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

  • Number of patients in set: 62

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-NRAS_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: 3. 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 28582 7564 492 62 62 6 0 0 20 0.75 0 170 0.04 0
CDKN2A 37324 10602 372 12 12 8 0 0 6 0.27 6.8e-10 53 0.04 6.2e-06
PPP6C 45756 12524 786 10 10 9 1 0 20 0.61 4.6e-08 36 0.04 0.00028
DSG1 153636 44268 1800 16 14 15 3 0 20 0.44 0.00015 32 0.039 0.69
CYP4Z1 73408 19034 1278 11 10 11 3 0 20 0.82 0.00028 25 0.038 1
C18orf26 30566 9052 384 8 8 8 3 0 20 1.5 0.00038 22 0.037 1
TUBAL3 64604 19096 498 6 6 6 2 0 20 0.26 0.00077 14 0.035 1
TP53 58590 17112 1236 13 13 12 0 0 4 1.4 0.0011 37 0.041 1
DEFA4 13702 4402 246 5 5 5 0 0 20 0.82 0.0012 13 0.034 1
LPAR1 52762 15438 378 6 6 5 1 0 20 0.72 0.0013 20 0.037 1
MS4A2 36704 10664 786 4 4 4 0 0 11 0.089 0.0013 14 0.035 1
SGCZ 44206 13144 1398 10 9 9 0 0 16 1.8 0.0014 23 0.038 1
PTEN 60388 14508 1044 4 4 4 0 0 20 0.53 0.0018 19 0.037 1
C6orf105 34224 9796 738 5 5 5 1 0 20 0.67 0.0019 15 0.036 1
HIST1H2AA 36580 11656 288 5 5 5 0 0 20 0.34 0.0021 16 0.036 1
OR2W1 45818 13206 132 9 8 9 0 0 20 1.4 0.0028 18 0.041 1
TP53INP1 37076 9362 468 3 3 2 0 0 20 0.66 0.0051 14 0.035 1
TRIOBP 277822 90892 1854 17 17 17 3 0 20 0.62 0.0052 37 0.041 1
FAM113B 53320 17112 108 7 7 6 4 0 20 0.89 0.0053 18 0.037 1
DDX3X 98270 26164 1944 7 7 7 0 0 12 0.57 0.0054 23 0.038 1
TTPAL 49166 15066 498 4 4 4 0 0 20 0.76 0.0058 16 0.037 1
LRTM1 49352 14942 378 8 8 8 5 0 20 1.3 0.0063 18 0.037 1
SPATS1 45074 11904 942 6 6 6 0 0 18 1 0.0066 15 0.036 1
PRC1 94302 24428 1818 7 6 7 0 0 20 0.59 0.0075 18 0.037 1
TCHHL1 131750 36518 264 13 10 13 2 0 17 0.56 0.0078 22 0.039 1
OR1N2 46624 14632 162 8 7 7 3 0 20 1.9 0.009 18 0.037 1
OR2G6 44826 14012 144 10 10 10 2 0 20 2.2 0.0093 19 0.037 1
LCE1B 17174 4960 144 5 5 5 0 0 20 1.1 0.0093 10 0.032 1
HRCT1 11718 4278 78 2 2 2 0 0 20 1.3 0.0094 12 0.034 1
CD163L1 214024 59706 2280 27 21 25 3 0 10 1.6 0.011 39 0.04 1
ARL11 25234 8122 78 3 3 3 1 0 20 0.51 0.011 11 0.033 1
UGT2B4 77810 21142 744 13 11 13 2 0 20 2.6 0.011 24 0.039 1
ACMSD 51088 13516 1212 5 5 5 0 0 20 0.54 0.011 15 0.036 1
LRRC4C 91512 27404 144 12 11 12 4 0 13 1.4 0.012 25 0.039 1
SERPINB10 59024 14880 834 6 6 6 0 0 20 0.76 0.012 14 0.036 1
NRAS

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

CDKN2A

Figure S2.  This figure depicts the distribution of mutations and mutation types across the CDKN2A significant gene.

PPP6C

Figure S3.  This figure depicts the distribution of mutations and mutation types across the PPP6C 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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