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

  • Number of patients in set: 34

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-WT.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: 0. 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
KRTAP5-1 21420 6664 0 4 4 4 0 0 20 0.76 0.005 12 0.02 1
MCART6 23732 7616 0 3 3 3 0 0 19 0.69 0.0076 13 0.021 1
RAC1 16150 4862 0 5 5 4 0 0 20 0.76 0.008 10 0.02 1
DPPA5 9418 2720 0 2 2 2 0 0 20 0.33 0.0086 8.6 0.019 1
MOSPD3 17850 6460 0 2 2 2 0 0 20 0.84 0.011 11 0.02 1
LSM7 2788 612 0 1 1 1 0 0 20 0.44 0.016 6.1 0.015 1
C2orf66 9350 2822 0 2 2 2 0 0 20 0.9 0.018 6.8 0.016 1
SERPINB11 28696 7718 0 2 2 2 0 0 20 0.6 0.018 10 0.02 1
NDUFS7 9452 2958 0 2 2 2 0 0 20 2.1 0.021 8.2 0.018 1
C6orf223 13124 3502 0 2 2 2 0 0 20 0.4 0.021 7.5 0.018 1
FAM113B 29240 9384 0 4 4 4 3 0 20 0.54 0.023 10 0.02 1
PLEKHF2 20026 5406 0 2 2 2 0 0 20 0.24 0.024 8.2 0.018 1
LENEP 10336 3366 0 2 2 2 0 0 20 0.58 0.024 7 0.017 1
SLC10A2 27846 8296 0 2 2 2 1 0 18 0.97 0.026 7.3 0.017 1
CLEC2L 8126 2142 0 2 2 2 0 0 20 2.4 0.026 7.3 0.017 1
IFITM5 5134 1836 0 1 1 1 0 0 20 1.7 0.026 6.1 0.027 1
ODF1 20264 5338 0 3 3 3 0 0 8 0.36 0.027 12 0.021 1
OCIAD2 13192 3264 0 2 2 2 0 0 20 0.34 0.027 7.2 0.017 1
CRYBA4 16116 4420 0 4 3 4 1 0 20 0.9 0.029 9 0.019 1
CEACAM20 41480 12818 0 4 4 4 1 0 11 2.6 0.03 11 0.021 1
SRPK1 47532 12614 0 3 3 3 1 0 15 0.5 0.032 12 0.021 1
NCR2 20570 6426 0 3 3 3 0 0 20 0 0.033 8.1 0.018 1
TMPRSS11B 34204 8908 0 3 3 3 1 0 11 1.6 0.033 12 0.021 1
TUBA1B 34374 9996 0 4 4 3 0 0 20 0.34 0.033 9 0.02 1
IGFL3 10336 2890 0 2 2 2 0 0 20 1.5 0.033 7.8 0.018 1
SPRR4 6494 1666 0 1 1 1 0 0 20 1.7 0.033 6 0.015 1
DNAJC5B 16252 4284 0 3 3 3 0 0 20 0.28 0.034 6.6 0.017 1
GABRB2 40290 11288 0 3 3 3 1 0 20 0.5 0.035 9.5 0.02 1
GML 12954 3502 0 2 2 2 0 0 20 0.84 0.036 7.1 0.017 1
C3orf23 42602 10574 0 3 3 3 0 0 20 0.44 0.036 9.4 0.02 1
EIF2B1 28526 8160 0 2 2 1 0 0 20 0.68 0.036 9.9 0.02 1
EMR3 52972 14892 0 4 3 4 0 0 20 1.3 0.037 15 0.022 1
MUC7 28152 10472 0 6 5 5 0 0 20 1 0.037 8.3 0.019 1
RPL22 10268 2482 0 1 1 1 0 0 20 0.65 0.038 5.9 0.015 1
AKT1S1 8194 2482 0 1 1 1 0 0 20 0.54 0.038 6 0.015 1
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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