Mutation Analysis (MutSigCV v0.9)
Skin Cutaneous Melanoma (Metastatic)
17 October 2014  |  analyses__2014_10_17
Maintainer Information
Citation Information
doi:10.7908/C1Q23Z57
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/C1Q23Z57
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: SKCM-TM

  • Number of patients in set: 278

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:SKCM-TM.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: SKCM-TM.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
NRAS 128158 33916 820 86 86 11 0 0 20 0.75 0 280 0.2 0
BRAF 480106 137054 3390 146 140 18 2 0 19 0.8 1.6e-15 370 0.2 1e-11
PCDHAC2 600202 190986 620 479 156 420 295 0 20 1.4 1.7e-15 300 0.2 1e-11
PTEN 270772 65052 1740 23 23 21 0 0 20 0.55 4.4e-15 110 0.2 2e-11
CDKN2A 167356 47538 620 42 41 19 1 0 6 0.6 6.2e-15 180 0.31 2.3e-11
TP53 262710 76728 2060 52 47 42 0 0 4 1 8.7e-15 160 0.2 2.4e-11
MRPS31 255204 69778 1310 20 19 5 0 0 20 0.66 9.3e-15 100 0.2 2.4e-11
PCDHGC5 594920 196546 730 354 141 329 248 0 5 5.6 3.8e-13 220 0.2 8.6e-10
BAGE 28356 7506 370 8 8 6 1 0 20 1.4 1.2e-11 52 0.19 2.4e-08
TMEM216 59492 18070 390 8 8 1 0 0 20 0.51 1.3e-11 52 0.2 2.4e-08
DSG1 688884 198492 3000 63 45 55 11 0 20 0.68 3.6e-09 96 0.2 5.9e-06
PPP6C 205164 56156 1310 21 20 15 3 0 20 0.81 8.9e-09 64 0.2 0.000013
SERPINB3 264378 66998 1430 58 42 49 17 0 10 1.7 1.1e-08 88 0.2 0.000016
MS4A2 164576 47816 1310 13 13 12 1 0 11 0.29 2.5e-08 47 0.19 0.000032
FAM113B 239080 76728 180 29 28 25 20 0 20 0.89 8.7e-08 67 0.2 0.00011
TSHB 92296 25020 420 6 5 5 3 0 20 0.027 1e-07 23 0.18 0.00012
NDUFB9 127602 32248 1060 8 8 1 1 0 20 0.62 2.6e-07 47 0.19 0.00028
PPIAL4G 108420 28912 240 15 15 11 8 0 20 0.77 3.6e-07 44 0.19 0.00036
TUBAL3 289676 85624 830 11 10 11 5 0 20 0.074 4.1e-07 32 0.19 0.00039
ARMC4 660250 184314 3480 81 54 64 21 0 15 1.6 4.3e-07 110 0.2 0.00039
RPS27 88126 24464 1160 25 24 3 0 0 0 0 5.3e-07 120 0.2 0.00046
LUZP2 234632 59770 2340 28 27 25 4 0 8 1.1 6.8e-07 68 0.2 0.00056
AOAH 406158 97300 4080 28 27 25 11 0 20 0.69 1.5e-06 64 0.2 0.0012
FUT9 237134 61160 220 30 29 26 7 0 20 1.3 2.2e-06 61 0.2 0.0017
CYP4Z1 329152 85346 2130 28 27 22 10 0 20 0.88 3.3e-06 61 0.2 0.0024
TC2N 325816 88960 2160 20 20 19 14 0 20 0.8 3.9e-06 58 0.31 0.0027
TMPRSS11B 279668 72836 1980 26 22 23 6 0 11 1.5 4e-06 70 0.2 0.0027
OGDHL 648018 186538 4080 42 33 39 15 0 14 0.54 4.8e-06 73 0.2 0.0031
TCHHL1 590750 163742 440 54 39 50 12 0 17 0.71 5.4e-06 72 0.2 0.0034
C1QTNF9 182090 55044 630 16 16 13 3 0 19 0.63 5.6e-06 45 0.19 0.0034
LRRC4C 410328 122876 240 47 41 38 18 0 13 1.7 6.3e-06 88 0.2 0.0036
GPR141 198492 56156 240 16 16 12 5 0 20 0.51 6.3e-06 43 0.2 0.0036
ITGA4 699170 185982 6010 43 36 38 12 0 15 0.6 6.5e-06 73 0.2 0.0036
LCE1B 77006 22240 240 14 14 14 0 0 20 1.2 7.6e-06 39 0.19 0.004
TPTE2 356118 92574 5190 40 33 35 7 0 14 1.5 7.7e-06 78 0.2 0.004
NRAS

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

BRAF

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

PCDHAC2

Figure S3.  This figure depicts the distribution of mutations and mutation types across the PCDHAC2 significant gene.

PTEN

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

CDKN2A

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

TP53

Figure S6.  This figure depicts the distribution of mutations and mutation types across the TP53 significant gene.

MRPS31

Figure S7.  This figure depicts the distribution of mutations and mutation types across the MRPS31 significant gene.

PCDHGC5

Figure S8.  This figure depicts the distribution of mutations and mutation types across the PCDHGC5 significant gene.

BAGE

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

TMEM216

Figure S10.  This figure depicts the distribution of mutations and mutation types across the TMEM216 significant gene.

DSG1

Figure S11.  This figure depicts the distribution of mutations and mutation types across the DSG1 significant gene.

PPP6C

Figure S12.  This figure depicts the distribution of mutations and mutation types across the PPP6C significant gene.

SERPINB3

Figure S13.  This figure depicts the distribution of mutations and mutation types across the SERPINB3 significant gene.

MS4A2

Figure S14.  This figure depicts the distribution of mutations and mutation types across the MS4A2 significant gene.

FAM113B

Figure S15.  This figure depicts the distribution of mutations and mutation types across the FAM113B significant gene.

TSHB

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

NDUFB9

Figure S17.  This figure depicts the distribution of mutations and mutation types across the NDUFB9 significant gene.

PPIAL4G

Figure S18.  This figure depicts the distribution of mutations and mutation types across the PPIAL4G significant gene.

TUBAL3

Figure S19.  This figure depicts the distribution of mutations and mutation types across the TUBAL3 significant gene.

ARMC4

Figure S20.  This figure depicts the distribution of mutations and mutation types across the ARMC4 significant gene.

RPS27

Figure S21.  This figure depicts the distribution of mutations and mutation types across the RPS27 significant gene.

LUZP2

Figure S22.  This figure depicts the distribution of mutations and mutation types across the LUZP2 significant gene.

FUT9

Figure S23.  This figure depicts the distribution of mutations and mutation types across the FUT9 significant gene.

CYP4Z1

Figure S24.  This figure depicts the distribution of mutations and mutation types across the CYP4Z1 significant gene.

TC2N

Figure S25.  This figure depicts the distribution of mutations and mutation types across the TC2N significant gene.

TMPRSS11B

Figure S26.  This figure depicts the distribution of mutations and mutation types across the TMPRSS11B significant gene.

OGDHL

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

TCHHL1

Figure S28.  This figure depicts the distribution of mutations and mutation types across the TCHHL1 significant gene.

C1QTNF9

Figure S29.  This figure depicts the distribution of mutations and mutation types across the C1QTNF9 significant gene.

LRRC4C

Figure S30.  This figure depicts the distribution of mutations and mutation types across the LRRC4C significant gene.

GPR141

Figure S31.  This figure depicts the distribution of mutations and mutation types across the GPR141 significant gene.

ITGA4

Figure S32.  This figure depicts the distribution of mutations and mutation types across the ITGA4 significant gene.

LCE1B

Figure S33.  This figure depicts the distribution of mutations and mutation types across the LCE1B 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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