Mutation Analysis (MutSigCV v0.6)
Ovarian Serous Cystadenocarcinoma (Primary solid tumor)
22 February 2013  |  analyses__2013_02_22
Maintainer Information
Citation Information
doi:10.7908/C14F1NZK
Maintained by Dan DiCara (Broad Institute)
Cite as Broad Institute TCGA Genome Data Analysis Center (2013): Mutation Analysis (MutSigCV v0.6). Broad Institute of MIT and Harvard. doi:10.7908/C14F1NZK
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. MutSigCV v0.6 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
Results
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: OV-TP.patients.counts_and_rates.txt

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

  • nflank = number of noncoding mutations from this gene's flanking region, across the individual set

  • 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: 6. 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).

gene Nnon Nsil Nflank nnon npat nsite nsil nflank nnei fMLE p score time q
TP53 298620 87216 0 279 276 143 3 0 4 3.7 2.8e-15 1000 0.4 5.1e-11
BRCA1 1441592 364348 0 12 12 12 0 0 14 0.82 1.4e-06 64 0.29 0.012
OR4F21 60988 18644 0 3 3 1 0 0 20 0.47 2.5e-06 22 0.26 0.015
PECAM1 6952 2528 0 2 2 2 0 0 20 0 3.3e-06 14 0.21 0.015
RB1 899968 237316 0 9 9 9 0 0 20 0.64 6.7e-06 42 0.29 0.024
NF1 2974192 833608 0 15 14 15 0 0 0 0 0.000024 59 0.3 0.072
POTED 101752 23384 0 4 4 4 0 0 16 0.6 0.00011 18 0.26 0.29
GPRIN3 561532 173484 0 5 5 5 0 0 20 0 0.00026 18 0.26 0.59
GPX6 169692 45188 0 3 3 3 0 0 20 0.18 0.00036 15 0.25 0.68
FAM200A 47716 12640 0 2 2 2 0 0 20 0 0.00037 9.7 0.22 0.68
DUSP19 164952 44872 0 4 4 4 0 0 20 0.38 0.00048 15 0.25 0.71
PAK3 417120 113760 0 5 5 5 0 0 11 0.24 0.00049 20 0.27 0.71
C1orf95 75208 22752 0 3 3 3 0 0 20 0.46 0.0005 15 0.26 0.71
CHMP4A 285348 76472 0 3 3 3 0 0 20 0 0.00088 12 0.24 1
LCOR 321372 91640 0 4 4 4 0 0 3 0.3 0.00093 19 0.27 1
BDKRB1 253748 81212 0 4 4 4 0 0 20 0.18 0.00096 15 0.25 1
AOC2 626944 206032 0 4 4 4 1 0 20 0.25 0.0015 22 0.27 1
NALCN 1334152 360556 0 8 8 8 0 0 9 0 0.0016 25 0.3 1
MADD 1279484 367508 0 6 6 6 0 0 7 0 0.0017 25 0.31 1
TBP 249640 70468 0 4 4 2 0 0 20 2 0.0021 25 0.28 1
DAD1 82476 26544 0 2 2 2 0 0 20 0.94 0.0022 14 0.25 1
FAP 591236 149468 0 4 4 4 0 0 16 0.24 0.0026 19 0.27 1
TAS2R1 219304 64148 0 3 3 3 0 0 9 0 0.0026 14 0.25 1
PAOX 338120 83740 0 4 4 4 0 0 20 0.46 0.0026 19 0.27 1
HIST1H1C 151996 50560 0 4 4 4 0 0 9 0 0.0027 17 0.26 1
UTP14A 582704 159264 0 4 4 4 0 0 20 0.58 0.0028 22 0.27 1
ZNF706 60040 14536 0 2 2 2 0 0 20 1.5 0.0029 12 0.25 1
NXPH2 184228 50560 0 3 2 3 0 0 20 0.39 0.0035 13 0.25 1
CDK12 1078824 325796 0 9 9 9 0 0 20 1.2 0.0037 40 0.31 1
LRP1B 3540464 884168 0 14 13 14 0 0 6 0 0.0037 35 0.3 1
HHATL 383940 117236 0 4 4 4 0 0 9 0 0.0045 14 0.25 1
RAB26 109020 30020 0 3 2 3 0 0 20 0.3 0.0045 11 0.23 1
RTN2 352972 120080 0 5 5 4 1 0 20 0.45 0.0046 17 0.27 1
EPDR1 214880 64148 0 3 3 3 2 0 20 0.42 0.005 14 0.26 1
RUFY1 466416 116604 0 5 5 5 0 0 20 0.29 0.0052 16 0.26 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

This is an experimental feature. The full results of the analysis summarized in this report can be downloaded from the TCGA Data Coordination Center.

References
[1] TCGA, Integrated genomic analyses of ovarian carcinoma, Nature 474:609 - 615 (2011)
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