Mutation Analysis (MutSigCV v0.9)
Thyroid Adenocarcinoma (Primary solid tumor)
28 January 2016  |  analyses__2016_01_28
Maintainer Information
Citation Information
doi:10.7908/C1377862
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/C1377862
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: THCA-TP

  • Number of patients in set: 496

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:THCA-TP.final_analysis_set.maf

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

  • Significantly mutated genes (q ≤ 0.1): 12

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: THCA-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: 12. 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
BRAF 856592 244528 168144 291 291 3 2 0 19 1.4 0 980 0.52 0
NRAS 228656 60512 40672 40 40 2 0 0 20 0 0 160 0.47 0
EMG1 337280 102672 61008 11 11 2 0 0 20 0.51 3.1e-15 76 0.54 1.9e-11
HRAS 229648 66464 42656 17 17 2 0 0 20 1.9 4.3e-15 65 0.47 2e-11
DLX6 160208 46128 11904 7 7 3 0 0 20 1.5 2e-12 49 0.61 7.3e-09
EIF1AX 175584 41168 59520 9 7 7 0 0 20 1 8.9e-09 35 0.49 0.000027
TMEM184A 388864 118048 54064 5 5 1 0 0 20 1.2 1.2e-06 33 0.58 0.0032
PPM1D 600656 172112 78368 6 6 6 0 0 20 1.3 3.8e-06 36 0.51 0.0086
GYPE 89776 26784 23808 3 3 1 0 0 20 1.3 6.9e-06 22 0.5 0.014
RPTN 949840 217744 21824 11 10 6 1 0 5 3.7 0.000016 54 0.44 0.029
NDUFAF2 194928 51584 46624 3 3 1 0 0 20 0.56 0.000018 21 0.48 0.029
TG 3516640 1023744 521296 21 21 21 5 0 7 3.1 0.000021 90 0.52 0.032
CRIPAK 488064 162192 11408 4 4 4 0 0 20 0.74 0.00089 18 0.46 1
COTL1 107136 29264 20336 2 2 1 0 0 20 1.5 0.0011 14 0.38 1
ABL1 1282160 391344 123008 5 5 2 1 0 20 0.33 0.0014 29 0.42 1
CLIC6 290160 77376 52576 3 3 2 0 0 20 1.1 0.0014 17 0.47 1
BHLHE22 128464 43648 4960 2 2 2 0 0 20 0.8 0.002 14 0.47 1
SIKE1 253952 64976 49104 2 2 2 0 0 20 0.7 0.0021 14 0.53 1
TBC1D12 538160 144832 109120 4 4 2 0 0 5 1.3 0.0021 25 0.46 1
TMSB15A 57040 13392 21824 2 2 2 0 0 20 1.4 0.0026 8.9 0.5 1
MSI1 274784 81840 86304 3 3 3 0 0 20 0.86 0.0033 15 0.47 1
OR3A3 310992 100192 13392 3 3 3 0 0 20 0 0.0035 12 0.39 1
RAB27A 266848 69936 51088 2 2 2 0 0 20 0.28 0.0038 11 0.58 1
ARID3A 376464 115568 50592 4 4 4 0 0 20 2.2 0.0039 20 0.46 1
ADO 107632 35712 496 2 2 2 0 0 20 0.25 0.004 8.9 0.79 1
NUP93 981584 275280 209312 4 4 2 0 0 20 0.34 0.004 23 0.48 1
GJA3 188976 56544 3968 2 2 2 0 0 19 1.3 0.0042 14 0.4 1
SUMO3 119040 29760 30752 3 3 1 0 0 20 2.2 0.0042 12 0.57 1
S100A7 124992 28768 21824 3 3 3 0 0 20 1.9 0.0043 12 0.4 1
SHANK1 1119472 360096 165664 6 6 6 0 0 12 0.7 0.0048 33 0.52 1
EIF3F 391840 125488 78864 4 4 4 0 0 20 0.89 0.0054 17 0.41 1
DNMT3A 1027712 285200 215264 5 5 5 0 0 18 0.96 0.0062 28 0.54 1
TCF7L1 533696 171120 99696 4 4 4 1 0 20 1.7 0.0064 19 0.59 1
MUC7 410688 152768 21824 3 3 3 1 0 20 1.1 0.0064 14 0.59 1
GATA5 143840 47616 22816 2 2 2 0 0 20 0.38 0.0067 11 0.41 1
BRAF

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

NRAS

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

HRAS

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

DLX6

Figure S4.  This figure depicts the distribution of mutations and mutation types across the DLX6 significant gene.

EIF1AX

Figure S5.  This figure depicts the distribution of mutations and mutation types across the EIF1AX significant gene.

TMEM184A

Figure S6.  This figure depicts the distribution of mutations and mutation types across the TMEM184A significant gene.

PPM1D

Figure S7.  This figure depicts the distribution of mutations and mutation types across the PPM1D significant gene.

RPTN

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

TG

Figure S9.  This figure depicts the distribution of mutations and mutation types across the TG 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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