Ovarian Serous Cystadenocarcinoma: Mutation Analysis (MutSigCV v0.9)
(primary solid tumor cohort)
Maintained by Dan DiCara (Broad Institute)
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 v0.9 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: 1. 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 3.4e-15 990 0.29 6.3e-11
OR4F21 60988 18644 0 3 3 1 0 0 20 0.47 0.000014 21 0.2 0.1
PECAM1 6952 2528 0 2 2 2 0 0 20 0 0.000021 13 0.16 0.1
RB1 899968 237316 0 9 9 9 0 0 20 0.64 0.000022 41 0.22 0.1
BRCA1 1441592 364348 0 12 12 12 0 0 14 0.82 0.00021 61 0.24 0.75
POTED 101752 23384 0 4 4 4 0 0 16 0.6 0.00062 18 0.2 1
TBP 249640 70468 0 4 4 2 0 0 20 2 0.0016 25 0.21 1
C1orf95 75208 22752 0 3 3 3 0 0 20 0.46 0.0017 14 0.18 1
DAD1 82476 26544 0 2 2 2 0 0 20 0.94 0.0018 14 0.18 1
DUSP19 164952 44872 0 4 4 4 0 0 20 0.38 0.0019 14 0.19 1
ZNF706 60040 14536 0 2 2 2 0 0 20 1.5 0.0024 12 0.17 1
GPX6 169692 45188 0 3 3 3 0 0 20 0.18 0.0032 14 0.24 1
CDK12 1078824 325796 0 9 9 9 0 0 20 1.2 0.0032 39 0.22 1
FAM200A 47716 12640 0 2 2 2 0 0 20 0 0.0046 8.6 0.15 1
C10orf140 406060 119448 0 5 5 3 1 0 20 1.2 0.0055 24 0.22 1
UTP14A 582704 159264 0 4 4 4 0 0 20 0.58 0.0057 21 0.21 1
C9orf171 204452 62568 0 5 5 5 0 0 20 1.4 0.0067 18 0.2 1
FRG2 21172 4424 0 2 2 2 0 0 20 2 0.0068 7.8 0.15 1
BDKRB1 253748 81212 0 4 4 4 0 0 20 0.18 0.0072 14 0.19 1
PAK3 417120 113760 0 5 5 5 0 0 11 0.24 0.0075 19 0.21 1
GABRA6 342228 97012 0 6 6 6 1 0 20 0.97 0.0083 19 0.21 1
SLC10A2 258804 77104 0 2 2 2 1 0 18 0.81 0.0092 13 0.18 1
GPHB5 59092 20540 0 2 2 2 0 0 20 0.9 0.0099 8.1 0.15 1
NXPH2 184228 50560 0 3 2 3 0 0 20 0.39 0.011 13 0.2 1
OR6A2 236052 74260 0 4 4 4 0 0 20 0.74 0.011 13 0.19 1
PAOX 338120 83740 0 4 4 4 0 0 20 0.46 0.011 19 0.21 1
LCOR 321372 91640 0 4 4 4 0 0 3 0.3 0.012 19 0.2 1
C10orf113 116604 29388 0 3 3 3 0 0 20 0.97 0.013 11 0.18 1
FAM167B 72048 23068 0 2 2 2 0 0 20 1.2 0.015 10 0.18 1
CHST2 243636 81212 0 5 5 5 1 0 20 1.3 0.016 16 0.32 1
CBLN4 135564 42344 0 3 3 3 0 0 20 1 0.016 11 0.17 1
UIMC1 551104 146308 0 4 4 4 0 0 20 0.29 0.017 16 0.2 1
ACBD4 253748 36656 0 3 3 3 0 0 20 2 0.018 18 0.22 1
CACNG6 120712 42028 0 2 2 2 0 0 20 0.62 0.018 13 0.19 1
FAM24A 80896 21488 0 2 2 2 0 0 20 0.89 0.018 7.7 0.14 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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