/A) 3395 887188256 3.8e-06 3.8 0.33 4.7
A->mut 2777 841595742 3.3e-06 3.3 0.28 3.9
indel+null 5939 1728783998 3.4e-06 3.4 0.3 NaN
double_null 145 1728783998 8.4e-08 0.084 0.0072 NaN
Total 20063 1728783998 0.000012 12 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).

Figure 1. 

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

Figure 2.  Patients counts and rates file used to generate this plot: PAAD-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: *CpG->T

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

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

  • 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: 408. 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 HAMP hepcidin antimicrobial peptide 15219 8 8 1 0 0 0 0 0 8 0 0 0.26 0 7.7e-15 0 0
2 C15orf24 chromosome 15 open reading frame 24 42615 6 6 1 0 0 0 0 0 6 0 0 1 0 7.5e-08 0 0
3 CTCFL CCCTC-binding factor (zinc finger protein)-like 115822 5 5 1 0 0 0 0 0 5 0 0 0.92 0 0.000092 0 0
4 FOXN3 forkhead box N3 85125 11 11 1 0 0 0 0 0 11 0 0 0.3 0 1.4e-08 0 0
5 NOS1AP nitric oxide synthase 1 (neuronal) adaptor protein 90538 12 12 2 0 1 0 0 0 11 0 0 0.21 0 1.9e-14 0 0
6 MCL1 myeloid cell leukemia sequence 1 (BCL2-related) 55039 5 5 1 1 0 0 0 0 5 0 0 0.35 0 7.1e-07 0 0
7 TMEM127 transmembrane protein 127 34924 6 6 1 0 0 0 0 0 6 0 0 0.038 0 3.7e-09 0 0
8 NUFIP2 nuclear fragile X mental retardation protein interacting protein 2 119888 8 8 2 0 0 0 0 0 8 0 0 0.95 0 1.3e-09 0 0
9 NUDT11 nudix (nucleoside diphosphate linked moiety X)-type motif 11 27859 5 5 1 0 0 0 0 0 5 0 0 0.99 0 1 0 0
10 PAPD7 PAP associated domain containing 7 95571 5 5 1 1 0 0 0 0 5 0 0 0.99 0 0.000084 0 0
11 HAUS8 HAUS augmin-like complex, subunit 8 72585 6 6 1 0 0 0 0 0 6 0 0 0.88 0 8.1e-06 0 0
12 KRT10 keratin 10 (epidermolytic hyperkeratosis; keratosis palmaris et plantaris) 90106 7 7 2 0 0 0 0 0 7 0 0 1 0 3.1e-08 0 0
13 FUZ fuzzy homolog (Drosophila) 51398 11 11 1 0 0 0 0 0 11 0 0 0.99 0 6.2e-15 0 0
14 BIK BCL2-interacting killer (apoptosis-inducing) 23285 5 5 1 0 0 0 0 0 5 0 0 0.046 0 6.4e-09 0 0
15 SGOL1 shugoshin-like 1 (S. pombe) 97844 5 5 2 0 0 0 0 0 5 0 0 1 0 0.000035 0 0
16 TCF20 transcription factor 20 (AR1) 337013 24 16 7 3 0 1 1 0 22 0 8e-07 0.98 9e-06 1e-14 0 0
17 LRP10 low density lipoprotein receptor-related protein 10 123645 10 10 2 1 0 0 1 0 9 0 0 0.98 0 2.5e-09 0 0
18 POLR3GL polymerase (RNA) III (DNA directed) polypeptide G (32kD)-like 37519 6 6 1 0 0 0 0 0 6 0 0 0.46 0 0.00038 0 0
19 HMGB2 high-mobility group box 2 36819 7 7 1 1 0 0 0 0 7 0 0 0.027 0 2.6e-09 0 0
20 PAK3 p21 (CDKN1A)-activated kinase 3 96884 5 5 1 0 0 0 0 0 5 0 0 0.088 0 0.000058 0 0
21 C22orf32 chromosome 22 open reading frame 32 18921 4 4 1 0 0 0 0 0 4 0 4e-07 0.00014 0 9.5e-07 0 0
22 FYN FYN oncogene related to SRC, FGR, YES 103624 5 5 1 0 0 0 0 0 5 0 0 0.87 0 0.000014 0 0
23 LYPD3 LY6/PLAUR domain containing 3 60319 5 5 1 0 0 0 0 0 5 0 0 0.8 0 3.2e-07 0 0
24 NAP1L5 nucleosome assembly protein 1-like 5 31518 8 8 2 0 0 0 0 0 8 0 4e-07 0.4 9.2e-06 3e-14 0 0
25 CANX calnexin 104199 5 5 1 0 0 0 0 0 5 0 0 0.0091 0 0.49 0 0
26 ADAMTSL4 ADAMTS-like 4 189621 8 8 3 1 1 0 0 0 7 0 0.0012 1.6e-06 0 1.7e-06 0 0
27 IRS1 insulin receptor substrate 1 212717 5 5 1 1 0 0 0 0 5 0 0 0.96 0 0.011 0 0
28 HOXA1 homeobox A1 57912 12 11 2 0 1 0 0 0 11 0 0 1 0 1.4e-14 0 0
29 FLT3LG fms-related tyrosine kinase 3 ligand 38088 6 6 1 0 0 0 0 0 6 0 0 0.12 0 0.00013 0 0
30 OTOP1 otopetrin 1 96428 9 9 2 2 0 0 0 0 9 0 6e-07 0.000048 0 2.8e-10 0 0
31 IPO9 importin 9 180842 6 6 1 0 0 0 0 0 6 0 0 0.012 0 4.5e-06 0 0
32 FADS2 fatty acid desaturase 2 76230 5 5 1 0 0 0 0 0 5 0 0 0.013 0 0.000028 0 0
33 FXR1 fragile X mental retardation, autosomal homolog 1 109493 6 6 2 0 0 0 0 0 5 1 0 0.94 0 0.037 0 0
34 FXR2 fragile X mental retardation, autosomal homolog 2 96461 10 10 2 1 1 0 0 0 9 0 0 0.016 0 3.9e-12 0 0
35 C14orf49 chromosome 14 open reading frame 49 162141 9 9 1 1 0 0 0 0 9 0 0 0.98 0 7.2e-11 0 0
C15orf24

Figure S1.  This figure depicts the distribution of mutations and mutation types across the C15orf24 significant gene.

CTCFL

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

FOXN3

Figure S3.  This figure depicts the distribution of mutations and mutation types across the FOXN3 significant gene.

NOS1AP

Figure S4.  This figure depicts the distribution of mutations and mutation types across the NOS1AP significant gene.

MCL1

Figure S5.  This figure depicts the distribution of mutations and mutation types across the MCL1 significant gene.

TMEM127

Figure S6.  This figure depicts the distribution of mutations and mutation types across the TMEM127 significant gene.

NUFIP2

Figure S7.  This figure depicts the distribution of mutations and mutation types across the NUFIP2 significant gene.

PAPD7

Figure S8.  This figure depicts the distribution of mutations and mutation types across the PAPD7 significant gene.

HAUS8

Figure S9.  This figure depicts the distribution of mutations and mutation types across the HAUS8 significant gene.

KRT10

Figure S10.  This figure depicts the distribution of mutations and mutation types across the KRT10 significant gene.

FUZ

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

BIK

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

SGOL1

Figure S13.  This figure depicts the distribution of mutations and mutation types across the SGOL1 significant gene.

TCF20

Figure S14.  This figure depicts the distribution of mutations and mutation types across the TCF20 significant gene.

LRP10

Figure S15.  This figure depicts the distribution of mutations and mutation types across the LRP10 significant gene.

POLR3GL

Figure S16.  This figure depicts the distribution of mutations and mutation types across the POLR3GL significant gene.

HMGB2

Figure S17.  This figure depicts the distribution of mutations and mutation types across the HMGB2 significant gene.

PAK3

Figure S18.  This figure depicts the distribution of mutations and mutation types across the PAK3 significant gene.

C22orf32

Figure S19.  This figure depicts the distribution of mutations and mutation types across the C22orf32 significant gene.

FYN

Figure S20.  This figure depicts the distribution of mutations and mutation types across the FYN significant gene.

LYPD3

Figure S21.  This figure depicts the distribution of mutations and mutation types across the LYPD3 significant gene.

NAP1L5

Figure S22.  This figure depicts the distribution of mutations and mutation types across the NAP1L5 significant gene.

CANX

Figure S23.  This figure depicts the distribution of mutations and mutation types across the CANX significant gene.

ADAMTSL4

Figure S24.  This figure depicts the distribution of mutations and mutation types across the ADAMTSL4 significant gene.

IRS1

Figure S25.  This figure depicts the distribution of mutations and mutation types across the IRS1 significant gene.

HOXA1

Figure S26.  This figure depicts the distribution of mutations and mutation types across the HOXA1 significant gene.

FLT3LG

Figure S27.  This figure depicts the distribution of mutations and mutation types across the FLT3LG significant gene.

OTOP1

Figure S28.  This figure depicts the distribution of mutations and mutation types across the OTOP1 significant gene.

IPO9

Figure S29.  This figure depicts the distribution of mutations and mutation types across the IPO9 significant gene.

FADS2

Figure S30.  This figure depicts the distribution of mutations and mutation types across the FADS2 significant gene.

FXR1

Figure S31.  This figure depicts the distribution of mutations and mutation types across the FXR1 significant gene.

FXR2

Figure S32.  This figure depicts the distribution of mutations and mutation types across the FXR2 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 ZC3H3 zinc finger CCCH-type containing 3 5 1 5 57 5 2.1e-15 9.5e-12
2 TNFRSF9 tumor necrosis factor receptor superfamily, member 9 7 1 4 57 4 9.2e-15 2.1e-11
3 KRAS v-Ki-ras2 Kirsten rat sarcoma viral oncogene homolog 33 52 33 2964 423105 1.1e-13 1.4e-10
4 TTK TTK protein kinase 5 2 4 114 12 1.3e-13 1.4e-10
5 CDKN2A cyclin-dependent kinase inhibitor 2A (melanoma, p16, inhibits CDK4) 13 332 13 18924 380 5.8e-13 4.6e-10
6 TP53 tumor protein p53 37 356 35 20292 9591 6.2e-13 4.6e-10
7 SMAD4 SMAD family member 4 10 159 6 9063 16 1.7e-09 1.1e-06
8 ADAMTS18 ADAM metallopeptidase with thrombospondin type 1 motif, 18 8 8 3 456 6 2.4e-08 0.000014
9 GNAS GNAS complex locus 6 7 2 399 420 0.000011 0.0054
10 TGFBR2 transforming growth factor, beta receptor II (70/80kDa) 4 12 2 684 2 0.000031 0.014

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: 20. 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 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(1), DNAJC3(3), NFKBIA(2), RELA(1), TP53(37) 859778 44 39 40 3 9 2 9 9 15 0 0.0062 1.4e-15 3.2e-13
2 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(2), DAXX(7), HRAS(1), PML(1), RB1(1), SIRT1(1), SP100(4), TNFRSF1A(2), TNFRSF1B(2), TP53(37) 1656321 58 41 50 5 13 3 12 10 20 0 0.0038 1.8e-15 3.2e-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 MAX(2), MYC(4), SP1(1), TP53(37) 607537 44 41 37 0 9 1 8 7 19 0 0.000057 2.1e-15 3.2e-13
4 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(8), CDKN2A(13), MDM2(1), MYC(4), PIK3CA(1), PIK3R1(1), POLR1A(3), POLR1B(2), RB1(1), TP53(37) 1763289 71 39 61 3 12 5 13 8 33 0 0.00016 2.1e-15 3.2e-13
5 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(3), ATM(6), CCND1(1), CCNE1(1), CDK4(2), MDM2(1), RB1(1), TP53(37) 1563583 52 40 48 3 12 4 11 9 16 0 0.0016 3.8e-15 4.7e-13
6 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(1), CCND1(1), CDK4(2), CDKN2A(13), MDM2(1), NXT1(1), TP53(37) 738429 56 38 50 0 12 2 10 7 25 0 6.3e-06 5.3e-15 4.9e-13
7 P53HYPOXIAPATHWAY Hypoxia induces p53 accumulation and consequent apoptosis with p53-mediated cell cycle arrest, which is present under conditions of DNA damage. ABCB1, AKT1, ATM, BAX, CDKN1A, CPB2, CSNK1A1, CSNK1D, FHL2, GADD45A, HIC1, HIF1A, HSPA1A, HSPCA, IGFBP3, MAPK8, MDM2, NFKBIB, NQO1, TP53 19 ABCB1(2), AKT1(2), ATM(6), CSNK1D(1), FHL2(1), HIC1(1), HIF1A(1), MAPK8(1), MDM2(1), TP53(37) 1809048 53 40 49 4 10 3 11 11 18 0 0.0034 6e-15 4.9e-13
8 ATMPATHWAY The tumor-suppressing protein kinase ATM responds to radiation-induced DNA damage by blocking cell-cycle progression and activating DNA repair. ABL1, ATM, BRCA1, CDKN1A, CHEK1, CHEK2, GADD45A, JUN, MAPK8, MDM2, MRE11A, NBS1, NFKB1, NFKBIA, RAD50, RAD51, RBBP8, RELA, TP53, TP73 19 ABL1(8), ATM(6), BRCA1(3), CHEK1(3), CHEK2(1), MAPK8(1), MDM2(1), MRE11A(2), NFKBIA(2), RBBP8(2), RELA(1), TP53(37) 2565925 67 43 60 3 13 6 15 9 24 0 0.00032 6.3e-15 4.9e-13
9 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(6), CDC25A(2), CDC25C(2), CDK4(2), CHEK1(3), MYT1(9), RB1(1), TP53(37), YWHAH(1) 1510491 63 42 53 5 12 4 11 10 26 0 0.012 8e-15 5e-13
10 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 IFNGR1(2), IFNGR2(4), IKBKB(2), JAK2(2), LIN7A(1), NFKBIA(2), RB1(1), RELA(1), TNFRSF1A(2), TNFRSF1B(2), TP53(37), USH1C(1) 1594010 57 42 50 6 12 3 13 9 20 0 0.0094 8.4e-15 5e-13
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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