Mutation Analysis (MutSigCV v0.9)
Glioma (Primary solid tumor)
02 April 2015  |  analyses__2015_04_02
Maintainer Information
Citation Information
doi:10.7908/C18G8JRW
Maintained by David Heiman (Broad Institute)
Cite as Broad Institute TCGA Genome Data Analysis Center (2015): Mutation Analysis (MutSigCV v0.9). Broad Institute of MIT and Harvard. doi:10.7908/C18G8JRW
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: GBMLGG-TP

  • Number of patients in set: 796

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:GBMLGG-TP.final_analysis_set.maf

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

  • Significantly mutated genes (q ≤ 0.1): 41

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: GBMLGG-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: 41. 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
ATRX 4803920 1185258 376936 230 206 198 9 0 1 2.5 0 1000 0.65 0
EGFR 2451666 670228 314592 138 109 63 8 0 20 0.84 0 350 0.59 0
IDH1 801576 206958 85976 412 412 2 0 0 13 0.62 0 1500 0.75 0
NF1 7492056 2099870 630610 86 62 79 3 0 0 0.58 0 300 0.58 0
NOTCH1 3179138 918790 200238 55 42 43 3 0 20 1.1 0 190 0.58 0
PIK3R1 1483766 381288 183544 57 54 41 2 0 20 1.3 0 270 0.59 0
TP53 752220 219696 108170 415 327 166 3 0 4 1.9 0 1200 0.66 0
PIK3CA 2068830 529344 209836 83 75 48 0 0 20 1.2 7.8e-16 270 0.59 1.8e-12
PTEN 775230 186246 92200 115 112 90 0 0 20 0.84 6.2e-15 540 0.6 1.2e-11
PCDHAC2 1718638 546876 33220 47 40 47 36 0 20 1.3 6.7e-15 110 0.58 1.2e-11
CIC 2481936 899484 172224 127 109 90 1 0 8 0.74 8e-15 470 0.61 1.3e-11
RB1 2267064 597810 261146 31 30 27 1 0 20 1.1 9.5e-15 170 0.71 1.5e-11
FUBP1 1225046 361382 209066 51 48 46 1 0 5 0.58 1.5e-14 290 0.61 2.2e-11
TCF12 1395406 399594 215510 21 19 19 0 0 7 1.5 1.2e-13 110 0.58 1.6e-10
IDH2 730730 192632 94928 20 20 3 0 0 20 0.92 5.9e-13 74 0.6 7.1e-10
BCOR 2837062 848562 108056 22 21 22 9 0 20 1.3 1.1e-10 100 0.69 1.2e-07
PCDHGC5 1703456 562780 38914 48 45 48 16 0 5 3.2 1.9e-09 120 0.6 2e-06
TPTE2 1019718 265076 274050 13 13 10 0 0 14 0.58 3.1e-08 58 0.56 3e-05
CREBZF 597766 202970 8028 9 9 3 0 0 20 1 3.2e-08 54 3.4 3e-05
STAG2 2487498 617694 344284 17 16 17 1 0 20 1.2 4.3e-08 83 1.3 0.000037
EMG1 541268 164768 65104 7 7 3 0 0 20 1.1 4.3e-08 48 0.55 0.000037
SMARCA4 2578472 729202 292614 30 27 27 6 0 20 1.3 5.2e-08 93 1.2 0.000043
CDKN2C 311240 94724 22510 6 6 6 0 0 20 1 1.1e-07 39 0.63 9e-05
FLG 7313734 2170718 23474 64 60 63 21 0 15 1.7 3.1e-07 140 0.57 0.00023
NIPBL 5311008 1408150 465358 26 20 25 1 0 20 0.97 4.5e-07 98 0.58 0.00033
GABRA6 862054 244368 97438 15 15 12 2 0 20 1.1 8.4e-07 49 0.55 0.00059
SOX4 304142 94746 2582 8 7 8 0 0 20 0.9 8.7e-06 34 0.57 0.0059
ARID1A 3555740 1047538 199678 28 22 28 4 0 2 1.2 0.000014 110 0.78 0.0094
RPL5 581080 148852 228958 10 10 10 0 0 2 0.78 0.000015 46 0.58 0.0097
GFRA4 68478 26276 14084 3 3 3 1 0 20 0.96 0.000028 19 0.52 0.017
DDX5 1170124 318400 133392 9 9 6 0 0 20 0.97 0.000051 43 0.56 0.03
AFM 1176488 287356 147152 10 10 10 1 0 20 0.66 0.000063 36 0.55 0.036
UGT2A3 995812 270644 64212 12 11 12 0 0 20 1.2 0.000071 38 1.1 0.039
ARL6 370148 93134 76112 6 6 6 0 0 20 0.68 0.00013 25 0.65 0.072
OR8K3 570736 170344 12566 10 10 10 1 0 9 1.8 0.00014 39 0.55 0.072
ATRX

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

EGFR

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

IDH1

Figure S3.  This figure depicts the distribution of mutations and mutation types across the IDH1 significant gene.

NF1

Figure S4.  This figure depicts the distribution of mutations and mutation types across the NF1 significant gene.

NOTCH1

Figure S5.  This figure depicts the distribution of mutations and mutation types across the NOTCH1 significant gene.

PIK3R1

Figure S6.  This figure depicts the distribution of mutations and mutation types across the PIK3R1 significant gene.

TP53

Figure S7.  This figure depicts the distribution of mutations and mutation types across the TP53 significant gene.

PIK3CA

Figure S8.  This figure depicts the distribution of mutations and mutation types across the PIK3CA significant gene.

PTEN

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

PCDHAC2

Figure S10.  This figure depicts the distribution of mutations and mutation types across the PCDHAC2 significant gene.

CIC

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

RB1

Figure S12.  This figure depicts the distribution of mutations and mutation types across the RB1 significant gene.

FUBP1

Figure S13.  This figure depicts the distribution of mutations and mutation types across the FUBP1 significant gene.

TCF12

Figure S14.  This figure depicts the distribution of mutations and mutation types across the TCF12 significant gene.

IDH2

Figure S15.  This figure depicts the distribution of mutations and mutation types across the IDH2 significant gene.

BCOR

Figure S16.  This figure depicts the distribution of mutations and mutation types across the BCOR significant gene.

PCDHGC5

Figure S17.  This figure depicts the distribution of mutations and mutation types across the PCDHGC5 significant gene.

TPTE2

Figure S18.  This figure depicts the distribution of mutations and mutation types across the TPTE2 significant gene.

CREBZF

Figure S19.  This figure depicts the distribution of mutations and mutation types across the CREBZF significant gene.

STAG2

Figure S20.  This figure depicts the distribution of mutations and mutation types across the STAG2 significant gene.

EMG1

Figure S21.  This figure depicts the distribution of mutations and mutation types across the EMG1 significant gene.

SMARCA4

Figure S22.  This figure depicts the distribution of mutations and mutation types across the SMARCA4 significant gene.

CDKN2C

Figure S23.  This figure depicts the distribution of mutations and mutation types across the CDKN2C significant gene.

FLG

Figure S24.  This figure depicts the distribution of mutations and mutation types across the FLG significant gene.

NIPBL

Figure S25.  This figure depicts the distribution of mutations and mutation types across the NIPBL significant gene.

GABRA6

Figure S26.  This figure depicts the distribution of mutations and mutation types across the GABRA6 significant gene.

SOX4

Figure S27.  This figure depicts the distribution of mutations and mutation types across the SOX4 significant gene.

ARID1A

Figure S28.  This figure depicts the distribution of mutations and mutation types across the ARID1A significant gene.

RPL5

Figure S29.  This figure depicts the distribution of mutations and mutation types across the RPL5 significant gene.

GFRA4

Figure S30.  This figure depicts the distribution of mutations and mutation types across the GFRA4 significant gene.

DDX5

Figure S31.  This figure depicts the distribution of mutations and mutation types across the DDX5 significant gene.

AFM

Figure S32.  This figure depicts the distribution of mutations and mutation types across the AFM significant gene.

UGT2A3

Figure S33.  This figure depicts the distribution of mutations and mutation types across the UGT2A3 significant gene.

ARL6

Figure S34.  This figure depicts the distribution of mutations and mutation types across the ARL6 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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