Mutation Analysis (MutSigCV v0.9)
Glioma (Primary solid tumor)
28 January 2016  |  analyses__2016_01_28
Maintainer Information
Citation Information
doi:10.7908/C1QN664P
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/C1QN664P
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: 799

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): 53

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: 53. 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
IDH1 804597 207738 104120 415 415 2 0 0 13 0.7 0 1500 0.73 0
NOTCH1 3191117 922252 242798 55 42 43 3 0 20 1 0 190 0.73 0
PIK3CA 2076627 531339 254188 83 75 48 0 0 20 1.3 0 270 0.69 0
PTEN 778152 186948 111688 114 111 89 0 1 20 0.86 0 540 0.74 0
TP53 755055 220524 131242 420 331 166 2 0 4 1.5 0 1200 0.77 0
ATRX 4822025 1189725 456568 234 209 201 9 0 1 2.4 2.4e-15 1000 0.74 6.7e-12
EGFR 2460906 672754 380448 137 109 62 8 1 20 1 2.6e-15 340 0.65 6.7e-12
CIC 2491290 902874 208960 127 109 90 1 0 8 0.71 4e-15 470 0.65 9.1e-12
RB1 2275608 600063 315578 32 30 28 1 0 20 1.2 9.2e-15 170 0.81 1.9e-11
NF1 7520292 2107784 763218 86 62 79 4 0 0 0.73 1.3e-14 300 0.73 2.3e-11
FUBP1 1229663 362744 253418 51 48 46 1 0 5 0.54 1.5e-14 290 0.69 2.5e-11
PIK3R1 1489358 382725 222184 57 54 41 2 0 20 1.3 1.8e-14 270 0.69 2.7e-11
TCF12 1400665 401100 260422 21 19 19 0 0 7 1.5 1.3e-13 110 0.71 1.8e-10
IDH2 733484 193358 114976 20 20 3 0 0 20 0.93 5.5e-13 74 0.68 7.1e-10
BCOR 2847754 851760 131016 23 21 23 9 0 20 1.2 5.2e-11 100 0.65 6.3e-08
STAG2 2496873 620022 417308 18 16 18 1 0 20 1.2 1.1e-08 86 0.76 0.000013
SMARCA4 2588189 731950 354326 29 27 26 6 1 20 1.4 7e-08 93 0.78 0.000076
CDKN2C 312413 95081 27214 6 6 6 0 0 20 0.98 8.1e-08 39 0.62 0.000082
TPTE2 1023561 266075 332178 13 13 10 0 0 14 1.1 1.2e-07 60 1 0.00012
CREBZF 600019 203735 9708 9 9 3 0 0 20 1.3 1.5e-07 53 0.68 0.00014
GABRA6 865303 245289 117934 15 15 12 2 0 20 1.1 1.8e-07 52 0.74 0.00016
NIPBL 5331024 1413457 563582 26 20 25 1 0 20 0.91 5.9e-07 95 1.5 0.00049
FLG 7341298 2178899 28402 65 60 64 21 0 15 1.7 7.9e-07 140 0.66 0.00063
IL18RAP 1148970 314009 131072 10 10 10 2 0 14 0.45 5.7e-06 42 0.76 0.0044
SOX4 305288 95103 3142 8 7 8 1 0 20 0.85 6.5e-06 34 0.73 0.0047
ARID1A 3569141 1051486 241790 28 22 28 4 0 2 1.2 7.5e-06 110 0.65 0.0052
RPL5 583270 149413 278238 10 10 10 0 0 2 0.72 8.5e-06 47 1.9 0.0058
UGT2A3 999565 271664 77764 12 11 12 0 0 20 1.1 0.000014 41 0.74 0.0091
AFM 1180922 288439 178288 10 10 10 1 0 20 0.67 0.000017 39 0.64 0.011
OR9G1 558503 170988 17256 9 8 9 2 0 20 1.2 0.000019 34 3.6 0.012
EMG1 543308 165389 78880 5 5 2 0 0 20 1 0.000022 34 0.78 0.013
GFRA4 68736 26375 17108 3 3 3 1 0 20 0.97 0.000027 20 0.72 0.015
MYH4 3780093 975585 488164 22 22 22 1 0 19 1.3 0.000031 73 0.67 0.017
DDX5 1174534 319600 161728 9 9 6 0 0 20 0.91 0.000034 43 0.63 0.018
DLX6 258041 74297 15380 5 5 3 0 0 20 1.5 0.000037 29 0.61 0.019
IDH1

Figure S1.  This figure depicts the distribution of mutations and mutation types across the IDH1 significant gene.

NOTCH1

Figure S2.  This figure depicts the distribution of mutations and mutation types across the NOTCH1 significant gene.

PIK3CA

Figure S3.  This figure depicts the distribution of mutations and mutation types across the PIK3CA 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.

ATRX

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

EGFR

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

CIC

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

RB1

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

NF1

Figure S10.  This figure depicts the distribution of mutations and mutation types across the NF1 significant gene.

FUBP1

Figure S11.  This figure depicts the distribution of mutations and mutation types across the FUBP1 significant gene.

PIK3R1

Figure S12.  This figure depicts the distribution of mutations and mutation types across the PIK3R1 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.

SMARCA4

Figure S17.  This figure depicts the distribution of mutations and mutation types across the SMARCA4 significant gene.

CDKN2C

Figure S18.  This figure depicts the distribution of mutations and mutation types across the CDKN2C significant gene.

TPTE2

Figure S19.  This figure depicts the distribution of mutations and mutation types across the TPTE2 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.

IL18RAP

Figure S24.  This figure depicts the distribution of mutations and mutation types across the IL18RAP significant gene.

SOX4

Figure S25.  This figure depicts the distribution of mutations and mutation types across the SOX4 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.

UGT2A3

Figure S28.  This figure depicts the distribution of mutations and mutation types across the UGT2A3 significant gene.

AFM

Figure S29.  This figure depicts the distribution of mutations and mutation types across the AFM 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.

MYH4

Figure S32.  This figure depicts the distribution of mutations and mutation types across the MYH4 significant gene.

DDX5

Figure S33.  This figure depicts the distribution of mutations and mutation types across the DDX5 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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