Mutation Analysis (MutSig v1.5)
Liver Hepatocellular Carcinoma (Primary solid tumor)
02 April 2015  |  analyses__2015_04_02
Maintainer Information
Citation Information
doi:10.7908/C10C4TT2
Maintained by David Heiman (Broad Institute)
Cite as Broad Institute TCGA Genome Data Analysis Center (2015): Mutation Analysis (MutSig v1.5). Broad Institute of MIT and Harvard. doi:10.7908/C10C4TT2
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: 197

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): 28

  • Mutations seen in COSMIC: 176

  • Significantly mutated genes in COSMIC territory: 10

  • Significantly mutated genesets: 32

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

Mutation Preprocessing

  • Read 198 MAFs of type "Baylor-Illumina"

  • Total number of mutations in input MAFs: 27892

  • After removing 53 blacklisted mutations: 27839

  • After removing 219 noncoding mutations: 27620

  • After collapsing adjacent/redundant mutations: 27618

Mutation Filtering

  • Number of mutations before filtering: 27618

  • After removing 241 mutations outside patient set: 27377

  • After removing 1147 mutations outside gene set: 26230

  • After removing 33 mutations outside category set: 26197

Results
Breakdown of Mutations by Type

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

type count
Frame_Shift_Del 574
Frame_Shift_Ins 268
In_Frame_Del 130
In_Frame_Ins 21
Missense_Mutation 17201
Nonsense_Mutation 918
Silent 6465
Splice_Site 619
Translation_Start_Site 1
Total 26197
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
transit 8598 6157259362 1.4e-06 1.4 0.44 2
C->A 3806 3141918468 1.2e-06 1.2 0.38 4.4
flip 3779 6157259362 6.1e-07 0.61 0.19 5.3
A->C 1018 3015340894 3.4e-07 0.34 0.11 5.2
indel+null 2499 6157259362 4.1e-07 0.41 0.13 NaN
double_null 32 6157259362 5.2e-09 0.0052 0.0016 NaN
Total 19732 6157259362 3.2e-06 3.2 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: transit

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

  • n3 = number of nonsilent mutations of type: flip

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

  • 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: 28. 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 ALB albumin 369854 18 18 18 1 5 1 1 1 7 3 0.18 2.6e-15 3.2e-11
2 TP53 tumor protein p53 249557 63 62 50 1 20 15 3 3 22 0 1.2e-06 3.9e-15 3.2e-11
3 CTNNB1 catenin (cadherin-associated protein), beta 1, 88kDa 471692 52 50 25 2 20 4 18 7 2 1 0.000066 5.2e-15 3.2e-11
4 RB1 retinoblastoma 1 (including osteosarcoma) 518944 16 15 16 1 0 0 2 1 12 1 0.34 4e-13 1.9e-09
5 BAP1 BRCA1 associated protein-1 (ubiquitin carboxy-terminal hydrolase) 435698 11 11 11 0 0 0 1 2 8 0 0.22 1e-09 3.8e-06
6 ARID1A AT rich interactive domain 1A (SWI-like) 1137771 16 16 15 1 1 0 3 1 10 1 0.27 1.6e-08 5e-05
7 AXIN1 axin 1 434917 10 9 10 1 0 0 1 0 9 0 0.62 1.4e-07 0.00038
8 GRXCR1 glutaredoxin, cysteine rich 1 174143 8 7 8 1 2 3 3 0 0 0 0.37 1.4e-06 0.0033
9 HNF1A HNF1 homeobox A 356985 12 8 12 0 4 1 3 0 4 0 0.04 1.7e-06 0.0035
10 PTEN phosphatase and tensin homolog (mutated in multiple advanced cancers 1) 237849 7 7 7 0 1 0 1 0 5 0 0.47 1.9e-06 0.0035
11 CDKN1A cyclin-dependent kinase inhibitor 1A (p21, Cip1) 87268 5 4 5 0 0 2 1 1 1 0 0.38 3.3e-06 0.0054
12 IRX1 iroquois homeobox 1 195940 7 7 7 1 2 3 1 0 1 0 0.43 3.5e-06 0.0054
13 KIF19 kinesin family member 19 499210 10 10 10 0 6 2 0 1 1 0 0.042 6.7e-06 0.0096
14 TRPA1 transient receptor potential cation channel, subfamily A, member 1 669092 10 10 10 1 1 5 2 0 2 0 0.48 8.8e-06 0.011
15 LCE1E late cornified envelope 1E 70748 4 4 4 0 1 1 0 0 2 0 0.57 8.9e-06 0.011
16 CHL1 cell adhesion molecule with homology to L1CAM (close homolog of L1) 731382 11 11 11 1 5 3 2 1 0 0 0.21 0.000021 0.024
17 SGCZ sarcoglycan zeta 184196 5 5 5 0 2 1 1 0 1 0 0.21 0.000028 0.031
18 HIST1H1C histone cluster 1, H1c 126299 5 5 5 0 4 0 1 0 0 0 0.15 0.000031 0.032
19 LDOC1L leucine zipper, down-regulated in cancer 1-like 135746 5 5 5 0 3 1 0 0 1 0 0.16 0.000048 0.048
20 MAB21L1 mab-21-like 1 (C. elegans) 206986 6 6 6 0 3 2 1 0 0 0 0.13 0.000059 0.054
21 APOB apolipoprotein B (including Ag(x) antigen) 2679262 27 25 27 3 9 3 4 0 11 0 0.19 6e-05 0.054
22 IL12A interleukin 12A (natural killer cell stimulatory factor 1, cytotoxic lymphocyte maturation factor 1, p35) 153415 5 5 5 0 2 1 2 0 0 0 0.26 0.000069 0.059
23 IL6ST interleukin 6 signal transducer (gp130, oncostatin M receptor) 553112 7 7 7 1 0 1 0 0 6 0 0.84 8e-05 0.064
24 PDX1 pancreatic and duodenal homeobox 1 80852 4 4 4 0 2 2 0 0 0 0 0.27 0.000088 0.068
25 GLI2 GLI-Kruppel family member GLI2 754225 10 10 10 1 4 4 2 0 0 0 0.18 0.000094 0.07
26 KEAP1 kelch-like ECH-associated protein 1 355860 8 7 8 0 4 3 0 0 1 0 0.084 0.00013 0.096
27 ZNF676 zinc finger protein 676 324631 7 6 7 0 0 2 3 0 2 0 0.52 0.00014 0.096
28 NLGN1 neuroligin 1 487005 8 7 8 1 0 4 1 1 2 0 0.64 0.00015 0.098
29 UBE2N ubiquitin-conjugating enzyme E2N (UBC13 homolog, yeast) 93452 4 4 4 0 2 1 1 0 0 0 0.31 0.00016 0.1
30 KRAS v-Ki-ras2 Kirsten rat sarcoma viral oncogene homolog 138504 4 4 4 0 3 1 0 0 0 0 0.28 0.00018 0.11
31 PCDHB16 protocadherin beta 16 383268 6 6 6 1 2 1 2 0 1 0 0.55 0.00022 0.13
32 BAGE3 B melanoma antigen family, member 3 47451 3 3 3 0 3 0 0 0 0 0 0.29 0.00022 0.13
33 OR51G1 olfactory receptor, family 51, subfamily G, member 1 187442 5 5 5 1 2 3 0 0 0 0 0.42 0.00024 0.14
34 PCDH11Y protocadherin 11 Y-linked 623444 8 8 8 1 3 1 3 0 1 0 0.31 0.00025 0.14
35 SPRR4 small proline-rich protein 4 48053 3 3 3 0 0 1 0 1 1 0 0.49 0.00026 0.14
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 CTNNB1 catenin (cadherin-associated protein), beta 1, 88kDa 52 138 42 27186 11962 0 0
2 TP53 tumor protein p53 63 356 58 70132 10380 0 0
3 RB1 retinoblastoma 1 (including osteosarcoma) 16 267 12 52599 21 0 0
4 IDH1 isocitrate dehydrogenase 1 (NADP+), soluble 3 5 3 985 4476 5.2e-09 5.9e-06
5 GNAS GNAS complex locus 7 7 3 1379 630 1.4e-08 0.000013
6 PIK3CA phosphoinositide-3-kinase, catalytic, alpha polypeptide 7 220 5 43340 2949 3.8e-07 0.00029
7 PTEN phosphatase and tensin homolog (mutated in multiple advanced cancers 1) 7 767 7 151099 82 8.1e-07 0.00053
8 KRAS v-Ki-ras2 Kirsten rat sarcoma viral oncogene homolog 4 52 3 10244 16864 5.8e-06 0.0033
9 IDH2 isocitrate dehydrogenase 2 (NADP+), mitochondrial 4 6 2 1182 166 7.2e-06 0.0036
10 HNF1A HNF1 homeobox A 12 98 3 19306 8 0.000038 0.017

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: 32. 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 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(7), ATR(6), CHEK1(1), CHEK2(2), TP53(63), YWHAH(1) 4627970 80 72 67 4 22 18 9 6 25 0 5e-05 1.6e-15 3e-13
2 WNTPATHWAY The Wnt glycoprotein binds to membrane-bound receptors such as Frizzled to activate a number of signaling pathways, including that of beta-catenin. APC, AXIN1, BTRC, CCND1, CREBBP, CSNK1A1, CSNK1D, CSNK2A1, CTBP1, CTNNB1, DVL1, FRAT1, FZD1, GSK3B, HDAC1, MADH4, MAP3K7, MAP3K7IP1, MYC, NLK, PPARD, PPP2CA, TCF1, TLE1, WIF1, WNT1 23 APC(5), AXIN1(10), BTRC(1), CREBBP(6), CSNK2A1(1), CTNNB1(52), DVL1(1), FZD1(1), GSK3B(2), MAP3K7(1), MYC(1), NLK(1), PPARD(1), PPP2CA(1), TLE1(4), WIF1(1), WNT1(2) 8805327 91 78 64 6 33 8 23 8 18 1 1e-05 2.3e-15 3e-13
3 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(5), ATM(7), BAX(1), CDKN1A(5), CPB2(2), HIF1A(1), IGFBP3(1), MDM2(1), TP53(63) 6314867 86 76 73 7 26 19 9 7 25 0 0.00024 2.9e-15 3e-13
4 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(6), PAX3(3), PML(1), RARA(1), RB1(16), TNF(2), TNFRSF1A(1), TP53(63) 5503411 93 82 80 4 29 17 7 5 34 1 8.9e-07 3.2e-15 3e-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(7), BAX(1), BCL2(1), CCNE1(1), CDKN1A(5), E2F1(1), MDM2(1), RB1(16), TP53(63) 5292075 99 80 86 6 24 19 11 7 37 1 0.000028 3.9e-15 3e-13
6 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(2), NFKB1(2), NFKBIA(2), RELA(1), TP53(63) 3002721 70 68 57 6 24 16 4 3 23 0 0.00061 4.3e-15 3e-13
7 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 CDKN1A(5), CDKN2A(1), CFL1(1), E2F1(1), MDM2(1), TP53(63) 2400548 72 68 59 2 20 17 7 5 23 0 1.7e-06 4.3e-15 3e-13
8 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(1), SP1(2), SP3(3), TP53(63), WT1(3) 2072209 72 70 59 1 26 15 4 4 23 0 1.1e-07 4.7e-15 3e-13
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 CDKN2A(1), E2F1(1), MDM2(1), MYC(1), PIK3CA(7), PIK3R1(2), POLR1A(1), RB1(16), TBX2(3), TP53(63) 5835542 96 84 82 5 27 18 8 6 36 1 4.8e-06 4.8e-15 3e-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(7), CHEK1(1), MYT1(4), RB1(16), TP53(63), WEE1(2), YWHAH(1) 5188043 94 83 81 6 24 18 9 6 36 1 0.000058 4.9e-15 3e-13

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 HSA00472_D_ARGININE_AND_D_ORNITHINE_METABOLISM Genes involved in D-arginine and D-ornithine metabolism DAO 1 DAO(5) 206449 5 5 5 0 3 1 1 0 0 0 0.2 0.00091 0.56
2 FOSBPATHWAY FOSB gene expression and drug abuse CDK5, FOSB, GRIA2, JUND, PPP1R1B 5 GRIA2(7), JUND(1), PPP1R1B(1) 1097157 9 9 9 1 6 1 2 0 0 0 0.17 0.005 1
3 ACHPATHWAY Nicotinic acetylcholine receptors are ligand-gated ion channels that primarily mediate neuromuscular signaling and may inhibit neuronal apoptosis via the AKT pathway. AKT1, BAD, CHRNB1, CHRNG, FOXO3A, MUSK, PIK3CA, PIK3R1, PTK2, PTK2B, RAPSN, SRC, TERT, TNFSF6, YWHAH 13 MUSK(4), PIK3CA(7), PIK3R1(2), PTK2(6), PTK2B(4), RAPSN(1), SRC(1), YWHAH(1) 4891704 26 24 25 2 12 3 4 1 6 0 0.021 0.0059 1
4 PTENPATHWAY PTEN suppresses AKT-induced cell proliferation and antagonizes the action of PI3K. AKT1, BCAR1, CDKN1B, FOXO3A, GRB2, ILK, ITGB1, MAPK1, MAPK3, PDK2, PDPK1, PIK3CA, PIK3R1, PTEN, PTK2, SHC1, SOS1, TNFSF6 15 BCAR1(2), ITGB1(1), MAPK1(1), PDK2(1), PIK3CA(7), PIK3R1(2), PTK2(6), SHC1(2), SOS1(4) 5556210 26 25 25 1 16 5 1 2 2 0 0.0028 0.0094 1
5 VOBESITYPATHWAY The adipose tissue of obese individuals overexpresses a key glucocorticoid-metabolizing enzyme, activating inactive circulating corticosteroids and inducing insulin resistance. APM1, HSD11B1, LPL, NR3C1, PPARG, RETN, RXRA, TNF 7 LPL(1), NR3C1(2), RXRA(5), TNF(2) 1684442 10 10 10 1 4 1 3 2 0 0 0.25 0.021 1
6 FXRPATHWAY The nuclear receptor transcription factors FXR and LXR are activated by cholesterol metabolites and regulate cholesterol homeostasis. FABP6, LDLR, NR0B2, NR1H3, NR1H4, RXRA 6 LDLR(1), NR0B2(2), NR1H3(2), RXRA(5) 1561481 10 10 10 0 5 3 0 2 0 0 0.05 0.026 1
7 IFNGPATHWAY IFN gamma signaling pathway IFNG, IFNGR1, IFNGR2, JAK1, JAK2, STAT1 6 IFNG(2), IFNGR1(2), JAK1(2), JAK2(4), STAT1(2) 2415080 12 12 12 0 4 0 4 2 2 0 0.072 0.029 1
8 REDUCTIVE_CARBOXYLATE_CYCLE_CO2_FIXATION ACO1, ACO2, FH, IDH1, IDH2, MDH1, MDH2, SDHB, SUCLA2 9 ACO1(1), ACO2(3), FH(2), IDH1(3), IDH2(4), SDHB(1) 2632793 14 13 12 1 9 0 4 1 0 0 0.053 0.029 1
9 STILBENE_COUMARINE_AND_LIGNIN_BIOSYNTHESIS EPX, GBA3, LPO, MPO, PRDX1, PRDX2, PRDX5, PRDX6, TPO, TYR 10 EPX(2), LPO(3), MPO(5), PRDX1(1), PRDX2(1), TPO(9), TYR(4) 2869824 25 23 25 4 10 5 5 0 5 0 0.11 0.053 1
10 CAPROLACTAM_DEGRADATION AKR1A1, ECHS1, EHHADH, HADHA, SDS 5 ECHS1(1), EHHADH(9), SDS(2) 1439908 12 7 12 1 6 2 2 1 1 0 0.12 0.058 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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