Mutation Analysis (MutSig v2.0 and MutSigCV v0.9 merged result)
Pancreatic Adenocarcinoma (Primary solid tumor)
15 January 2014  |  analyses__2014_01_15
Maintainer Information
Citation Information
doi:10.7908/C1805136
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/C1805136
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): 99

  • Mutations seen in COSMIC: 134

  • Significantly mutated genes in COSMIC territory: 8

  • Significantly mutated genesets: 21

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 3296 blacklisted mutations: 24354

  • After removing 387 noncoding mutations: 23967

  • After collapsing adjacent/redundant mutations: 23883

Mutation Filtering

  • Number of mutations before filtering: 23883

  • After removing 898 mutations outside gene set: 22985

  • After removing 130 mutations outside category set: 22855

  • After removing 1 "impossible" mutations in

  • gene-patient-category bins of zero coverage: 21826

Results
Breakdown of Mutations by Type

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

type count
Frame_Shift_Del 795
Frame_Shift_Ins 275
In_Frame_Del 884
In_Frame_Ins 19
Missense_Mutation 13811
Nonsense_Mutation 868
Nonstop_Mutation 4
Silent 5460
Splice_Site 736
Translation_Start_Site 3
Total 22855
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 4314 98986159 0.000044 44 4.3 2.1
*Cp(A/C/T)->T 3444 788202097 4.4e-06 4.4 0.43 1.7
C->(G/A) 3341 887188256 3.8e-06 3.8 0.37 4.7
A->mut 2711 841595742 3.2e-06 3.2 0.32 3.9
indel+null 3465 1728783998 2e-06 2 0.2 NaN
double_null 119 1728783998 6.9e-08 0.069 0.0068 NaN
Total 17394 1728783998 1e-05 10 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: 99. 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 C15orf24 chromosome 15 open reading frame 24 42615 6 6 1 0 0 0 0 0 6 0 0 1 0 5.5e-08 0 0
2 IRS1 insulin receptor substrate 1 212717 5 5 1 1 0 0 0 0 5 0 0 0.96 0 0.011 0 0
3 FYN FYN oncogene related to SRC, FGR, YES 103624 5 5 1 0 0 0 0 0 5 0 0 0.87 0 0.000019 0 0
4 FADS2 fatty acid desaturase 2 76230 5 5 1 0 0 0 0 0 5 0 0 0.013 0 0.000027 0 0
5 C14orf49 chromosome 14 open reading frame 49 162141 9 9 1 1 0 0 0 0 9 0 0 0.98 0 3.4e-11 0 0
6 INTS10 integrator complex subunit 10 124543 2 1 2 1 0 0 0 1 0 1 0.4 0 0 0.78 0 0
7 FGF10 fibroblast growth factor 10 36330 6 6 1 0 0 0 0 0 6 0 0 1 0 5.1e-07 0 0
8 CEL carboxyl ester lipase (bile salt-stimulated lipase) 103583 4 4 1 2 0 0 0 0 4 0 1.2e-06 0.000042 0 0.00056 0 0
9 CCR3 chemokine (C-C motif) receptor 3 61695 5 5 1 0 0 0 0 0 4 1 0 0.75 0 3.1e-06 0 0
10 OR10A2 olfactory receptor, family 10, subfamily A, member 2 52212 6 6 1 0 0 0 0 0 6 0 0 0.0066 0 1.9e-08 0 0
11 OR10A7 olfactory receptor, family 10, subfamily A, member 7 54378 9 9 1 0 0 0 0 0 9 0 0 0.92 0 2.9e-14 0 0
12 POP5 processing of precursor 5, ribonuclease P/MRP subunit (S. cerevisiae) 29146 5 5 1 0 0 0 0 0 5 0 0 0.72 0 4e-08 0 0
13 SRP14 signal recognition particle 14kDa (homologous Alu RNA binding protein) 24486 7 7 1 0 0 0 0 0 7 0 0 1 0 9.4e-11 0 0
14 WRN Werner syndrome 250953 5 5 1 0 0 0 0 0 5 0 0 0.64 0 0.35 0 0
15 TMEM40 transmembrane protein 40 40250 9 9 2 0 0 0 0 0 9 0 0 0.56 0 8.4e-15 0 0
16 KRAS v-Ki-ras2 Kirsten rat sarcoma viral oncogene homolog 39758 33 33 4 0 0 14 15 4 0 0 0 0.0024 0 5.4e-08 0 0
17 TP53 tumor protein p53 71159 37 37 33 0 9 1 7 7 13 0 1.2e-06 0.00033 0 3.3e-15 0 0
18 QRICH1 glutamine-rich 1 134916 7 7 2 1 1 0 0 0 6 0 3.6e-06 0.012 0 0.000021 0 0
19 ST6GALNAC5 ST6 (alpha-N-acetyl-neuraminyl-2,3-beta-galactosyl-1,3)-N-acetylgalactosaminide alpha-2,6-sialyltransferase 5 54579 6 6 1 0 0 0 0 0 6 0 0 0.14 0 2.4e-08 0 0
20 TNFSF9 tumor necrosis factor (ligand) superfamily, member 9 34191 6 6 1 1 0 0 0 0 6 0 0 0.61 0 7.2e-10 0 0
21 CDKN2A cyclin-dependent kinase inhibitor 2A (melanoma, p16, inhibits CDK4) 56371 13 13 11 0 0 1 1 0 11 0 0.0056 0.0041 0.0014 2.8e-13 1.5e-14 1.3e-11
22 SEH1L SEH1-like (S. cerevisiae) 74814 8 8 2 0 0 0 0 0 8 0 8.2e-06 0.98 0.000048 9.1e-11 1.5e-13 1.2e-10
23 SCD stearoyl-CoA desaturase (delta-9-desaturase) 62889 8 8 2 0 0 0 0 0 8 0 8.8e-06 0.94 0.000057 1.5e-10 2.9e-13 2.3e-10
24 TMC4 transmembrane channel-like 4 112036 9 9 2 0 0 0 0 1 8 0 1.6e-06 0.24 6.6e-06 5.9e-09 1.2e-12 9.3e-10
25 MED15 mediator complex subunit 15 137354 11 9 5 0 0 0 1 1 9 0 0.000031 0.77 0.0001 6e-10 2e-12 1.4e-09
26 TNFRSF9 tumor necrosis factor receptor superfamily, member 9 45333 7 6 4 0 0 0 0 0 7 0 0.021 0.0011 0.00075 2.1e-09 4.5e-11 3.2e-08
27 BRDT bromodomain, testis-specific 165362 8 8 2 0 0 0 1 0 7 0 1e-05 0.25 0.000043 1.5e-07 1.7e-10 1.2e-07
28 CXXC4 CXXC finger 4 34485 6 6 1 0 0 0 0 0 6 0 NaN NaN NaN 3.4e-10 3.4e-10 2.2e-07
29 MBD3 methyl-CpG binding domain protein 3 50273 6 6 2 0 0 1 0 0 5 0 2.2e-06 0.99 9.6e-06 2e-06 4.9e-10 3.1e-07
30 TULP1 tubby like protein 1 84798 6 6 2 1 1 0 0 0 5 0 0.000085 0.97 0.0002 2e-07 9.9e-10 6e-07
31 PHF13 PHD finger protein 13 52336 4 4 1 0 0 0 0 0 4 0 8e-07 0.98 6e-06 8.2e-06 1.2e-09 7.1e-07
32 BHLHB9 basic helix-loop-helix domain containing, class B, 9 93837 5 5 2 0 1 0 0 0 4 0 1.4e-06 0.38 8e-06 0.000012 2.4e-09 1.4e-06
33 PRDM8 PR domain containing 8 73928 6 6 2 0 0 0 1 0 5 0 0.000051 1 0.00016 1e-06 4e-09 2.2e-06
34 SMAD4 SMAD family member 4 96994 10 10 9 0 3 0 0 1 6 0 0.3 0.36 0.48 1.9e-09 2e-08 0.000011
35 C14orf43 chromosome 14 open reading frame 43 179212 7 7 2 0 0 0 1 0 6 0 2.4e-06 0.57 0.000021 0.000047 2.1e-08 0.000011
C15orf24

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

IRS1

Figure S2.  This figure depicts the distribution of mutations and mutation types across the IRS1 significant gene.

FYN

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

FADS2

Figure S4.  This figure depicts the distribution of mutations and mutation types across the FADS2 significant gene.

C14orf49

Figure S5.  This figure depicts the distribution of mutations and mutation types across the C14orf49 significant gene.

INTS10

Figure S6.  This figure depicts the distribution of mutations and mutation types across the INTS10 significant gene.

FGF10

Figure S7.  This figure depicts the distribution of mutations and mutation types across the FGF10 significant gene.

CEL

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

CCR3

Figure S9.  This figure depicts the distribution of mutations and mutation types across the CCR3 significant gene.

OR10A2

Figure S10.  This figure depicts the distribution of mutations and mutation types across the OR10A2 significant gene.

OR10A7

Figure S11.  This figure depicts the distribution of mutations and mutation types across the OR10A7 significant gene.

POP5

Figure S12.  This figure depicts the distribution of mutations and mutation types across the POP5 significant gene.

SRP14

Figure S13.  This figure depicts the distribution of mutations and mutation types across the SRP14 significant gene.

WRN

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

TMEM40

Figure S15.  This figure depicts the distribution of mutations and mutation types across the TMEM40 significant gene.

KRAS

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

TP53

Figure S17.  This figure depicts the distribution of mutations and mutation types across the TP53 significant gene.

QRICH1

Figure S18.  This figure depicts the distribution of mutations and mutation types across the QRICH1 significant gene.

ST6GALNAC5

Figure S19.  This figure depicts the distribution of mutations and mutation types across the ST6GALNAC5 significant gene.

TNFSF9

Figure S20.  This figure depicts the distribution of mutations and mutation types across the TNFSF9 significant gene.

CDKN2A

Figure S21.  This figure depicts the distribution of mutations and mutation types across the CDKN2A significant gene.

SEH1L

Figure S22.  This figure depicts the distribution of mutations and mutation types across the SEH1L significant gene.

SCD

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

TMC4

Figure S24.  This figure depicts the distribution of mutations and mutation types across the TMC4 significant gene.

MED15

Figure S25.  This figure depicts the distribution of mutations and mutation types across the MED15 significant gene.

TNFRSF9

Figure S26.  This figure depicts the distribution of mutations and mutation types across the TNFRSF9 significant gene.

BRDT

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

MBD3

Figure S28.  This figure depicts the distribution of mutations and mutation types across the MBD3 significant gene.

TULP1

Figure S29.  This figure depicts the distribution of mutations and mutation types across the TULP1 significant gene.

PHF13

Figure S30.  This figure depicts the distribution of mutations and mutation types across the PHF13 significant gene.

BHLHB9

Figure S31.  This figure depicts the distribution of mutations and mutation types across the BHLHB9 significant gene.

PRDM8

Figure S32.  This figure depicts the distribution of mutations and mutation types across the PRDM8 significant gene.

SMAD4

Figure S33.  This figure depicts the distribution of mutations and mutation types across the SMAD4 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: 8. Number of genes displayed: 10

rank gene description n cos n_cos N_cos cos_ev p q
1 KRAS v-Ki-ras2 Kirsten rat sarcoma viral oncogene homolog 33 52 33 2964 423105 0 0
2 TP53 tumor protein p53 37 356 35 20292 9591 0 0
3 CDKN2A cyclin-dependent kinase inhibitor 2A (melanoma, p16, inhibits CDK4) 13 332 13 18924 380 0 0
4 TNFRSF9 tumor necrosis factor receptor superfamily, member 9 7 1 4 57 4 2e-15 2.3e-12
5 TTK TTK protein kinase 5 2 4 114 12 6.4e-14 5.8e-11
6 SMAD4 SMAD family member 4 10 159 6 9063 16 7.4e-10 5.6e-07
7 GNAS GNAS complex locus 6 7 2 399 420 8e-06 0.0052
8 TGFBR2 transforming growth factor, beta receptor II (70/80kDa) 4 12 2 684 2 0.000024 0.013
9 BRCA2 breast cancer 2, early onset 6 59 2 3363 2 0.00056 0.22
10 MCM2 minichromosome maintenance complex component 2 3 1 1 57 1 0.00057 0.22

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 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 1.3e-15 3.4e-13
2 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(1), IFNGR2(4), IKBKB(2), JAK2(2), LIN7A(1), NFKBIA(2), RB1(1), RELA(1), TNFRSF1A(2), TNFRSF1B(1), TP53(37), USH1C(1) 1594010 55 41 48 6 12 3 12 9 19 0 0.011 2.6e-15 3.4e-13
3 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), CCNE1(1), CDK4(2), MDM2(1), RB1(1), TP53(37) 1563583 51 40 47 3 12 4 11 9 15 0 0.0016 2.6e-15 3.4e-13
4 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 3.1e-15 3.4e-13
5 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), SP1(1), TP53(37) 607537 40 40 36 0 9 1 8 7 15 0 0.000057 3.9e-15 3.4e-13
6 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), PIK3CA(1), PIK3R1(1), POLR1A(3), POLR1B(2), RB1(1), TP53(37) 1763289 67 38 60 3 12 5 13 8 29 0 0.00016 4.2e-15 3.4e-13
7 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), MAPK8(1), MDM2(1), MRE11A(2), NFKBIA(2), RBBP8(2), RELA(1), TP53(37) 2565925 63 42 58 2 13 6 14 9 21 0 0.000087 4.4e-15 3.4e-13
8 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(1), DAXX(2), HRAS(1), PML(1), RB1(1), SIRT1(1), SP100(4), TNFRSF1A(2), TNFRSF1B(1), TP53(37) 1656321 51 38 47 5 13 3 11 10 14 0 0.0043 4.4e-15 3.4e-13
9 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), CDK4(2), CDKN2A(13), MDM2(1), NXT1(1), TP53(37) 738429 55 38 49 0 12 2 10 7 24 0 6.3e-06 5.2e-15 3.6e-13
10 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), MYT1(6), RB1(1), TP53(37), YWHAH(1) 1510491 57 41 51 3 12 4 11 10 20 0 0.0014 6e-15 3.7e-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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