Mutation Analysis (MutSigCV v0.9)
Head and Neck Squamous Cell Carcinoma (Primary solid tumor)
15 July 2014  |  analyses__2014_07_15
Maintainer Information
Citation Information
Maintained by David Heiman (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/C18K77TQ
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: 306

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): 32

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: 32. 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
CDKN2A 183760 52206 17278 66 65 31 0 0 6 0.86 5.6e-16 350 0.19 7.1e-12
TP53 289170 84456 58318 251 213 157 5 0 4 2.7 7.8e-16 810 0.2 7.1e-12
JUB 256420 75274 46034 19 18 19 1 0 20 0.93 1.8e-15 100 0.18 1.1e-11
CASP8 445542 104346 61334 27 27 24 0 0 20 0.98 3.4e-15 120 0.18 1.5e-11
PIK3CA 795320 203494 114004 65 64 24 0 0 20 0.87 4e-15 170 0.19 1.5e-11
NSD1 1941890 548966 128652 38 33 38 1 0 20 0.47 6.2e-15 140 0.18 1.9e-11
NOTCH1 1222568 353330 108278 62 57 62 5 0 20 0.94 7.5e-15 220 0.18 1.9e-11
FAT1 3253530 940598 112726 86 69 85 2 0 2 0.76 8.3e-15 300 0.18 1.9e-11
MLL2 3240448 1071186 221792 58 53 58 3 0 20 0.87 9.5e-15 220 0.19 1.9e-11
EPHA2 653074 193720 81972 16 13 15 0 0 16 0.47 5.9e-10 70 0.18 1.1e-06
B2M 87826 24480 18704 7 7 6 0 0 20 0.77 1.5e-09 38 0.17 2.4e-06
FLG 2811614 834488 12826 57 47 57 9 0 15 0.93 1.3e-08 110 0.18 0.000019
NFE2L2 431158 114138 23150 18 17 13 0 0 20 0.77 5.5e-08 50 0.19 0.000077
FBXW7 594264 163100 68862 16 15 14 1 0 20 0.83 1.2e-07 54 0.18 0.00016
ZNF750 502148 161568 12612 15 13 14 1 0 20 1.3 5.5e-07 58 0.19 0.00066
HRAS 141730 41018 24392 11 10 6 0 0 20 0.62 5.8e-07 34 0.17 0.00066
HLA-A 250900 75882 44384 9 9 8 2 0 20 2 7.5e-07 51 0.18 0.0008
NECAB1 153276 37936 25928 7 6 7 2 0 20 0.83 1e-06 32 0.18 0.001
CSMD3 2722284 760742 411484 89 70 88 17 0 5 2.9 1.1e-06 150 0.19 0.0011
RB1 871544 229820 143534 10 10 10 2 0 20 0.61 1.3e-06 51 0.18 0.0012
TGFBR2 416168 111692 68112 11 10 9 1 0 20 1.4 1.7e-06 49 0.18 0.0015
CTCF 539786 138312 58572 13 11 13 1 0 20 0.91 5.8e-06 46 0.18 0.0048
EP300 1751544 492046 181108 24 24 21 1 0 20 0.82 1e-05 72 0.18 0.0082
RAC1 145352 43758 34722 10 9 8 0 0 20 1.1 0.000015 29 0.18 0.012
STEAP4 326810 97920 22768 10 10 10 1 0 16 1.2 0.000033 38 0.19 0.024
PRB1 141608 48852 17918 8 7 7 1 0 12 1.8 0.000036 30 0.17 0.025
CUL3 559700 143520 86570 10 10 10 1 0 20 0.65 0.000065 37 0.18 0.044
PLSCR4 237158 63956 40236 7 7 7 1 0 20 0.84 0.000084 27 0.17 0.055
KRT5 419210 127598 53246 9 8 9 1 0 20 1.1 0.000087 38 0.18 0.055
FCRL4 372712 111998 70450 14 13 14 1 0 16 0.96 0.0001 37 0.18 0.064
HIST1H1B 156370 51104 6588 7 7 7 2 0 20 1.1 0.00014 28 0.17 0.085
SLC26A7 498496 137400 110140 8 8 8 1 0 20 1.2 0.00016 37 0.17 0.094
EPB41L3 791300 228576 122432 16 16 16 5 0 16 1.1 0.00021 48 0.19 0.11
CSNK2A1 292544 77114 68618 6 6 6 0 0 13 1.2 0.00033 30 0.18 0.18
PEX11A 163098 48960 13144 5 5 5 0 0 20 0.53 0.00035 20 0.17 0.18
CDKN2A

Figure S1.  This figure depicts the distribution of mutations and mutation types across the CDKN2A significant gene.

TP53

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

JUB

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

PIK3CA

Figure S4.  This figure depicts the distribution of mutations and mutation types across the PIK3CA significant gene.

NSD1

Figure S5.  This figure depicts the distribution of mutations and mutation types across the NSD1 significant gene.

NOTCH1

Figure S6.  This figure depicts the distribution of mutations and mutation types across the NOTCH1 significant gene.

FAT1

Figure S7.  This figure depicts the distribution of mutations and mutation types across the FAT1 significant gene.

MLL2

Figure S8.  This figure depicts the distribution of mutations and mutation types across the MLL2 significant gene.

EPHA2

Figure S9.  This figure depicts the distribution of mutations and mutation types across the EPHA2 significant gene.

B2M

Figure S10.  This figure depicts the distribution of mutations and mutation types across the B2M significant gene.

FLG

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

NFE2L2

Figure S12.  This figure depicts the distribution of mutations and mutation types across the NFE2L2 significant gene.

FBXW7

Figure S13.  This figure depicts the distribution of mutations and mutation types across the FBXW7 significant gene.

ZNF750

Figure S14.  This figure depicts the distribution of mutations and mutation types across the ZNF750 significant gene.

HRAS

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

HLA-A

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

NECAB1

Figure S17.  This figure depicts the distribution of mutations and mutation types across the NECAB1 significant gene.

CSMD3

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

RB1

Figure S19.  This figure depicts the distribution of mutations and mutation types across the RB1 significant gene.

TGFBR2

Figure S20.  This figure depicts the distribution of mutations and mutation types across the TGFBR2 significant gene.

CTCF

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

EP300

Figure S22.  This figure depicts the distribution of mutations and mutation types across the EP300 significant gene.

RAC1

Figure S23.  This figure depicts the distribution of mutations and mutation types across the RAC1 significant gene.

STEAP4

Figure S24.  This figure depicts the distribution of mutations and mutation types across the STEAP4 significant gene.

PRB1

Figure S25.  This figure depicts the distribution of mutations and mutation types across the PRB1 significant gene.

CUL3

Figure S26.  This figure depicts the distribution of mutations and mutation types across the CUL3 significant gene.

PLSCR4

Figure S27.  This figure depicts the distribution of mutations and mutation types across the PLSCR4 significant gene.

KRT5

Figure S28.  This figure depicts the distribution of mutations and mutation types across the KRT5 significant gene.

FCRL4

Figure S29.  This figure depicts the distribution of mutations and mutation types across the FCRL4 significant gene.

HIST1H1B

Figure S30.  This figure depicts the distribution of mutations and mutation types across the HIST1H1B significant gene.

SLC26A7

Figure S31.  This figure depicts the distribution of mutations and mutation types across the SLC26A7 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)