Mutation Analysis (MutSigCV v0.9)
Skin Cutaneous Melanoma (Metastatic)
02 April 2015  |  analyses__2015_04_02
Maintainer Information
Citation Information
doi:10.7908/C1CF9P6B
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/C1CF9P6B
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: 290

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): 351

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: 351. 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 133694 35380 18534 90 87 10 1 0 20 0.75 0 290 0.21 0
BRAF 500840 142974 76696 169 145 19 5 0 19 0.81 6.7e-16 400 0.22 6.1e-12
TP53 274050 80040 44722 54 48 43 2 0 4 1.3 2.6e-15 160 0.22 1.6e-11
CDKN2A 174128 49470 13186 46 42 24 2 0 6 0.73 5.7e-15 180 0.22 2.6e-11
PTEN 282386 67842 38608 25 25 23 0 0 20 0.49 7e-15 120 0.21 2.6e-11
ARMC4 688710 192258 77588 84 57 66 22 0 15 1.4 3.3e-12 130 0.22 1e-08
PPP6C 214088 58608 31638 21 20 15 3 0 20 0.74 8.6e-11 67 0.21 2.2e-07
DSG1 718640 207064 67298 64 46 56 12 0 20 0.75 2.8e-10 97 0.21 6.4e-07
DCDC1 252894 68732 33950 48 36 45 14 0 20 1.8 6.2e-10 81 0.21 1.3e-06
MS4A2 171734 49896 29152 13 13 12 2 0 11 0.25 7.9e-10 49 0.21 1.3e-06
TMPRSS11B 291758 75986 43788 29 24 25 6 0 11 1.2 8e-10 78 0.21 1.3e-06
PPIAL4G 113102 30160 5538 14 14 11 4 0 20 0.43 1.4e-09 46 0.22 2.1e-06
AOAH 423930 101574 91364 27 25 25 14 0 20 0.56 3.1e-09 69 0.21 4.3e-06
VEGFC 278102 71626 28596 23 20 20 2 0 6 0.49 4.3e-09 64 0.21 5.6e-06
MPP7 406286 106720 70240 40 32 33 6 0 8 0.89 5.4e-09 78 0.22 6.6e-06
TMC5 773730 213150 96910 60 51 48 37 0 20 1.2 6.5e-09 100 0.21 7.4e-06
PREX2 1172756 304208 271492 98 71 84 35 0 12 1.3 7.5e-09 130 0.22 8.1e-06
PROL1 161250 55392 9156 27 24 21 7 0 20 0.86 1.1e-08 56 0.21 1e-05
OGDHL 675906 194568 89186 44 35 41 15 0 14 0.55 1.1e-08 82 0.21 1e-05
C8orf34 303042 80330 58454 36 32 33 6 0 20 1.7 1.3e-08 82 0.21 0.000012
ITGA4 729376 194014 132712 45 38 40 12 0 15 0.62 1.6e-08 81 0.26 0.000014
COL5A1 1056984 340826 318804 84 57 80 32 0 10 0.79 1.6e-08 110 0.22 0.000014
SYCP1 627372 146762 108792 38 30 31 8 0 6 0.55 2e-08 78 0.22 0.000016
CYP4Z1 343366 89032 47494 29 27 22 10 0 20 0.79 2.6e-08 65 0.21 0.000019
KIAA2022 1027700 274612 11490 77 56 67 29 0 11 1 2.6e-08 110 0.21 0.000019
STXBP5L 825086 227368 116356 76 58 69 13 0 16 1.2 2.8e-08 100 0.21 2e-05
SCN5A 1283998 375018 80708 103 71 98 58 0 20 1.1 3.8e-08 130 0.21 0.000025
PCSK1 522300 142974 61522 31 27 27 13 0 20 0.68 3.9e-08 75 0.21 0.000025
STK31 727910 181542 108806 51 38 45 13 0 18 0.72 4.9e-08 83 0.21 0.000031
LRRC4C 428046 128182 5294 50 43 41 18 0 13 1.8 5.9e-08 96 0.21 0.000036
C1orf168 513924 132250 87480 50 40 44 16 0 8 0.92 8e-08 83 0.21 0.000047
TPTE2 371532 96578 114198 38 31 34 6 0 14 1.5 8.8e-08 82 0.21 5e-05
C12orf50 296402 72794 52782 30 25 28 10 0 16 1 1e-07 65 0.21 0.000057
LCE1B 80330 23198 5424 15 15 15 0 0 20 1.2 1.1e-07 44 0.21 0.000057
GK2 371492 109330 4888 41 34 34 6 0 20 1.3 1.2e-07 76 0.22 0.000061
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.

TP53

Figure S3.  This figure depicts the distribution of mutations and mutation types across the TP53 significant gene.

CDKN2A

Figure S4.  This figure depicts the distribution of mutations and mutation types across the CDKN2A significant gene.

PTEN

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

ARMC4

Figure S6.  This figure depicts the distribution of mutations and mutation types across the ARMC4 significant gene.

PPP6C

Figure S7.  This figure depicts the distribution of mutations and mutation types across the PPP6C significant gene.

DSG1

Figure S8.  This figure depicts the distribution of mutations and mutation types across the DSG1 significant gene.

DCDC1

Figure S9.  This figure depicts the distribution of mutations and mutation types across the DCDC1 significant gene.

MS4A2

Figure S10.  This figure depicts the distribution of mutations and mutation types across the MS4A2 significant gene.

TMPRSS11B

Figure S11.  This figure depicts the distribution of mutations and mutation types across the TMPRSS11B significant gene.

PPIAL4G

Figure S12.  This figure depicts the distribution of mutations and mutation types across the PPIAL4G significant gene.

MPP7

Figure S13.  This figure depicts the distribution of mutations and mutation types across the MPP7 significant gene.

TMC5

Figure S14.  This figure depicts the distribution of mutations and mutation types across the TMC5 significant gene.

PREX2

Figure S15.  This figure depicts the distribution of mutations and mutation types across the PREX2 significant gene.

PROL1

Figure S16.  This figure depicts the distribution of mutations and mutation types across the PROL1 significant gene.

OGDHL

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

C8orf34

Figure S18.  This figure depicts the distribution of mutations and mutation types across the C8orf34 significant gene.

ITGA4

Figure S19.  This figure depicts the distribution of mutations and mutation types across the ITGA4 significant gene.

COL5A1

Figure S20.  This figure depicts the distribution of mutations and mutation types across the COL5A1 significant gene.

SYCP1

Figure S21.  This figure depicts the distribution of mutations and mutation types across the SYCP1 significant gene.

CYP4Z1

Figure S22.  This figure depicts the distribution of mutations and mutation types across the CYP4Z1 significant gene.

KIAA2022

Figure S23.  This figure depicts the distribution of mutations and mutation types across the KIAA2022 significant gene.

STXBP5L

Figure S24.  This figure depicts the distribution of mutations and mutation types across the STXBP5L significant gene.

SCN5A

Figure S25.  This figure depicts the distribution of mutations and mutation types across the SCN5A significant gene.

PCSK1

Figure S26.  This figure depicts the distribution of mutations and mutation types across the PCSK1 significant gene.

STK31

Figure S27.  This figure depicts the distribution of mutations and mutation types across the STK31 significant gene.

LRRC4C

Figure S28.  This figure depicts the distribution of mutations and mutation types across the LRRC4C significant gene.

C1orf168

Figure S29.  This figure depicts the distribution of mutations and mutation types across the C1orf168 significant gene.

TPTE2

Figure S30.  This figure depicts the distribution of mutations and mutation types across the TPTE2 significant gene.

C12orf50

Figure S31.  This figure depicts the distribution of mutations and mutation types across the C12orf50 significant gene.

LCE1B

Figure S32.  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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