Mutation Analysis (MutSigCV v0.9)
Sarcoma (Primary solid tumor)
28 January 2016  |  analyses__2016_01_28
Maintainer Information
Citation Information
doi:10.7908/C1ZG6RQC
Maintained by David Heiman (Broad Institute)
Cite as Broad Institute TCGA Genome Data Analysis Center (2016): Mutation Analysis (MutSigCV v0.9). Broad Institute of MIT and Harvard. doi:10.7908/C1ZG6RQC
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: SARC-TP

  • Number of patients in set: 247

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

  • MAF used for this analysis:SARC-TP.final_analysis_set.maf

  • Blacklist used for this analysis: pancan_mutation_blacklist.v14.hg19.txt

  • Significantly mutated genes (q ≤ 0.1): 8

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). If the figure is unpopulated, then full coverage is assumed (e.g. MutSig CV doesn't use WIGs and assumes full coverage).

Figure 1. 

Distribution of Mutation Counts, Coverage, and Mutation Rates Across Samples

Figure 2.  Patients counts and rates file used to generate this plot: SARC-TP.patients.counts_and_rates.txt

Lego Plots

The mutation spectrum is depicted in the lego plots below in which the 96 possible mutation types are subdivided into six large blocks, color-coded to reflect the base substitution type. Each large block is further subdivided into the 16 possible pairs of 5' and 3' neighbors, as listed in the 4x4 trinucleotide context legend. The height of each block corresponds to the mutation frequency for that kind of mutation (counts of mutations normalized by the base coverage in a given bin). The shape of the spectrum is a signature for dominant mutational mechanisms in different tumor types.

Figure 3.  Get High-res Image SNV Mutation rate lego plot for entire set. Each bin is normalized by base coverage for that bin. Colors represent the six SNV types on the upper right. The three-base context for each mutation is labeled in the 4x4 legend on the lower right. The fractional breakdown of SNV counts is shown in the pie chart on the upper left. If this figure is blank, not enough information was provided in the MAF to generate it.

Figure 4.  Get High-res Image SNV Mutation rate lego plots for 4 slices of mutation allele fraction (0<=AF<0.1, 0.1<=AF<0.25, 0.25<=AF<0.5, & 0.5<=AF) . The color code and three-base context legends are the same as the previous figure. If this figure is blank, not enough information was provided in the MAF to generate it.

CoMut Plot

Figure 5.  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: 8. 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
TP53 233415 68172 50882 90 85 75 3 0 4 4.5 0 320 0.21 0
ATRX 1490645 367783 175617 38 36 38 0 2 1 1.3 4.2e-15 160 0.21 3.8e-11
RB1 703456 185497 120042 26 24 26 0 1 20 0.97 6.6e-15 140 0.2 4e-11
LOR 30875 10127 4940 6 6 2 2 0 20 1.7 4.5e-13 43 0.19 2e-09
NUMBL 157092 50141 28899 8 8 1 0 0 20 0.87 3.2e-11 50 0.21 1.2e-07
KRTAP5-5 131404 38532 5928 9 7 8 1 0 20 0.67 4.6e-10 40 0.2 1.4e-06
PTEN 240578 57798 42978 8 7 8 0 0 20 0.71 9.4e-06 29 0.2 0.025
EOMES 263055 75088 28158 5 5 1 0 0 20 0.68 0.000011 31 0.21 0.026
CABLES1 250952 72124 51623 3 3 1 0 0 20 0.31 0.00041 20 0.18 0.84
MMP3 281827 78299 49153 4 4 4 1 0 20 0.55 0.00093 19 0.23 1
DCDC1 215384 58539 37297 5 5 5 0 0 20 1.8 0.0014 20 0.19 1
OR8D1 173641 53105 6669 5 5 5 0 0 13 0.21 0.0016 16 0.2 1
LTBP3 544141 151411 98059 5 5 2 0 0 19 0.68 0.0021 28 0.22 1
SOX1 58786 16549 1729 2 2 1 0 0 20 1.4 0.0026 14 0.2 1
SCOC 75335 18031 20501 2 2 2 0 0 20 0.4 0.0034 11 0.15 1
OR2V2 179569 52858 6422 4 4 4 1 0 20 1.6 0.004 16 0.21 1
COPS4 243542 63726 49153 4 4 4 0 0 20 0.63 0.0044 16 0.19 1
F11R 176852 53846 50141 4 3 4 0 0 20 0.75 0.0063 15 0.21 1
GRP 64220 13091 10374 2 2 2 0 0 20 0.28 0.0064 8 0.19 1
ZNF880 94601 23465 0 3 3 3 0 0 20 1.1 0.0067 11 0.18 1
SCN2A 1190540 318136 127205 11 11 11 0 0 16 1 0.0068 31 0.22 1
RAB38 123006 33592 14326 2 2 2 0 0 20 0.82 0.0071 12 0.17 1
SUMO3 59280 14820 15314 2 2 2 0 0 20 0.78 0.0071 11 0.14 1
CCDC7 280592 67184 73853 4 4 4 1 0 11 0.71 0.0081 18 0.18 1
CXCL14 48906 11362 14820 2 2 2 0 0 20 2.1 0.0083 11 0.16 1
TNFRSF9 152646 42237 35074 2 2 2 0 0 20 0.74 0.0084 13 0.18 1
GPR123 153634 49894 86944 4 4 4 1 1 10 2 0.0085 20 0.18 1
KRCC1 155857 36556 5928 2 2 2 0 0 20 0.66 0.0085 13 0.17 1
FOXC1 102999 26676 2964 2 2 2 0 0 20 0.45 0.0086 11 0.15 1
GPX5 136344 31863 53352 2 2 2 1 0 20 0.78 0.009 12 0.17 1
RPL41 8151 1482 8151 1 1 1 0 0 20 1.1 0.0097 4.9 0.16 1
FBXO5 244283 64714 20007 3 3 3 0 1 20 0.55 0.01 13 0.19 1
MS4A2 146224 42484 32357 3 3 3 0 0 11 0 0.01 10 0.17 1
CD300LG 181792 59033 31616 3 3 3 0 0 20 0 0.012 11 0.16 1
KLK13 148941 47177 32110 3 3 3 0 1 20 1.1 0.012 13 0.18 1
TP53

Figure S1.  This figure depicts the distribution of mutations and mutation types across the TP53 significant gene.

ATRX

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

RB1

Figure S3.  This figure depicts the distribution of mutations and mutation types across the RB1 significant gene.

LOR

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

NUMBL

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

KRTAP5-5

Figure S6.  This figure depicts the distribution of mutations and mutation types across the KRTAP5-5 significant gene.

PTEN

Figure S7.  This figure depicts the distribution of mutations and mutation types across the PTEN significant gene.

EOMES

Figure S8.  This figure depicts the distribution of mutations and mutation types across the EOMES 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

In addition to the links below, the full results of the analysis summarized in this report can also be downloaded programmatically using firehose_get, or interactively from either the Broad GDAC website or TCGA Data Coordination Center Portal.

References
[1] TCGA, Integrated genomic analyses of ovarian carcinoma, Nature 474:609 - 615 (2011)
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