Mutation Analysis (MutSig 2CV v3.1)
Ovarian Serous Cystadenocarcinoma (Primary solid tumor)
17 October 2014  |  analyses__2014_10_17
Maintainer Information
Citation Information
doi:10.7908/C1CV4GNX
Maintained by David Heiman (Broad Institute)
Cite as Broad Institute TCGA Genome Data Analysis Center (2014): Mutation Analysis (MutSig 2CV v3.1). Broad Institute of MIT and Harvard. doi:10.7908/C1CV4GNX
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 2CV v3.1 was used to generate the results found in this report.

  • Working with individual set: OV-TP

  • Number of patients in set: 316

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:OV-TP.final_analysis_set.maf

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

  • Significantly mutated genes (q ≤ 0.1): 13

Results
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 1.  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 2.  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 3.  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:

  • nnon = 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

  • p = p-value (overall)

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

Table 1.  Get Full Table A Ranked List of Significantly Mutated Genes. Number of significant genes found: 13. 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 longname codelen nnei nncd nsil nmis nstp nspl nind nnon npat nsite pCV pCL pFN p q
1 TP53 tumor protein p53 1314 5 0 3 178 25 32 41 276 273 140 1e-16 1e-05 1e-05 1e-16 1.8e-12
2 BRCA1 breast cancer 1, early onset 5750 12 0 0 1 4 0 7 12 12 12 1.5e-14 1 0.19 1.3e-13 1.1e-09
3 FAM86B2 family with sequence similarity 86, member B2 1021 41 0 0 0 0 0 6 6 6 1 1.1e-08 2e-05 0.42 3.3e-12 2e-08
4 TBP TATA box binding protein 1044 42 0 0 0 0 0 4 4 4 2 1.4e-07 0.00019 1 7.6e-10 3.5e-06
5 NBPF10 neuroblastoma breakpoint family, member 10 10994 2 0 0 0 0 0 4 4 4 2 0.00016 0.0001 0.00031 3.1e-07 0.0011
6 NF1 neurofibromin 1 (neurofibromatosis, von Recklinghausen disease, Watson disease) 8807 0 0 0 6 4 1 4 15 14 15 1.2e-07 1 0.17 5.8e-07 0.0018
7 C10orf140 chromosome 10 open reading frame 140 2727 152 0 1 2 0 0 3 5 5 3 0.00018 0.0003 0.61 9.9e-07 0.0026
8 BRCA2 breast cancer 2, early onset 10361 1 0 0 2 4 0 6 12 11 12 1.3e-07 1 0.93 2.1e-06 0.0048
9 CDK12 cyclin-dependent kinase 12 4525 11 0 0 4 2 0 2 8 8 8 1.4e-06 1 0.18 5.2e-06 0.01
10 OR4F21 olfactory receptor, family 4, subfamily F, member 21 937 81 0 0 0 0 0 3 3 3 1 0.00087 0.001 0.83 0.000013 0.024
11 C9orf171 chromosome 9 open reading frame 171 989 68 0 0 4 0 0 1 5 5 5 0.00042 1 0.0019 0.000034 0.054
12 HYDIN hydrocephalus inducing homolog (mouse) 15717 41 0 3 11 0 0 0 11 11 10 0.0035 0.00057 0.3 0.000036 0.054
13 RB1 retinoblastoma 1 (including osteosarcoma) 2891 170 0 0 4 2 1 1 8 8 8 3.6e-06 1 0.62 0.000049 0.068
14 GART phosphoribosylglycinamide formyltransferase, phosphoribosylglycinamide synthetase, phosphoribosylaminoimidazole synthetase 3123 1 0 0 1 0 0 2 3 3 2 0.0023 0.0029 0.73 0.000089 0.12
15 SRC v-src sarcoma (Schmidt-Ruppin A-2) viral oncogene homolog (avian) 1655 18 0 0 4 0 0 0 4 4 2 0.034 0.0003 0.056 0.00014 0.16
16 ZNF236 zinc finger protein 236 5658 103 0 2 4 3 0 0 7 7 7 0.000069 1 0.075 0.00014 0.16
17 NBPF16 neuroblastoma breakpoint family, member 16 4146 6 0 1 0 0 0 4 4 4 2 0.092 0.00019 0.61 0.00015 0.16
18 CYP11B1 cytochrome P450, family 11, subfamily B, polypeptide 1 1546 105 0 0 7 0 0 0 7 7 6 0.000016 1 0.7 0.00019 0.2
19 SON SON DNA binding protein 7584 4 0 0 4 0 0 4 8 8 7 0.001 0.015 0.66 0.00024 0.23
20 LCOR ligand dependent nuclear receptor corepressor 1323 161 0 0 2 2 0 0 4 4 4 0.00074 1 0.0088 0.00036 0.32
21 ITGB7 integrin, beta 7 2453 115 0 1 4 0 0 0 4 4 3 0.023 0.011 0.075 0.00045 0.39
22 FBLN2 fibulin 2 2452 69 0 0 2 1 1 0 4 4 4 0.00064 1 0.056 0.00047 0.39
23 PKD1L1 polycystic kidney disease 1 like 1 8774 32 0 2 7 1 0 1 9 8 9 0.0078 1 0.0026 0.00057 0.45
24 SSPO SCO-spondin homolog (Bos taurus) 15871 4 0 1 1 0 0 3 4 4 3 0.0093 0.0042 0.96 0.00061 0.45
25 TMPRSS3 transmembrane protease, serine 3 1494 54 0 1 1 0 2 0 3 3 2 0.023 0.021 0.026 0.00062 0.45
26 EPS15L1 epidermal growth factor receptor pathway substrate 15-like 1 2685 98 0 0 2 0 2 0 4 4 4 0.0013 1 0.035 0.00074 0.52
27 RASAL1 RAS protein activator like 1 (GAP1 like) 2495 64 0 1 4 0 0 2 6 6 6 0.000077 1 0.92 0.00081 0.55
28 SMG6 Smg-6 homolog, nonsense mediated mRNA decay factor (C. elegans) 4334 6 0 0 0 2 0 0 2 2 1 0.0092 0.01 0.79 0.00095 0.62
29 C11orf59 chromosome 11 open reading frame 59 502 35 0 0 2 0 0 0 2 2 1 0.0066 0.016 0.19 0.0011 0.65
30 TGIF1 TGFB-induced factor homeobox 1 1292 383 0 0 1 0 0 2 3 3 2 0.0091 0.012 0.47 0.0011 0.65
31 NRAS neuroblastoma RAS viral (v-ras) oncogene homolog 590 34 0 0 2 0 0 0 2 2 1 0.011 0.01 0.64 0.0011 0.65
32 ACBD4 acyl-Coenzyme A binding domain containing 4 1092 59 0 0 0 1 0 2 3 3 3 0.00011 1 0.61 0.0011 0.65
33 ACVR2B activin A receptor, type IIB 1581 156 0 0 3 0 0 0 3 3 2 0.013 0.0091 0.32 0.0012 0.65
34 NBPF14 neuroblastoma breakpoint family, member 14 2852 19 0 0 2 0 0 2 4 4 3 0.016 0.012 0.58 0.0013 0.65
35 KIAA1462 KIAA1462 4092 26 0 1 2 1 0 2 5 5 5 0.0065 1 0.0099 0.0013 0.65
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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