Mutation Analysis (MutSigCV v0.9)
Prostate Adenocarcinoma (Primary solid tumor)
02 April 2015  |  analyses__2015_04_02
Maintainer Information
Citation Information
doi:10.7908/C1GT5M75
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/C1GT5M75
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: PRAD-TP

  • Number of patients in set: 425

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:PRAD-TP.final_analysis_set.maf

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

  • Significantly mutated genes (q ≤ 0.1): 7

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: PRAD-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: 7. 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
SPOP 388875 102000 77280 49 48 15 0 0 20 0.54 3.3e-16 180 0.51 6.1e-12
FOXA1 346800 101575 18060 26 25 18 2 0 20 2 5e-15 120 0.46 4.6e-11
TP53 401625 117300 86520 44 43 34 0 0 4 1.1 1.6e-14 160 0.47 8.5e-11
PTEN 413950 99450 73080 14 14 14 0 0 20 0.43 1.9e-14 79 0.44 8.5e-11
CDKN1B 197625 54825 73080 5 5 5 0 0 20 0.51 3.3e-07 33 0.59 0.0012
ZMYM3 1113925 319600 142380 10 9 10 0 0 20 0.87 8.8e-06 44 0.6 0.027
EMG1 289000 87975 51660 4 4 2 0 0 20 0.85 0.000016 27 0.43 0.041
LCE2D 109650 31450 10080 4 4 4 0 0 20 0.93 0.000047 19 0.7 0.11
SLC10A2 348075 103700 51660 5 5 5 0 0 18 0.95 0.00011 21 0.43 0.21
LMOD2 374425 105825 8820 5 5 3 0 0 20 1 0.00012 26 0.56 0.21
OR10R2 325125 101150 10500 5 5 5 0 0 20 0.4 0.00015 21 0.49 0.21
BHLHE22 110075 37400 4200 3 3 2 0 0 20 1.5 0.00016 21 0.56 0.21
CTNNB1 781575 233750 118440 11 11 8 0 0 20 1.4 0.00016 34 0.59 0.21
BRAF 733975 209525 142380 8 8 7 0 0 19 0.63 0.00016 29 0.86 0.21
NKX3-1 165750 50150 10080 5 5 5 0 0 11 0.72 0.00018 22 0.51 0.22
DLX6 137275 39525 10080 3 3 3 0 0 20 1.6 0.00021 20 0.42 0.24
CASZ1 1362975 407575 117180 7 7 7 0 0 20 0.37 0.00032 37 0.54 0.32
CDK12 1450950 438175 111720 12 8 12 1 0 20 0.18 0.00032 34 0.6 0.32
LMTK2 1464125 418625 108360 7 7 7 0 0 20 0 0.00033 31 0.51 0.32
RPL11 160650 44200 44940 4 4 4 0 0 20 1 0.00038 18 0.42 0.34
PIK3CA 1104575 282625 166320 12 11 11 2 0 20 1.3 0.00046 34 0.46 0.4
MFGE8 368475 102425 58380 4 4 4 0 0 20 1.2 0.00049 22 0.52 0.41
RYBP 215050 59500 25620 4 4 4 1 0 20 0.8 0.00057 18 0.58 0.46
SMG7 1149625 320450 176400 7 7 6 0 0 20 0.78 0.00061 32 0.48 0.46
FAM181B 84575 27625 4200 3 3 3 0 0 20 1.3 0.00071 16 0.48 0.5
HRAS 196775 56950 36120 5 5 3 0 0 20 0.76 0.00071 18 0.46 0.5
PBX4 300050 85850 48300 4 4 4 0 0 20 0.76 0.00091 20 0.66 0.61
MED15 739075 211225 139860 6 6 6 0 0 20 0.94 0.00095 26 0.47 0.62
MYOT 505325 140675 75600 4 4 4 0 0 13 0 0.0011 18 0.45 0.67
CD200R1L 273700 80750 52080 3 3 3 1 0 20 0.2 0.0012 15 0.45 0.71
ATP6V1C2 463250 128350 116760 5 5 5 0 0 20 0.69 0.0012 20 0.48 0.73
AADACL4 403325 120700 34860 6 6 6 1 0 20 0.92 0.0013 22 0.57 0.76
HDGFL1 97325 25075 5040 2 2 1 0 0 20 1.5 0.0017 14 0.39 0.94
IL6ST 937550 249900 136500 6 5 6 0 0 7 0 0.0018 25 0.56 0.94
ZCCHC10 171275 44200 32760 2 2 2 0 0 20 0.51 0.0019 13 0.42 1
SPOP

Figure S1.  This figure depicts the distribution of mutations and mutation types across the SPOP significant gene.

FOXA1

Figure S2.  This figure depicts the distribution of mutations and mutation types across the FOXA1 significant gene.

TP53

Figure S3.  This figure depicts the distribution of mutations and mutation types across the TP53 significant gene.

PTEN

Figure S4.  This figure depicts the distribution of mutations and mutation types across the PTEN significant gene.

CDKN1B

Figure S5.  This figure depicts the distribution of mutations and mutation types across the CDKN1B significant gene.

ZMYM3

Figure S6.  This figure depicts the distribution of mutations and mutation types across the ZMYM3 significant gene.

EMG1

Figure S7.  This figure depicts the distribution of mutations and mutation types across the EMG1 significant gene.

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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