Skin Cutaneous Melanoma: Mutation Analysis (MutSigCV v0.9)
(BRAF_Hotspot_Mutants cohort)
Maintained by Dan DiCara (Broad Institute)
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-BRAF_Hotspot_Mutants

  • Number of patients in set: 97

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
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).

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-BRAF_Hotspot_Mutants.patients.counts_and_rates.txt

CoMut Plot

Figure 3.  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: 4. 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 167519 47821 5085 99 97 4 1 0 19 0.84 2.8e-15 240 0.065 5.1e-11
PTEN 94478 22698 2610 12 12 11 0 0 20 0.86 9.3e-11 53 0.057 8.5e-07
CDKN2A 58394 16587 930 12 12 10 0 0 6 0.23 7.5e-09 52 0.063 0.000046
B2M 27839 7760 960 4 4 4 0 0 20 0.71 9.8e-06 22 0.058 0.045
IL32 39576 10379 1635 4 4 2 1 0 20 1.2 0.00039 21 0.052 1
OR4K1 70616 19982 360 16 14 13 2 0 20 2.3 0.0004 28 0.061 1
RBM11 50052 13386 675 6 6 6 0 0 20 1.3 0.00055 21 0.059 1
ADAM32 146567 37151 4125 10 10 10 1 0 20 0.8 0.0008 29 0.055 1
SIGLEC6 102044 30846 2115 11 11 8 4 0 8 0.78 0.0012 29 0.063 1
CDR1 61110 15229 360 7 7 7 1 0 20 2.5 0.0016 24 0.06 1
C7orf58 242112 64990 6690 16 13 15 1 0 20 1.3 0.0017 33 0.055 1
NMNAT3 49373 14065 2760 5 5 5 5 0 20 1.1 0.002 18 0.1 1
SLC16A14 115430 34047 1260 9 9 9 5 0 20 1.1 0.0031 23 0.053 1
LCE1B 26869 7760 360 4 4 4 0 0 20 1.4 0.0031 14 0.055 1
ST6GAL2 107088 31040 1455 14 13 13 3 0 20 1.7 0.0031 26 0.061 1
DAPL1 20273 5723 870 2 2 2 0 0 20 0.81 0.0032 12 0.051 1
TCEB3C 74108 23862 165 9 7 7 2 0 20 1.5 0.0033 23 0.052 1
ZNF215 122123 29779 1560 8 8 8 1 0 20 0.88 0.0035 22 0.058 1
CYP4Z1 114848 29779 3195 9 9 9 2 0 20 0.81 0.0037 21 0.059 1
GK2 124257 36569 345 14 12 13 1 0 20 1.6 0.004 26 0.061 1
CT62 28712 8536 345 3 3 2 1 0 20 0.29 0.005 10 0.049 1
TIMD4 86233 26481 2700 8 6 8 3 0 20 0.86 0.0053 20 0.058 1
PCDP1 132599 34047 4815 8 8 6 0 0 11 0.4 0.0054 21 0.056 1
MYPOP 24250 7760 195 3 3 3 1 0 20 0.53 0.0055 12 0.099 1
NAT2 66542 18139 330 5 5 3 0 0 20 1.4 0.0055 18 0.11 1
SPINK13 23183 5529 1260 4 4 4 0 0 20 1.7 0.006 13 0.053 1
OR51S1 69937 23862 405 9 8 7 3 0 20 1.3 0.0063 18 0.058 1
KCNB2 206125 59073 660 22 16 21 8 0 20 2.1 0.0064 33 0.056 1
GPR141 69258 19594 360 6 6 5 0 0 20 0.61 0.0064 16 0.056 1
MORF4 53544 14647 345 8 8 8 1 0 17 2.3 0.0066 19 0.059 1
SV2B 160050 42680 3630 8 8 8 3 0 20 0.94 0.0074 23 0.053 1
PPP6C 71586 19594 1965 7 6 5 0 0 20 0.65 0.0076 16 0.1 1
GZMA 60528 17363 1545 4 4 4 0 0 20 0.66 0.0079 14 0.055 1
C1orf168 171884 44232 5865 13 13 12 2 0 8 0.88 0.0081 30 0.055 1
EIF2B1 81383 23280 3255 3 3 1 2 0 20 0.63 0.0082 17 0.051 1
BRAF

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

PTEN

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

CDKN2A

Figure S3.  This figure depicts the distribution of mutations and mutation types across the CDKN2A significant gene.

B2M

Figure S4.  This figure depicts the distribution of mutations and mutation types across the B2M 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

This is an experimental feature. The full results of the analysis summarized in this report can be downloaded from the TCGA Data Coordination Center.

References
[1] TCGA, Integrated genomic analyses of ovarian carcinoma, Nature 474:609 - 615 (2011)
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