Mutation Analysis (MutSigCV v0.9)
Stomach Adenocarcinoma (Primary solid tumor)
02 April 2015  |  analyses__2015_04_02
Maintainer Information
Citation Information
doi:10.7908/C12V2F7K
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/C12V2F7K
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: STAD-TP

  • Number of patients in set: 289

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:STAD-TP.final_analysis_set.maf

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

  • Significantly mutated genes (q ≤ 0.1): 111

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: STAD-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: 111. 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
PTEN 281486 67626 0 33 23 22 4 0 20 0.78 0 100 0.21 0
ARID1A 1290963 380324 0 119 90 83 4 0 2 0.63 3.3e-16 390 0.22 3e-12
PIK3CA 751111 192185 0 72 57 34 2 0 20 0.91 1.7e-15 130 0.21 9.6e-12
TP53 273105 79764 0 148 137 89 1 0 4 1 2.1e-15 490 0.21 9.6e-12
RNF43 481185 152303 0 63 49 19 2 0 8 0.56 4.1e-15 240 0.22 1.5e-11
XYLT2 496791 153748 0 35 32 10 3 0 16 0.8 6e-15 140 0.21 1.8e-11
BZRAP1 1062653 338708 0 47 46 17 5 0 2 1.1 7.4e-15 190 0.21 1.9e-11
B2M 82943 23120 0 30 17 18 1 0 20 0.64 9e-15 84 0.2 2.1e-11
GNG12 50864 13583 0 11 11 3 2 0 20 0.7 4.4e-14 57 0.2 8.9e-11
LMAN1 354025 95081 0 22 22 5 2 0 10 0.87 6.2e-14 110 0.21 1.1e-10
MLL2 3060799 1011789 0 102 65 73 12 0 20 0.82 2.8e-13 200 0.21 4.7e-10
PSME4 1219869 327437 0 42 35 16 5 0 20 0.91 1.2e-11 130 0.22 1.8e-08
SMAD4 382636 106641 0 28 24 23 1 0 20 0.97 1.5e-09 82 0.21 2.1e-06
PLEKHA6 585803 170221 0 26 20 18 1 0 20 0.54 2.6e-09 86 0.21 3.4e-06
CDH1 564706 167909 0 30 29 27 4 0 20 0.93 4.8e-09 93 0.21 5.9e-06
CRYGD 106641 29189 0 12 12 5 2 0 20 1.3 6.4e-09 59 0.21 7.3e-06
RHOA 191896 55777 0 17 16 13 0 0 20 0.37 7.8e-09 52 0.21 8.3e-06
MBD6 644759 244783 0 31 23 18 2 0 20 1.1 1.2e-08 94 0.21 0.000013
JARID2 812668 236113 0 34 28 22 6 0 16 0.71 4.5e-08 96 0.21 0.000044
LARP4B 493901 145078 0 29 27 8 2 0 2 0.65 5.9e-08 120 0.21 0.000052
DDX6 322524 88434 0 15 15 4 1 0 3 0.45 6e-08 74 0.2 0.000052
CD4 302872 89012 0 15 15 6 3 0 20 0.84 7.1e-08 63 0.2 0.000059
OR5M3 204901 58089 0 16 15 9 1 0 20 1 8.7e-08 57 0.2 0.000069
TLE2 322524 93925 0 21 19 13 4 0 20 0.9 1e-07 70 0.21 0.000079
ATP6V1B1 340731 101439 0 22 20 10 2 0 20 1.2 1.1e-07 80 0.22 8e-05
DNAJC18 251141 66470 0 13 13 5 0 0 20 0.79 1.1e-07 57 0.2 8e-05
KLF3 236113 67915 0 22 19 14 2 0 7 1.2 1.4e-07 74 0.21 0.000096
HLA-C 239581 73695 0 13 13 9 0 0 20 0.58 1.6e-07 57 0.2 0.0001
FBXW7 561238 154037 0 28 27 18 1 0 20 0.86 2.5e-07 76 0.21 0.00016
CTCF 509796 130628 0 19 18 11 2 0 20 0.75 3.1e-07 72 0.2 0.00019
PCDHAC2 623951 198543 0 40 24 36 10 0 20 1 3.3e-07 80 0.2 0.0002
ZNF43 567596 134963 0 41 34 17 3 0 1 0.97 4.6e-07 120 0.21 0.00026
APC 1928208 540430 0 53 42 46 7 0 4 0.62 5.2e-07 130 0.21 0.00029
EDNRB 306918 88145 0 30 27 22 5 0 4 1.3 5.7e-07 84 0.2 0.00031
PGM5 309519 91613 0 29 25 7 0 0 20 0.86 1.1e-06 59 0.2 0.00057
PTEN

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

ARID1A

Figure S2.  This figure depicts the distribution of mutations and mutation types across the ARID1A significant gene.

PIK3CA

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

TP53

Figure S4.  This figure depicts the distribution of mutations and mutation types across the TP53 significant gene.

RNF43

Figure S5.  This figure depicts the distribution of mutations and mutation types across the RNF43 significant gene.

XYLT2

Figure S6.  This figure depicts the distribution of mutations and mutation types across the XYLT2 significant gene.

BZRAP1

Figure S7.  This figure depicts the distribution of mutations and mutation types across the BZRAP1 significant gene.

B2M

Figure S8.  This figure depicts the distribution of mutations and mutation types across the B2M significant gene.

GNG12

Figure S9.  This figure depicts the distribution of mutations and mutation types across the GNG12 significant gene.

LMAN1

Figure S10.  This figure depicts the distribution of mutations and mutation types across the LMAN1 significant gene.

MLL2

Figure S11.  This figure depicts the distribution of mutations and mutation types across the MLL2 significant gene.

PSME4

Figure S12.  This figure depicts the distribution of mutations and mutation types across the PSME4 significant gene.

SMAD4

Figure S13.  This figure depicts the distribution of mutations and mutation types across the SMAD4 significant gene.

PLEKHA6

Figure S14.  This figure depicts the distribution of mutations and mutation types across the PLEKHA6 significant gene.

CDH1

Figure S15.  This figure depicts the distribution of mutations and mutation types across the CDH1 significant gene.

CRYGD

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

RHOA

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

MBD6

Figure S18.  This figure depicts the distribution of mutations and mutation types across the MBD6 significant gene.

JARID2

Figure S19.  This figure depicts the distribution of mutations and mutation types across the JARID2 significant gene.

LARP4B

Figure S20.  This figure depicts the distribution of mutations and mutation types across the LARP4B significant gene.

DDX6

Figure S21.  This figure depicts the distribution of mutations and mutation types across the DDX6 significant gene.

CD4

Figure S22.  This figure depicts the distribution of mutations and mutation types across the CD4 significant gene.

OR5M3

Figure S23.  This figure depicts the distribution of mutations and mutation types across the OR5M3 significant gene.

TLE2

Figure S24.  This figure depicts the distribution of mutations and mutation types across the TLE2 significant gene.

ATP6V1B1

Figure S25.  This figure depicts the distribution of mutations and mutation types across the ATP6V1B1 significant gene.

DNAJC18

Figure S26.  This figure depicts the distribution of mutations and mutation types across the DNAJC18 significant gene.

KLF3

Figure S27.  This figure depicts the distribution of mutations and mutation types across the KLF3 significant gene.

HLA-C

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

FBXW7

Figure S29.  This figure depicts the distribution of mutations and mutation types across the FBXW7 significant gene.

CTCF

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

PCDHAC2

Figure S31.  This figure depicts the distribution of mutations and mutation types across the PCDHAC2 significant gene.

ZNF43

Figure S32.  This figure depicts the distribution of mutations and mutation types across the ZNF43 significant gene.

APC

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

EDNRB

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