Mutation Analysis (MutSigCV v0.9)
Prostate Adenocarcinoma (Primary solid tumor)
28 January 2016  |  analyses__2016_01_28
Maintainer Information
Citation Information
doi:10.7908/C1T72GW4
Maintained by David Heiman (Broad Institute)
Cite as Broad Institute TCGA Genome Data Analysis Center (2016): Mutation Analysis (MutSigCV v0.9). Broad Institute of MIT and Harvard. doi:10.7908/C1T72GW4
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: 498

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): 9

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: 9. 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 470610 137448 102382 60 57 45 0 0 4 1.9 3e-15 210 0.44 5.3e-11
FOXA1 406368 119022 21371 29 28 20 3 0 20 1.5 5.8e-15 140 0.51 5.3e-11
PTEN 485052 116532 86478 17 17 17 0 0 20 0.36 1.5e-14 98 0.51 7.5e-11
SPOP 455670 119520 91448 58 57 19 0 0 20 0.7 1.6e-14 210 0.48 7.5e-11
CDKN1B 231570 64242 86478 6 6 6 0 0 20 0.42 8.3e-09 40 0.48 3e-05
ZMYM3 1305258 374496 168483 13 12 13 0 0 20 0.98 7.7e-07 54 0.58 0.0023
LMOD2 438738 124002 10437 6 6 4 0 0 20 0.68 4e-06 34 0.48 0.01
EMG1 338640 103086 61131 4 4 2 0 0 20 0.87 0.000031 27 0.65 0.071
CTNNB1 915822 273900 140154 13 13 10 0 0 20 1.1 0.000037 39 0.46 0.074
LCE2D 128484 36852 11928 4 4 4 0 0 20 0.73 0.000055 19 0.41 0.1
CDK12 1700172 513438 132202 14 9 14 1 0 20 0.71 8e-05 45 0.5 0.13
GATA6 311250 102090 43736 4 4 2 0 0 20 0.96 0.00014 27 0.62 0.2
PIK3CA 1294302 331170 196812 16 14 13 2 0 20 1.3 0.00014 41 0.47 0.2
LMTK2 1715610 490530 128226 9 9 9 0 0 20 0.29 0.00015 38 0.48 0.2
BHLHE22 128982 43824 4970 3 3 2 0 0 20 1.2 0.00019 21 0.53 0.23
DLX6 160854 46314 11928 3 3 3 0 0 20 1.3 0.00021 21 0.44 0.24
ZFP36L2 251988 81174 7952 4 4 4 1 0 20 0.68 0.00033 23 0.79 0.34
BRAF 860046 245514 168483 8 8 7 0 0 19 0.71 0.00033 29 0.51 0.34
SLC10A2 407862 121512 61131 5 5 5 0 0 18 1 0.00036 21 0.44 0.34
ETV3 174798 43824 31808 5 5 5 0 0 11 1.5 0.00038 24 0.53 0.35
OR10R2 380970 118524 12425 5 5 5 0 1 20 0.66 0.0004 21 0.47 0.35
RYBP 251988 69720 30317 4 4 4 1 0 20 0.45 0.00042 19 0.4 0.35
NKX3-1 194220 58764 11928 5 5 5 0 0 11 1 0.00049 22 0.47 0.39
COL11A1 2131938 669312 631687 16 14 16 2 0 18 0.75 0.00053 47 0.49 0.4
CASZ1 1597086 477582 138663 9 8 9 0 0 20 0.41 0.00054 38 0.44 0.4
AADACL4 472602 141432 41251 7 7 7 1 0 20 0.77 0.0007 24 0.57 0.47
GTPBP10 468618 125496 99897 3 3 3 0 0 20 0.2 0.00072 19 0.43 0.47
MFGE8 431766 120018 69083 4 4 4 0 0 20 1.1 0.00072 23 0.5 0.47
FAM181B 99102 32370 4970 3 3 3 0 0 20 1 0.00077 17 0.42 0.47
SMARCA1 1258944 324198 223650 8 8 8 0 0 18 1.3 0.00077 39 0.43 0.47
SMG7 1347090 375492 208740 8 8 7 0 0 20 0.76 0.0008 34 0.44 0.47
RPL11 188244 51792 53179 4 4 4 0 0 20 1.1 0.00083 18 0.48 0.47
CHD1 2014908 495510 314601 9 8 9 3 0 14 0.66 0.00098 37 0.41 0.54
TMPRSS2 543816 151890 111825 5 5 5 2 0 20 1.2 0.001 26 0.53 0.55
ERF 547302 184260 36778 5 5 5 0 0 20 0.9 0.0011 26 0.43 0.57
TP53

Figure S1.  This figure depicts the distribution of mutations and mutation types across the TP53 significant gene.

FOXA1

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

PTEN

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

SPOP

Figure S4.  This figure depicts the distribution of mutations and mutation types across the SPOP 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.

LMOD2

Figure S7.  This figure depicts the distribution of mutations and mutation types across the LMOD2 significant gene.

CTNNB1

Figure S8.  This figure depicts the distribution of mutations and mutation types across the CTNNB1 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)
Copyright © 2016 Broad Institute TCGA GDAC as part of the TCGA Research Network. All rights reserved.
Made with Nozzle