Mutation Analysis (MutSigCV v0.9)
Rectum Adenocarcinoma (Primary solid tumor)
21 August 2015  |  analyses__2015_08_21
Maintainer Information
Citation Information
doi:10.7908/C1N8793F
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/C1N8793F
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: READ-TP

  • Number of patients in set: 122

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:READ-TP.final_analysis_set.maf

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

  • Significantly mutated genes (q ≤ 0.1): 14

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: READ-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: 14. 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 115290 33672 2266 108 91 70 5 0 4 3.5 2.1e-15 250 0.094 3.2e-11
KRAS 73810 18056 1166 63 63 14 3 1 1 8 3.9e-15 130 0.095 3.2e-11
APC 813984 228140 3201 191 108 136 25 0 4 8.2 5.2e-15 430 0.096 3.2e-11
PTEN 118828 28548 1914 47 33 46 21 0 20 4 8.2e-15 92 0.093 3.4e-11
SMAD4 161528 45018 2442 25 25 22 9 0 20 2 9.2e-15 78 0.093 3.4e-11
FBXW7 236924 65026 2629 38 28 33 11 1 20 3.2 5.4e-14 84 0.093 1.6e-10
VHL 36844 11590 484 22 17 22 4 0 13 1.7 3.6e-13 55 0.092 9.4e-10
PIK3CA 317078 81130 4356 56 37 47 16 0 20 3.1 2.7e-12 83 0.093 6.2e-09
CRIPAK 120048 39894 253 13 11 8 1 0 20 1.3 5.4e-11 52 0.09 1.1e-07
MUC4 555344 180072 4422 34 25 19 4 0 2 1.8 4.9e-09 100 0.096 8.9e-06
TCF7L2 181170 51118 3003 12 12 11 1 1 20 1.2 2.8e-08 49 0.091 0.000047
NRAS 56242 14884 902 11 11 6 1 0 20 0.94 9.1e-08 33 0.088 0.00014
CTNNB1 224358 67100 3102 21 19 19 6 0 20 1.8 4.5e-06 44 0.091 0.0063
BRAF 210694 60146 3729 14 13 11 5 0 19 1.4 0.000011 38 0.091 0.015
RB1 347456 91622 5346 16 14 15 9 0 20 1.6 0.00011 39 0.091 0.13
KIT 287676 78080 4609 22 16 21 9 0 20 2.3 0.00025 41 0.092 0.29
SOX9 114924 33794 572 6 5 6 0 0 20 1.2 0.00037 26 0.089 0.4
RBM10 188368 53314 3344 6 6 5 0 0 16 0.41 0.00039 32 0.092 0.4
ELF3 108458 29768 1738 4 4 4 0 0 20 0.95 0.00062 23 0.089 0.6
SPRR2E 20984 5734 264 3 3 2 0 0 20 0.89 0.0019 11 0.079 1
PDCD5 32696 7808 1122 3 3 2 0 0 20 0 0.0022 10 0.076 1
ZFP36L2 61732 19886 176 3 3 3 0 0 20 0.96 0.0026 18 0.09 1
CDH1 238388 70882 3806 12 12 12 2 0 20 1.8 0.0027 32 0.089 1
ADSS 127612 35380 2739 3 3 3 1 0 20 0.16 0.0033 9.7 0.074 1
PTPN11 176290 45262 3069 10 10 10 6 0 20 1.4 0.0044 23 0.09 1
NF2 156282 39406 3080 6 5 6 3 0 20 0.73 0.0059 20 0.09 1
TLR8 298778 81740 484 9 8 9 2 0 20 0.59 0.0059 23 0.087 1
MEMO1 81130 20740 1716 5 4 5 0 0 20 0.68 0.0063 13 0.08 1
TAGAP 211182 61976 2035 7 7 7 3 0 20 0.63 0.01 18 0.085 1
TAS2R10 87962 23912 264 4 4 4 1 0 20 0.72 0.011 13 0.08 1
TPTE2 156282 40626 5709 5 5 5 0 0 14 0.65 0.011 20 0.088 1
PIK3R1 227408 58438 3795 11 8 11 1 0 20 2.4 0.011 27 0.089 1
CEBPA 21594 6588 44 2 2 1 0 0 20 1.5 0.011 9.7 0.075 1
KIAA1804 220820 65270 1980 12 10 10 0 0 20 0.93 0.011 23 0.088 1
FGFR2 254980 71370 5643 11 8 11 2 0 18 1.1 0.012 23 0.09 1
TP53

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

KRAS

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

APC

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

PTEN

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

SMAD4

Figure S5.  This figure depicts the distribution of mutations and mutation types across the SMAD4 significant gene.

FBXW7

Figure S6.  This figure depicts the distribution of mutations and mutation types across the FBXW7 significant gene.

VHL

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

PIK3CA

Figure S8.  This figure depicts the distribution of mutations and mutation types across the PIK3CA significant gene.

CRIPAK

Figure S9.  This figure depicts the distribution of mutations and mutation types across the CRIPAK significant gene.

MUC4

Figure S10.  This figure depicts the distribution of mutations and mutation types across the MUC4 significant gene.

TCF7L2

Figure S11.  This figure depicts the distribution of mutations and mutation types across the TCF7L2 significant gene.

NRAS

Figure S12.  This figure depicts the distribution of mutations and mutation types across the NRAS significant gene.

CTNNB1

Figure S13.  This figure depicts the distribution of mutations and mutation types across the CTNNB1 significant gene.

BRAF

Figure S14.  This figure depicts the distribution of mutations and mutation types across the BRAF 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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