Mutation Analysis (MutSigCV v0.9)
Head and Neck Squamous Cell Carcinoma (Primary solid tumor)
21 August 2015  |  analyses__2015_08_21
Maintainer Information
Citation Information
doi:10.7908/C1MK6C3P
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/C1MK6C3P
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: HNSC-TP

  • Number of patients in set: 510

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:HNSC-TP.final_analysis_set.maf

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

  • Significantly mutated genes (q ≤ 0.1): 94

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: HNSC-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: 94. 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
NOTCH1 2036430 588540 182780 96 87 93 9 0 20 0.84 0 350 0.35 0
TP53 481950 140760 99086 436 359 216 5 0 4 1.6 3.3e-16 1500 0.37 3e-12
PIK3CA 1325490 339150 190476 96 94 35 1 0 20 1.1 2.9e-15 260 0.33 1.2e-11
HRAS 236130 68340 41366 32 29 9 0 0 20 0.85 3.1e-15 99 0.33 1.2e-11
CDKN2A 307020 87210 29822 117 112 54 1 0 6 0.78 3.2e-15 620 0.34 1.2e-11
FAT1 5422830 1567740 187109 143 114 132 11 0 2 1.3 5.3e-15 480 0.35 1.4e-11
HLA-A 418200 126480 74074 24 22 21 4 0 20 1.6 6.1e-15 110 0.33 1.4e-11
NSD1 3236460 914940 209716 79 63 78 2 0 20 0.71 6.2e-15 270 0.38 1.4e-11
FBXW7 990420 271830 114959 35 33 26 4 0 20 0.7 8.1e-15 140 0.34 1.6e-11
CASP8 742560 173910 102453 63 55 50 1 0 20 0.87 9.3e-15 260 0.35 1.7e-11
EPHA2 1088340 322830 137085 29 24 26 2 0 16 1.1 2.6e-13 120 0.41 4.3e-10
ZNF750 836910 269280 21164 24 21 22 1 0 20 0.98 6.8e-13 99 0.33 1e-09
PTEN 496740 119340 83694 14 14 14 0 0 20 0.53 8.7e-13 70 0.32 1.2e-09
TGFBR2 693600 186150 115440 25 23 16 2 0 20 1.4 1.6e-11 91 0.33 2.1e-08
B2M 146370 40800 30784 10 9 9 0 0 20 0.74 1.8e-11 51 0.32 2.1e-08
RB1 1452480 383010 233766 18 18 18 2 0 20 0.72 1.6e-10 87 0.35 1.9e-07
NFE2L2 718590 190230 38961 27 26 18 2 0 20 1.1 2.3e-10 77 0.33 2.4e-07
FLG 4685880 1390770 21164 86 70 84 23 0 15 1.2 4e-10 170 0.35 4e-07
CSMD3 4536960 1267860 683982 143 108 140 30 2 5 3.1 7.8e-10 250 0.35 7.5e-07
RAC1 242250 72930 56758 15 14 8 0 1 20 0.79 6.6e-09 47 0.32 6e-06
EP300 2919240 820080 300144 39 39 32 1 0 20 0.93 1.6e-08 120 0.35 0.000014
C6 1157700 300390 164502 25 23 25 2 0 9 0.85 1.8e-08 86 0.33 0.000015
DST 8014140 2068050 3569982 71 57 70 17 0 0 0.6 5.7e-08 150 0.35 0.000046
CTCF 899640 230520 96681 18 16 18 2 0 20 0.73 1.1e-07 63 0.33 0.000084
HLA-B 378420 115770 54834 26 24 21 1 0 1 2.1 1.4e-07 100 0.34 0.0001
CUL3 932790 239190 143819 14 14 14 1 0 20 0.49 1.6e-07 57 0.34 0.00011
ZFP36L2 258060 83130 7696 8 8 8 2 0 20 0.83 3.5e-07 45 0.4 0.00024
COL11A1 2183310 685440 611351 68 47 67 11 1 18 2.3 3.8e-07 130 0.35 0.00025
FCRL4 621180 186660 116402 18 17 18 3 0 16 0.87 4e-07 58 0.37 0.00025
SMAD4 675240 188190 106782 14 13 14 1 1 20 0.68 9.1e-07 52 0.33 0.00056
ADCY8 1361700 402390 170274 28 28 28 8 0 15 1.3 1.4e-06 82 0.34 0.00082
HUWE1 4846530 1429530 796055 48 45 44 5 0 8 0.7 2.9e-06 120 0.33 0.0016
NECAB1 255510 63240 43290 8 7 8 3 0 20 0.93 4.4e-06 36 0.32 0.0025
RELN 4240650 1142400 627224 53 49 53 12 0 14 1.1 4.7e-06 130 0.34 0.0025
CCDC7 579360 138720 143819 10 10 10 0 0 11 0.38 0.000011 39 0.32 0.0059
NOTCH1

Figure S1.  This figure depicts the distribution of mutations and mutation types across the NOTCH1 significant gene.

TP53

Figure S2.  This figure depicts the distribution of mutations and mutation types across the TP53 significant gene.

PIK3CA

Figure S3.  This figure depicts the distribution of mutations and mutation types across the PIK3CA significant gene.

HRAS

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

CDKN2A

Figure S5.  This figure depicts the distribution of mutations and mutation types across the CDKN2A significant gene.

FAT1

Figure S6.  This figure depicts the distribution of mutations and mutation types across the FAT1 significant gene.

HLA-A

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

NSD1

Figure S8.  This figure depicts the distribution of mutations and mutation types across the NSD1 significant gene.

FBXW7

Figure S9.  This figure depicts the distribution of mutations and mutation types across the FBXW7 significant gene.

EPHA2

Figure S10.  This figure depicts the distribution of mutations and mutation types across the EPHA2 significant gene.

ZNF750

Figure S11.  This figure depicts the distribution of mutations and mutation types across the ZNF750 significant gene.

PTEN

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

TGFBR2

Figure S13.  This figure depicts the distribution of mutations and mutation types across the TGFBR2 significant gene.

B2M

Figure S14.  This figure depicts the distribution of mutations and mutation types across the B2M significant gene.

RB1

Figure S15.  This figure depicts the distribution of mutations and mutation types across the RB1 significant gene.

NFE2L2

Figure S16.  This figure depicts the distribution of mutations and mutation types across the NFE2L2 significant gene.

FLG

Figure S17.  This figure depicts the distribution of mutations and mutation types across the FLG significant gene.

CSMD3

Figure S18.  This figure depicts the distribution of mutations and mutation types across the CSMD3 significant gene.

RAC1

Figure S19.  This figure depicts the distribution of mutations and mutation types across the RAC1 significant gene.

EP300

Figure S20.  This figure depicts the distribution of mutations and mutation types across the EP300 significant gene.

C6

Figure S21.  This figure depicts the distribution of mutations and mutation types across the C6 significant gene.

CTCF

Figure S22.  This figure depicts the distribution of mutations and mutation types across the CTCF significant gene.

HLA-B

Figure S23.  This figure depicts the distribution of mutations and mutation types across the HLA-B significant gene.

CUL3

Figure S24.  This figure depicts the distribution of mutations and mutation types across the CUL3 significant gene.

ZFP36L2

Figure S25.  This figure depicts the distribution of mutations and mutation types across the ZFP36L2 significant gene.

COL11A1

Figure S26.  This figure depicts the distribution of mutations and mutation types across the COL11A1 significant gene.

FCRL4

Figure S27.  This figure depicts the distribution of mutations and mutation types across the FCRL4 significant gene.

SMAD4

Figure S28.  This figure depicts the distribution of mutations and mutation types across the SMAD4 significant gene.

ADCY8

Figure S29.  This figure depicts the distribution of mutations and mutation types across the ADCY8 significant gene.

HUWE1

Figure S30.  This figure depicts the distribution of mutations and mutation types across the HUWE1 significant gene.

NECAB1

Figure S31.  This figure depicts the distribution of mutations and mutation types across the NECAB1 significant gene.

RELN

Figure S32.  This figure depicts the distribution of mutations and mutation types across the RELN 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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