Mutation Analysis (MutSigCV v0.9)
Ovarian Serous Cystadenocarcinoma (Primary solid tumor)
02 April 2015  |  analyses__2015_04_02
Maintainer Information
Citation Information
doi:10.7908/C1WQ02WV
Maintained by David Heiman (Broad Institute)
Cite as Broad Institute TCGA Genome Data Analysis Center (2015): Mutation Analysis (MutSigCV v0.9). Broad Institute of MIT and Harvard. doi:10.7908/C1WQ02WV
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: 473

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): 5

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). 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: OV-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:

  • 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: 5. 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 446985 130548 74778 398 394 175 2 0 4 2.9 0 1500 0.47 0
RB1 1347104 355223 176418 15 15 15 0 0 20 0.51 2e-13 77 0.38 1.8e-09
BRCA1 2157826 545369 162987 19 19 19 0 0 14 0.6 2.7e-12 100 0.41 1.7e-08
NF1 4451876 1247774 429792 27 25 26 0 0 0 0 8.3e-07 110 0.39 0.0038
PECAM1 10406 3784 34122 2 2 2 1 0 20 0.48 0.000026 13 0.27 0.094
IL21R 586520 176902 56628 8 8 8 0 0 20 1.4 0.00012 34 0.37 0.37
NRAS 218053 57706 29766 4 4 3 0 0 20 0.35 0.0002 19 0.33 0.52
TOP2A 1555224 396847 162624 9 9 8 1 0 20 0.55 0.00027 39 0.42 0.6
EFEMP1 566181 150887 72963 7 7 7 0 0 20 0.97 0.00041 29 0.36 0.82
DUSP19 246906 67166 30129 4 4 4 0 0 20 0.42 0.00074 16 0.32 1
PROKR2 422389 123453 16698 7 7 6 2 0 20 1.1 0.00079 24 0.38 1
PTEN 460702 110682 63162 5 5 5 0 0 20 1.5 0.0011 25 0.36 1
DAD1 123453 39732 15972 2 2 2 0 0 20 1 0.0012 14 0.33 1
ZNF706 89870 21758 15246 2 2 2 0 0 20 1.1 0.0012 12 0.3 1
UTP14A 872212 238392 108537 4 4 3 0 0 20 0.76 0.0013 25 0.41 1
GABRA6 512259 145211 66429 7 7 7 1 0 20 1.2 0.0015 23 0.35 1
TTN 39942958 11552079 2416128 109 90 107 20 0 9 1.2 0.0016 180 0.49 1
IL8 112101 31218 26499 3 3 3 0 0 20 1.6 0.0019 14 0.31 1
EMR3 736934 207174 114708 7 7 7 2 0 20 0.69 0.002 26 0.47 1
CRLS1 236027 69058 52272 3 3 2 0 0 20 1.1 0.0021 15 0.35 1
C20orf185 498542 178321 102003 6 5 6 1 0 20 0.77 0.0022 20 0.41 1
LYPD6B 216634 55341 30855 3 3 2 0 0 20 0.79 0.0022 15 0.32 1
TSPYL1 475365 142373 8712 4 4 4 0 0 20 1.1 0.0023 23 0.42 1
PPPDE1 222310 61017 37026 2 2 2 0 0 20 0.15 0.0023 8.8 0.24 1
FAM171B 899173 260150 56265 9 9 9 1 0 20 2.2 0.0025 33 0.61 1
DEFB118 137643 39732 15972 4 4 4 0 0 12 3 0.0025 19 0.36 1
GPR1 392117 112101 8712 4 4 4 0 0 20 1 0.0025 17 0.33 1
ITGA2B 954514 300355 172788 7 7 7 0 0 20 0.87 0.0026 27 0.46 1
CACNG6 180686 62909 26862 3 3 3 0 0 20 0.92 0.0027 17 0.39 1
EOMES 503745 143792 41382 5 5 5 0 0 20 1.1 0.0032 23 0.35 1
CTSL1 388806 96492 51183 4 4 4 0 0 20 0.71 0.0034 17 0.38 1
PPM1F 370832 117777 37389 5 5 4 0 0 20 0.62 0.0035 17 0.36 1
OR5AK2 340560 96492 9438 3 3 3 1 0 17 0.42 0.0036 17 0.36 1
C1orf95 112574 34056 28677 2 2 2 0 0 20 0.32 0.004 11 0.32 1
LASS3 447458 108317 70785 4 4 4 0 0 11 0.67 0.004 20 0.35 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)
Copyright © 2015 Broad Institute TCGA GDAC as part of the TCGA Research Network. All rights reserved.
Made with Nozzle