Skin Cutaneous Melanoma: Mutation Analysis (MutSigCV v0.9)
(NF1_Any_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-NF1_Any_Mutants

  • Number of patients in set: 31

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-NF1_Any_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: 2. 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
NF1 291772 81778 0 42 31 40 1 0 0 0.14 1.3e-15 95 0.021 2.4e-11
FAM58A 14446 4154 0 5 5 4 0 0 20 0.8 6.9e-07 27 0.019 0.0063
NRAS 14291 3782 0 9 9 6 0 0 20 0.71 0.000018 22 0.019 0.11
OR51S1 22351 7626 0 11 11 9 1 0 20 1.6 0.00023 23 0.019 0.99
IL1F8 17856 4619 0 6 6 6 1 0 19 1.2 0.00027 20 0.019 0.99
GK2 39711 11687 0 14 11 14 4 0 20 1.6 0.00071 25 0.019 1
TP53 29295 8556 0 11 10 10 0 0 4 0.58 0.00086 30 0.02 1
TXNDC3 44981 10943 0 11 11 10 3 0 20 1.2 0.0019 23 0.02 1
CNRIP1 8091 2201 0 2 2 2 0 0 20 0.45 0.0023 11 0.017 1
TCEB3C 23684 7626 0 13 12 13 4 0 20 1.6 0.0024 20 0.02 1
PLUNC 18259 6355 0 5 5 5 1 0 20 0.76 0.0024 15 0.018 1
MS4A2 18352 5332 0 5 5 5 0 0 11 0.29 0.0025 14 0.018 1
DSG1 76818 22134 0 19 12 15 4 0 20 0.56 0.0026 24 0.019 1
ATP6V1G3 10726 2046 0 3 3 3 1 0 20 0.78 0.0028 12 0.017 1
ZFX 60574 15252 0 8 7 8 0 0 20 0.62 0.0029 21 0.019 1
C6orf127 7595 2046 0 2 2 2 0 0 20 0.86 0.0031 11 0.017 1
TEX19 11470 3100 0 3 3 3 0 0 20 0.62 0.0035 13 0.018 1
STARD6 16647 4371 0 6 4 6 1 0 20 0.85 0.0043 13 0.018 1
CAPZA3 22506 5797 0 9 7 7 5 0 15 2.6 0.0046 20 0.019 1
TSHB 10292 2790 0 3 2 3 0 0 20 0.14 0.0048 6.5 0.012 1
LRTM1 24676 7471 0 10 10 10 4 0 20 0.8 0.005 15 0.027 1
OR6K6 24645 7285 0 5 5 4 2 0 20 1.5 0.0053 17 0.019 1
ANGPT1 37913 9269 0 12 10 11 1 0 20 1 0.0054 19 0.019 1
CCDC11 39463 9145 0 8 8 7 0 0 20 0.47 0.0058 17 0.019 1
PCP4L1 4588 1240 0 2 2 2 0 0 20 0.83 0.0068 8.7 0.016 1
OR52A1 22351 6572 0 8 8 5 3 0 12 1.3 0.007 18 0.019 1
DEGS2 17515 5704 0 3 3 3 0 0 20 0.33 0.0073 13 0.018 1
IL32 12648 3317 0 4 4 4 0 0 20 0.64 0.0073 11 0.017 1
UBE2V2 10912 2883 0 3 3 2 0 0 20 0.73 0.0073 10 0.017 1
GJA8 29822 9114 0 10 9 10 3 0 20 1.6 0.0075 19 0.019 1
OLIG3 14291 4247 0 4 4 4 0 0 20 0.7 0.0076 12 0.018 1
ZSCAN4 32054 8463 0 8 8 8 3 0 19 0.73 0.0087 15 0.019 1
PROL1 17236 5921 0 10 9 9 2 0 20 1.3 0.009 15 0.018 1
CATSPERB 83979 22196 0 16 11 15 8 0 11 1.3 0.0091 25 0.02 1
PPIAL4G 12090 3224 0 3 3 3 2 0 20 0.68 0.011 10 0.017 1
NF1

Figure S1.  This figure depicts the distribution of mutations and mutation types across the NF1 significant gene.

FAM58A

Figure S2.  This figure depicts the distribution of mutations and mutation types across the FAM58A 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)
Copyright © 2013 Broad Institute TCGA GDAC as part of the TCGA Research Network. All rights reserved.
Made with Nozzle