Skin Cutaneous Melanoma: Mutation Analysis (MutSigCV v0.9)
(All_Primary 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-All_Primary

  • Number of patients in set: 38

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-All_Primary.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: 1. 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 65626 18734 2373 24 23 4 0 0 19 0.84 3.6e-12 50 0.036 6.6e-08
PTEN 37012 8892 1218 5 5 5 0 0 20 0.2 0.000069 21 0.034 0.63
NRAS 17518 4636 574 6 6 1 0 0 20 0.54 0.00016 17 0.034 1
PPP6C 28044 7676 917 5 5 4 0 0 20 0.36 0.0011 15 0.033 1
TNFSF14 19798 6802 525 4 4 4 0 0 20 0.79 0.0026 12 0.031 1
KCNE1 11362 3420 168 3 3 3 0 0 20 0.92 0.014 7.5 0.027 1
PIK3R1 70832 18202 2415 4 4 4 0 0 20 0.2 0.015 15 0.035 1
PPIP5K1 40812 11362 686 2 2 1 0 0 20 0.58 0.017 11 0.031 1
CFC1B 4826 1330 147 1 1 1 0 0 20 1 0.018 6.2 0.024 1
PAGE1 11400 3078 574 2 2 2 0 0 20 1.2 0.021 7.9 0.028 1
SPRR1B 8056 2204 168 1 1 1 0 0 20 0.34 0.022 6.1 0.022 1
C1orf201 26220 7448 1001 2 2 2 0 0 20 0.13 0.022 8.4 0.028 1
GPR88 6802 2584 0 1 1 1 0 0 20 1.2 0.023 6.2 0.025 1
FBRS 17708 6080 602 2 2 2 0 0 20 0.94 0.024 8.3 0.029 1
C16orf54 5548 1824 126 1 1 1 0 0 20 0.59 0.026 6.1 0.024 1
LMCD1 32072 9044 777 3 3 3 1 0 20 1.3 0.028 9.7 0.031 1
HDGFL1 8702 2242 84 1 1 1 1 0 20 1.8 0.029 6.2 0.025 1
NDUFAF2 14934 3952 658 2 2 2 0 0 20 1.2 0.029 7.7 0.028 1
G6PC2 32338 8740 721 3 3 3 1 0 20 0.88 0.03 9.3 0.03 1
MRPL33 8854 1862 574 1 1 1 0 0 19 0.37 0.03 6.1 0.024 1
TSHB 12616 3420 294 1 1 1 0 0 20 0.19 0.03 3.5 0.014 1
UGT2B7 48260 12730 868 4 4 4 0 0 20 1.2 0.032 11 0.032 1
LY86 14592 3990 693 3 3 3 2 0 20 0.87 0.033 6 0.025 1
LELP1 8892 2318 161 3 3 2 0 0 18 2.1 0.033 6.5 0.026 1
NBPF7 38912 10032 1169 4 4 4 0 0 20 1.9 0.034 11 0.033 1
PRB2 33516 12198 371 9 8 7 0 0 12 3.3 0.035 12 0.033 1
AADACL2 34732 9500 637 3 3 3 0 0 20 1.1 0.036 9.6 0.031 1
C7orf11 7068 2052 175 1 1 1 0 0 20 0.86 0.036 6 0.024 1
OR10A7 27664 8246 189 3 3 3 0 0 20 1.6 0.036 9.3 0.031 1
CSH2 16492 5016 546 1 1 1 0 0 20 0.62 0.039 5.9 0.025 1
TMCO2 16340 4598 308 1 1 1 0 0 20 0.18 0.041 5.8 0.024 1
IL32 15504 4066 763 1 1 1 0 0 20 0.19 0.041 5.8 0.024 1
TCEB3C 29032 9348 77 3 3 3 2 0 20 0.87 0.041 9.4 0.03 1
OTUD6A 16378 4484 56 3 3 3 0 0 20 0.21 0.042 7.7 0.028 1
VIL1 75050 21052 2597 5 5 5 0 0 20 0.19 0.042 13 0.036 1
BRAF

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