Mutation Analysis (MutSigCV v0.6)
Glioblastoma Multiforme (Primary solid tumor)
22 February 2013  |  analyses__2013_02_22
Maintainer Information
Citation Information
doi:10.7908/C11834PW
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/C11834PW
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: GBM-TP

  • Number of patients in set: 291

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: GBM-TP.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: 17. 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
PIK3CA 756309 193515 0 35 32 28 0 0 20 0.96 2.7e-15 100 0.27 1.6e-11
TP53 274995 80316 0 100 83 61 1 0 4 1 3.7e-15 280 0.27 1.6e-11
NF1 2738892 767658 0 34 32 33 1 0 0 0.5 3.9e-15 160 0.27 1.6e-11
EGFR 896280 245022 0 95 77 45 7 0 20 1.5 4.1e-15 200 0.28 1.6e-11
RB1 828768 218541 0 24 24 22 1 0 20 0.78 4.3e-15 140 0.27 1.6e-11
PTEN 283434 68094 0 93 90 75 0 0 20 0.43 5.3e-15 430 0.28 1.6e-11
PIK3R1 542424 139389 0 34 33 28 0 0 20 1 6.7e-15 150 0.28 1.7e-11
STAG2 909375 225816 0 12 12 12 0 0 20 0.69 1.1e-08 63 0.27 0.000023
IDH1 293037 75660 0 15 15 2 0 0 13 0.65 1.1e-08 47 0.26 0.000023
RPL5 212430 54417 0 8 8 8 0 0 2 0.8 3.9e-07 43 0.33 0.0007
PRB2 256662 93411 0 6 6 2 0 0 12 1.7 0.000018 37 0.26 0.029
GABRA6 315153 89337 0 11 11 10 1 0 20 0.98 0.000024 34 0.26 0.036
QKI 258408 74205 0 5 5 5 0 0 12 0.3 0.000026 26 0.25 0.037
TPTE2 372771 96903 0 8 8 6 0 0 14 0.61 0.000031 33 0.26 0.04
CD3EAP 338724 107961 0 3 3 1 0 0 20 0 0.000041 20 0.25 0.05
LZTR1 510996 145791 0 10 10 10 0 0 20 0.4 0.000067 33 0.26 0.077
ZPBP 221160 58782 0 5 5 4 0 0 5 0 0.000081 21 0.25 0.087
TAS2R41 206319 61983 0 5 4 4 0 0 20 0.23 0.00011 20 0.24 0.11
LCE4A 68385 18624 0 2 2 1 0 0 20 0.17 0.00014 14 0.19 0.13
CDC27 566868 153357 0 7 6 3 0 0 20 0.91 0.00014 35 0.26 0.13
ZNF697 120765 31137 0 3 3 3 0 0 20 0 0.00021 15 0.23 0.18
CDKN2C 113781 34629 0 3 3 3 0 0 20 0.93 0.0003 20 0.25 0.24
HIST1H2BE 84390 26190 0 3 3 3 0 0 20 0.58 0.00042 17 0.24 0.33
CYP3A5 353274 97776 0 5 5 5 0 0 20 0.21 0.00082 18 0.24 0.62
AP3S1 162378 45105 0 3 3 3 0 0 9 0 0.0012 14 0.24 0.88
ATF7IP2 476949 125712 0 5 5 5 0 0 20 0.18 0.0013 17 0.24 0.93
SPTA1 1721556 443775 0 29 27 27 1 0 0 0.86 0.0015 69 0.27 1
ATRX 1756185 433299 0 17 17 17 2 0 1 1.4 0.002 72 0.28 1
PASD1 497610 133278 0 5 5 4 0 0 11 0.31 0.0025 22 0.25 1
ATG12 101268 30264 0 2 2 2 0 0 8 0.34 0.0026 14 0.23 1
PSPH 171690 49470 0 5 5 3 0 0 19 1.1 0.0027 19 0.26 1
LRRC55 226689 71004 0 6 6 6 1 0 20 0.99 0.0029 21 0.27 1
GLIS1 320682 104760 0 4 4 4 0 0 20 0.21 0.0033 17 0.24 1
DDX5 427770 116400 0 4 4 3 0 0 20 0.62 0.0035 21 0.26 1
OR5AR1 208647 60819 0 7 7 7 0 0 20 1.6 0.004 21 0.25 1
PIK3CA

Figure S1.  This figure depicts the distribution of mutations and mutation types across the PIK3CA significant gene.

TP53

Figure S2.  This figure depicts the distribution of mutations and mutation types across the TP53 significant gene.

NF1

Figure S3.  This figure depicts the distribution of mutations and mutation types across the NF1 significant gene.

EGFR

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

RB1

Figure S5.  This figure depicts the distribution of mutations and mutation types across the RB1 significant gene.

PTEN

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

PIK3R1

Figure S7.  This figure depicts the distribution of mutations and mutation types across the PIK3R1 significant gene.

STAG2

Figure S8.  This figure depicts the distribution of mutations and mutation types across the STAG2 significant gene.

IDH1

Figure S9.  This figure depicts the distribution of mutations and mutation types across the IDH1 significant gene.

RPL5

Figure S10.  This figure depicts the distribution of mutations and mutation types across the RPL5 significant gene.

GABRA6

Figure S11.  This figure depicts the distribution of mutations and mutation types across the GABRA6 significant gene.

QKI

Figure S12.  This figure depicts the distribution of mutations and mutation types across the QKI significant gene.

TPTE2

Figure S13.  This figure depicts the distribution of mutations and mutation types across the TPTE2 significant gene.

CD3EAP

Figure S14.  This figure depicts the distribution of mutations and mutation types across the CD3EAP significant gene.

LZTR1

Figure S15.  This figure depicts the distribution of mutations and mutation types across the LZTR1 significant gene.

ZPBP

Figure S16.  This figure depicts the distribution of mutations and mutation types across the ZPBP 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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