Mutation Analysis (MutSigCV v0.6)
Skin Cutaneous Melanoma (Metastatic)
22 February 2013  |  analyses__2013_02_22
Maintainer Information
Citation Information
doi:10.7908/C1H41PPQ
Maintained by Dan DiCara (Broad Institute)
Cite as Broad Institute TCGA Genome Data Analysis Center (2013): Mutation Analysis (MutSigCV v0.6). Broad Institute of MIT and Harvard. doi:10.7908/C1H41PPQ
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 v0.6 was used to generate the results found in this report.

  • Working with individual set: SKCM-TM

  • Number of patients in set: 225

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-TM.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: 6. 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 388575 110925 7119 120 115 16 2 0 19 0.77 1e-15 290 0.16 1.8e-11
CDKN2A 135450 38475 1302 31 31 15 1 0 6 0.65 4.1e-15 140 0.16 3.7e-11
NRAS 103725 27450 1722 65 65 9 1 0 20 0.79 6.3e-15 190 0.16 3.8e-11
PTEN 219150 52650 3654 18 18 16 0 0 20 0.57 8.3e-14 86 0.16 3.8e-10
TP53 212625 62100 4326 37 34 31 1 0 4 0.97 1.5e-13 110 0.16 5.4e-10
PPP6C 166050 45450 2751 18 17 13 2 0 20 0.69 2e-06 53 0.16 0.0061
NF1 2117700 593550 24864 42 31 40 7 0 0 0.34 0.000043 110 0.16 0.11
MS4A2 133200 38700 2751 9 9 9 1 0 11 0.24 0.000057 28 0.15 0.13
DSG1 557550 160650 6300 50 37 44 8 0 20 0.58 7e-05 68 0.15 0.14
COPG2 210600 58725 27027 11 9 8 1 0 4 0.24 0.00011 36 0.15 0.2
EIF2B1 188775 54000 4557 9 9 3 3 0 20 0.61 0.00019 42 0.15 0.32
LCE1B 62325 18000 504 13 13 13 0 0 20 1.2 0.0003 34 0.15 0.44
IL32 91800 24075 2289 9 9 6 2 0 20 0.96 0.00031 37 0.15 0.44
LIN7A 113400 34200 4431 10 10 9 0 0 2 0 0.00037 34 0.15 0.49
TSGA13 151875 38925 2961 10 9 8 2 0 18 0.44 0.00042 32 0.15 0.51
B2M 64575 18000 1344 5 5 4 0 0 20 0.86 0.00092 28 0.15 1
GRXCR1 154800 43650 1764 20 18 18 3 0 3 0.72 0.00099 45 0.15 1
PPIAL4G 87750 23400 504 11 11 8 7 0 20 0.78 0.0013 29 0.15 1
GPR141 160650 45450 504 13 13 9 5 0 20 0.61 0.0014 33 0.15 1
LARP4B 384525 112950 6909 9 9 9 0 0 2 0 0.0026 33 0.15 1
DGAT2L6 158850 47475 2352 10 10 9 0 0 9 0.36 0.0035 27 0.14 1
CCNE2 246600 61425 5124 12 12 8 2 0 20 0.6 0.0041 35 0.15 1
FAM58A 104850 30150 1596 5 5 4 0 0 20 0.73 0.0055 28 0.15 1
CA1 137025 37575 2877 8 8 8 2 0 3 0.3 0.0059 24 0.14 1
MPP7 315225 82800 6615 27 24 23 5 0 8 0.79 0.0082 46 0.16 1
AOAH 328725 78750 8568 21 20 19 8 0 20 0.72 0.0082 44 0.15 1
CLEC2B 78750 18675 1512 5 5 5 0 0 12 0.77 0.0089 23 0.14 1
DPY19L4 394425 102825 7455 18 15 14 2 0 11 0.44 0.0094 39 0.15 1
MCC 729900 204750 8400 11 11 10 0 0 1 0 0.01 36 0.15 1
DNAJC5B 107550 28350 1680 10 10 9 3 0 20 0.57 0.01 23 0.14 1
AMHR2 284400 82800 4221 14 13 14 3 0 20 0.71 0.01 43 0.15 1
TSHB 74700 20250 882 5 4 5 2 0 20 0.17 0.011 11 0.12 1
TCHHL1 478125 132525 924 40 30 38 6 0 17 0.61 0.011 46 0.15 1
MCART6 157050 50400 504 9 9 9 1 0 19 0.64 0.012 29 0.16 1
C1QTNF9 147375 44550 1323 13 13 12 3 0 19 0.68 0.013 29 0.15 1
BRAF

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

CDKN2A

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

NRAS

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

PTEN

Figure S4.  This figure depicts the distribution of mutations and mutation types across the PTEN significant gene.

TP53

Figure S5.  This figure depicts the distribution of mutations and mutation types across the TP53 significant gene.

PPP6C

Figure S6.  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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