Mutation Analysis (MutSigCV v0.9)
Glioma (Primary solid tumor)
21 August 2015  |  analyses__2015_08_21
Maintainer Information
Citation Information
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/C16M3616
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): 52

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: 52. 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
FUBP1 1225046 361382 253022 51 48 46 1 0 5 0.55 0 290 0.61 0
IDH1 801576 206958 103958 412 412 2 0 0 13 0.71 0 1500 0.67 0
NF1 7492056 2099870 762034 86 62 79 3 0 0 0.56 0 300 0.61 0
NOTCH1 3179138 918790 242418 55 42 43 3 0 20 1.1 0 190 0.59 0
PIK3R1 1483766 381288 221839 57 54 41 2 0 20 1.2 0 270 0.59 0
CIC 2481936 899484 208632 127 109 90 1 0 8 0.72 3.9e-15 470 0.65 1.2e-11
TP53 752220 219696 131036 416 328 166 2 0 4 1.5 5.7e-15 1200 0.69 1.3e-11
PTEN 775230 186246 111514 114 111 89 0 1 20 0.87 5.8e-15 540 0.6 1.3e-11
RB1 2267064 597810 315092 31 30 27 1 0 20 1.2 8.2e-15 170 0.6 1.7e-11
PIK3CA 2068830 529344 253792 83 75 48 0 0 20 1.3 1.1e-14 270 0.61 1.9e-11
EGFR 2451666 670228 379860 137 109 62 8 1 20 1 1.1e-14 340 0.61 1.9e-11
ATRX 4803920 1185258 455857 230 206 198 9 0 1 2.4 1.4e-14 1000 0.68 2.1e-11
TCF12 1395406 399594 260021 21 19 19 0 0 7 1.6 1.2e-13 110 0.58 1.7e-10
IDH2 730730 192632 114797 20 20 3 0 0 20 0.88 3.1e-13 74 0.61 4e-10
BCOR 2837062 848562 130811 22 21 22 9 0 20 1.2 5.4e-11 100 0.61 6.6e-08
STAG2 2487498 617694 416656 17 16 17 1 0 20 1.2 1.2e-08 86 0.58 0.000014
TPTE2 1019718 265076 331659 13 13 10 0 0 14 0.89 3.8e-08 61 0.59 0.000041
SMARCA4 2578472 729202 353775 29 27 26 6 1 20 1.3 4.1e-08 93 0.59 0.000042
CDKN2C 311240 94724 27172 6 6 6 0 0 20 1 8.1e-08 39 0.58 0.000078
CREBZF 597766 202970 9693 9 9 3 0 0 20 1.3 1.1e-07 53 0.62 0.000099
GABRA6 862054 244368 117751 15 15 12 2 0 20 1.2 1.8e-07 52 0.58 0.00016
NIPBL 5311008 1408150 562705 26 20 25 1 0 20 0.93 6e-07 95 0.61 0.00049
FLG 7313734 2170718 28358 64 60 63 21 0 15 1.8 8.6e-07 140 0.61 0.00068
EMG1 541268 164768 78757 6 6 2 0 0 20 1.1 9.8e-07 41 0.59 0.00075
SOX4 304142 94746 3137 8 7 8 0 0 20 0.78 4.6e-06 34 0.56 0.0034
IL18RAP 1144656 312830 130869 10 10 10 2 0 14 0.45 5.8e-06 42 0.56 0.0041
ARID1A 3555740 1047538 241414 28 22 28 4 0 2 1.2 7.5e-06 110 0.61 0.0051
RPL5 581080 148852 277798 10 10 10 0 0 2 0.74 8.4e-06 47 0.59 0.0055
AFM 1176488 287356 178010 10 10 10 1 0 20 0.63 0.000012 39 0.63 0.0077
UGT2A3 995812 270644 77643 12 11 12 0 0 20 1.1 0.000014 41 0.58 0.0087
OR9G1 556406 170346 17229 9 8 9 2 0 20 1.3 0.000019 34 0.57 0.011
GFRA4 68478 26276 17081 3 3 3 1 0 20 0.92 0.000024 20 0.5 0.013
DDX5 1170124 318400 161475 9 9 6 0 0 20 0.93 0.000034 43 0.61 0.019
EIF1AX 281790 66068 77290 5 5 4 1 0 20 0.62 0.000048 24 0.56 0.026
MYH4 3765900 971922 487403 21 21 21 1 0 19 1.3 0.000064 71 0.59 0.034
FUBP1

Figure S1.  This figure depicts the distribution of mutations and mutation types across the FUBP1 significant gene.

IDH1

Figure S2.  This figure depicts the distribution of mutations and mutation types across the IDH1 significant gene.

NF1

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

NOTCH1

Figure S4.  This figure depicts the distribution of mutations and mutation types across the NOTCH1 significant gene.

PIK3R1

Figure S5.  This figure depicts the distribution of mutations and mutation types across the PIK3R1 significant gene.

CIC

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

TP53

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

PTEN

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

RB1

Figure S9.  This figure depicts the distribution of mutations and mutation types across the RB1 significant gene.

PIK3CA

Figure S10.  This figure depicts the distribution of mutations and mutation types across the PIK3CA significant gene.

EGFR

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

ATRX

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

TCF12

Figure S13.  This figure depicts the distribution of mutations and mutation types across the TCF12 significant gene.

IDH2

Figure S14.  This figure depicts the distribution of mutations and mutation types across the IDH2 significant gene.

BCOR

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

STAG2

Figure S16.  This figure depicts the distribution of mutations and mutation types across the STAG2 significant gene.

TPTE2

Figure S17.  This figure depicts the distribution of mutations and mutation types across the TPTE2 significant gene.

SMARCA4

Figure S18.  This figure depicts the distribution of mutations and mutation types across the SMARCA4 significant gene.

CDKN2C

Figure S19.  This figure depicts the distribution of mutations and mutation types across the CDKN2C significant gene.

CREBZF

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

GABRA6

Figure S21.  This figure depicts the distribution of mutations and mutation types across the GABRA6 significant gene.

NIPBL

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

FLG

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

SOX4

Figure S24.  This figure depicts the distribution of mutations and mutation types across the SOX4 significant gene.

IL18RAP

Figure S25.  This figure depicts the distribution of mutations and mutation types across the IL18RAP significant gene.

ARID1A

Figure S26.  This figure depicts the distribution of mutations and mutation types across the ARID1A significant gene.

RPL5

Figure S27.  This figure depicts the distribution of mutations and mutation types across the RPL5 significant gene.

AFM

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

UGT2A3

Figure S29.  This figure depicts the distribution of mutations and mutation types across the UGT2A3 significant gene.

OR9G1

Figure S30.  This figure depicts the distribution of mutations and mutation types across the OR9G1 significant gene.

GFRA4

Figure S31.  This figure depicts the distribution of mutations and mutation types across the GFRA4 significant gene.

DDX5

Figure S32.  This figure depicts the distribution of mutations and mutation types across the DDX5 significant gene.

EIF1AX

Figure S33.  This figure depicts the distribution of mutations and mutation types across the EIF1AX 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)