Mutation Analysis (MutSigCV v0.9)
Colorectal Adenocarcinoma (Primary solid tumor)
15 January 2014  |  analyses__2014_01_15
Maintainer Information
Citation Information
doi:10.7908/C1GM85Q4
Maintained by Dan DiCara (Broad Institute)
Cite as Broad Institute TCGA Genome Data Analysis Center (2014): Mutation Analysis (MutSigCV v0.9). Broad Institute of MIT and Harvard. doi:10.7908/C1GM85Q4
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: COADREAD-TP

  • Number of patients in set: 227

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). 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: COADREAD-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: 15. 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
APC 1514544 424490 291 257 167 158 4 0 4 0.73 0 780 0.13 0
TP53 214515 62652 206 123 121 69 2 0 4 0.98 3e-15 400 0.13 2.7e-11
KRAS 137335 33596 106 98 98 12 0 0 1 0 4.7e-15 230 0.14 2.8e-11
FBXW7 440834 120991 239 48 40 28 2 1 20 1.4 1.2e-14 120 0.13 4.9e-11
NRAS 104647 27694 82 21 21 8 0 0 20 0.65 1.3e-14 67 0.13 4.9e-11
SMAD4 300548 83763 222 31 27 23 0 0 20 1 6.3e-14 84 0.13 1.9e-10
FAM123B 562052 166618 98 27 25 24 3 0 20 1.8 1.5e-12 110 0.13 4e-09
PIK3CA 589973 150955 396 40 33 21 2 0 20 1.3 3.4e-08 76 0.13 0.000079
SMAD2 253559 70824 199 17 16 12 1 0 20 1.2 1.2e-07 54 0.14 0.00023
TCF7L2 337095 95113 273 20 18 18 5 0 20 1.5 2e-07 63 0.13 0.00036
SOX9 213834 62879 52 11 10 11 0 0 20 1.3 2.1e-07 55 0.13 0.00036
ACVR2A 282388 74456 222 14 11 10 1 0 10 0.84 5.5e-07 49 0.13 0.00084
ELF3 201803 55388 158 8 8 7 0 0 20 0.75 2e-06 42 0.13 0.0028
BRAF 392029 111911 339 23 22 4 0 0 19 1 5.4e-06 51 0.13 0.0071
CCDC160 88303 21338 5 10 7 10 0 0 20 1.3 0.000048 27 0.12 0.058
B2M 65149 18160 64 7 5 6 0 0 20 0.96 0.00011 23 0.12 0.13
KIAA1804 410870 121445 180 20 16 16 0 0 20 0.65 0.0002 42 0.13 0.21
ZNF593 37909 11350 43 4 4 4 0 0 20 0.66 0.00022 19 0.12 0.22
MYO1B 628790 162305 576 20 14 16 2 0 20 0.84 0.00025 49 0.14 0.24
CRTC1 294646 93070 274 6 6 3 1 0 20 0.45 0.0004 32 0.12 0.37
CDC27 442196 119629 351 18 15 10 6 0 20 1.1 0.00052 42 0.13 0.44
CASP14 123488 34504 102 11 9 8 0 0 20 1.2 0.00055 28 0.12 0.44
CASP8 330512 77407 213 11 10 10 0 0 20 0.88 0.00056 35 0.13 0.44
AKT1S1 54707 16571 54 3 3 3 0 0 20 0.41 0.00066 16 0.11 0.49
PTEN 221098 53118 174 13 8 9 1 0 20 0.78 0.00067 29 0.13 0.49
ESR1 276259 78315 146 12 11 12 0 0 20 0.58 0.00074 31 0.12 0.52
ARL2BP 88984 22246 111 7 6 6 1 0 20 0.99 0.00085 22 0.12 0.57
MAPK10 261277 65830 358 9 9 8 1 0 16 0.8 0.00088 30 0.13 0.57
TXNDC3 329377 80131 294 14 11 14 2 0 20 1.3 0.00093 37 0.13 0.59
MAP7 366832 110095 334 11 11 10 0 0 20 0.84 0.001 37 0.13 0.61
MAPK9 251743 65376 230 7 7 6 1 0 20 0.5 0.0011 28 0.13 0.64
SAT1 94886 22700 117 4 4 2 0 0 20 1 0.0011 21 0.12 0.64
CCBP2 201349 60382 24 11 11 10 0 0 20 0.94 0.0012 27 0.12 0.67
MGC26647 134838 37228 24 7 7 7 0 0 13 1.5 0.0013 27 0.13 0.71
CPXM2 357071 99199 258 13 11 12 1 0 19 0.72 0.0015 34 0.13 0.79
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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