Mutation Analysis (MutSigCV v0.9)
Stomach Adenocarcinoma (Primary solid tumor)
28 January 2016  |  analyses__2016_01_28
Maintainer Information
Citation Information
doi:10.7908/C17H1J3R
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/C17H1J3R
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: 395

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): 559

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: 559. 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
TP53 373275 109020 78898 202 190 113 2 0 4 0.89 1.9e-15 710 0.48 1.8e-11
ARID1A 1764465 519820 144008 124 99 97 0 0 2 0.3 2.8e-15 450 0.55 1.8e-11
B2M 113365 31600 24512 28 18 19 1 1 20 0.84 4.2e-15 90 0.61 1.8e-11
PIK3CA 1026605 262675 151668 80 65 35 2 0 20 1.1 6.2e-15 160 0.53 1.8e-11
PTEN 384730 92430 66642 39 30 26 4 1 20 0.85 7.1e-15 140 1.7 1.8e-11
RNF43 657675 208165 67025 63 45 26 2 1 8 0.69 7.8e-15 210 0.58 1.8e-11
LARP4B 675055 198290 126007 33 30 12 3 0 2 0.42 7.9e-15 140 0.46 1.8e-11
CBWD1 299410 78605 81579 22 21 3 2 2 5 0.87 8.9e-15 100 1.1 1.8e-11
XYLT2 679005 210140 67408 44 38 15 5 0 16 0.78 8.9e-15 160 0.54 1.8e-11
MUC6 1586715 557740 101495 58 46 54 12 0 20 1.1 1.2e-14 160 0.53 2.1e-11
GNG12 69520 18565 16852 12 12 4 2 0 20 0.72 1.3e-14 64 0.68 2.1e-11
PGM5 423045 125215 68940 41 39 9 3 0 20 0.99 3.1e-14 100 0.45 4.8e-11
DDX59 582230 160765 54386 26 24 7 2 0 20 1.1 6.1e-14 110 0.79 8.5e-11
KRT75 508365 153655 69323 40 38 10 3 0 20 1.3 6.5e-14 120 0.47 8.5e-11
CDH1 771830 229495 132518 33 32 29 3 1 20 0.65 7.2e-14 110 2.3 8.8e-11
LRRN2 623310 215670 7660 39 36 17 9 0 20 0.69 8.4e-14 100 0.49 9.6e-11
MAP2K7 262280 72680 75834 40 27 38 0 2 20 1.2 1.6e-13 90 0.53 1.8e-10
JARID2 1110740 322715 158562 45 37 34 10 0 16 0.7 2.4e-13 130 0.49 2.5e-10
ZFP36L2 199870 64385 6128 14 14 12 1 0 20 0.51 3e-13 72 0.45 2.8e-10
DCDC1 344440 93615 57833 34 30 34 4 0 20 1.7 3.6e-13 99 0.54 3.3e-10
WASF3 465705 139435 129837 22 19 13 3 1 13 0.57 2.5e-12 85 0.44 2.2e-09
PLEKHA6 800665 232655 129071 29 23 18 5 0 20 0.57 3.6e-12 100 0.47 3e-09
OR5M3 280055 79395 9575 20 19 13 1 0 20 0.82 5.5e-12 74 0.49 4.3e-09
SMAD4 522980 145755 85026 32 28 26 1 2 20 0.97 1.4e-11 93 0.47 1.1e-08
IRF2 335750 89665 61663 24 20 21 1 0 20 0.88 2.4e-11 79 0.45 1.7e-08
C4orf6 79000 22515 12256 13 12 7 0 0 20 0.99 5.8e-11 53 1.4 4e-08
KRAS 238975 58460 40598 37 37 6 0 0 1 0.36 1.1e-10 97 0.54 7.5e-08
RHOA 262280 76235 42513 20 19 15 0 0 20 0.68 1.2e-10 66 0.49 7.5e-08
APC 2635440 738650 111453 59 49 52 9 1 4 0.79 1.7e-10 170 0.45 1.1e-07
KLF3 322715 92825 39832 21 19 15 2 0 7 0.85 1.9e-10 81 0.68 1.1e-07
FBXW7 767090 210535 91537 32 31 20 1 2 20 0.89 4e-10 94 0.87 2.3e-07
HLA-B 293090 89665 43662 31 28 26 0 0 1 1.1 7e-10 110 0.44 4e-07
BCOR 1407780 421070 78515 34 28 32 6 0 20 0.88 2e-09 120 0.45 1.1e-06
EDNRB 419490 120475 140178 33 29 24 4 8 4 1.5 2.4e-09 98 0.9 1.3e-06
DST 6207030 1601725 2842626 100 65 97 20 0 0 0.38 2.4e-09 160 0.91 1.3e-06
TP53

Figure S1.  This figure depicts the distribution of mutations and mutation types across the TP53 significant gene.

ARID1A

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

B2M

Figure S3.  This figure depicts the distribution of mutations and mutation types across the B2M significant gene.

PIK3CA

Figure S4.  This figure depicts the distribution of mutations and mutation types across the PIK3CA significant gene.

PTEN

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

RNF43

Figure S6.  This figure depicts the distribution of mutations and mutation types across the RNF43 significant gene.

LARP4B

Figure S7.  This figure depicts the distribution of mutations and mutation types across the LARP4B significant gene.

CBWD1

Figure S8.  This figure depicts the distribution of mutations and mutation types across the CBWD1 significant gene.

XYLT2

Figure S9.  This figure depicts the distribution of mutations and mutation types across the XYLT2 significant gene.

MUC6

Figure S10.  This figure depicts the distribution of mutations and mutation types across the MUC6 significant gene.

GNG12

Figure S11.  This figure depicts the distribution of mutations and mutation types across the GNG12 significant gene.

PGM5

Figure S12.  This figure depicts the distribution of mutations and mutation types across the PGM5 significant gene.

DDX59

Figure S13.  This figure depicts the distribution of mutations and mutation types across the DDX59 significant gene.

KRT75

Figure S14.  This figure depicts the distribution of mutations and mutation types across the KRT75 significant gene.

CDH1

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

LRRN2

Figure S16.  This figure depicts the distribution of mutations and mutation types across the LRRN2 significant gene.

MAP2K7

Figure S17.  This figure depicts the distribution of mutations and mutation types across the MAP2K7 significant gene.

JARID2

Figure S18.  This figure depicts the distribution of mutations and mutation types across the JARID2 significant gene.

ZFP36L2

Figure S19.  This figure depicts the distribution of mutations and mutation types across the ZFP36L2 significant gene.

DCDC1

Figure S20.  This figure depicts the distribution of mutations and mutation types across the DCDC1 significant gene.

WASF3

Figure S21.  This figure depicts the distribution of mutations and mutation types across the WASF3 significant gene.

PLEKHA6

Figure S22.  This figure depicts the distribution of mutations and mutation types across the PLEKHA6 significant gene.

OR5M3

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

SMAD4

Figure S24.  This figure depicts the distribution of mutations and mutation types across the SMAD4 significant gene.

IRF2

Figure S25.  This figure depicts the distribution of mutations and mutation types across the IRF2 significant gene.

C4orf6

Figure S26.  This figure depicts the distribution of mutations and mutation types across the C4orf6 significant gene.

KRAS

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

RHOA

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

APC

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

KLF3

Figure S30.  This figure depicts the distribution of mutations and mutation types across the KLF3 significant gene.

FBXW7

Figure S31.  This figure depicts the distribution of mutations and mutation types across the FBXW7 significant gene.

HLA-B

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

BCOR

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