Mutation Analysis (MutSigCV v0.9)
Bladder Urothelial Carcinoma (Primary solid tumor)
21 August 2015  |  analyses__2015_08_21
Maintainer Information
Citation Information
doi:10.7908/C1SF2VB8
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/C1SF2VB8
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: BLCA-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:BLCA-TP.final_analysis_set.maf

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

  • Significantly mutated genes (q ≤ 0.1): 167

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: BLCA-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: 167. 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
CDKN1A 143385 48190 15211 43 35 33 1 0 20 1.1 0 210 0.26 0
FGFR3 489800 152865 116494 64 56 18 5 1 18 1.1 0 160 0.25 0
RB1 1124960 296645 180306 79 70 70 1 0 20 0.74 0 370 0.25 0
TBC1D12 428575 115340 81620 50 49 4 1 0 5 0.76 0 280 0.26 0
STAG2 1234375 306520 241892 61 56 54 8 0 20 1.4 1.2e-15 260 0.26 4.5e-12
ARID1A 1764465 519820 139496 125 97 110 8 0 2 1.6 1.6e-15 430 0.25 4.7e-12
TP53 373275 109020 76426 228 196 120 7 0 4 2 2e-15 680 0.26 5.2e-12
ELF3 351155 96380 58618 60 46 50 0 0 20 0.76 2.3e-15 200 0.26 5.3e-12
ZFP36L1 301780 96775 16324 32 25 31 1 6 20 0.87 3.8e-15 140 0.25 7.7e-12
CDKN2A 237790 67545 23002 30 26 22 0 0 6 1.4 4.3e-15 110 0.25 7.9e-12
EP300 2260980 635160 231504 78 61 74 7 0 20 1.7 5.2e-15 210 0.26 8.4e-12
KDM6A 1221735 334565 191807 113 103 97 6 0 1 1.9 5.9e-15 460 0.26 8.4e-12
PIK3CA 1026605 262675 146916 94 86 35 4 0 20 1.2 6e-15 200 0.26 8.4e-12
FBXW7 767090 210535 88669 35 30 25 1 6 20 0.83 7.2e-15 120 0.25 9.1e-12
KLF5 342860 99540 22631 24 23 21 3 0 20 1 7.4e-15 87 0.25 9.1e-12
RHOB 176170 52535 7420 30 26 18 0 0 20 0.68 1e-14 82 0.25 1.2e-11
TSC1 1094940 310865 155449 34 33 30 4 0 20 0.76 1.1e-14 160 0.28 1.2e-11
FOXQ1 91245 28045 0 14 14 9 5 0 20 0.74 1.2e-14 72 0.25 1.2e-11
RBM10 609880 172615 112784 21 21 21 4 0 16 0.64 7.4e-14 97 0.25 7.1e-11
ERCC2 732725 218435 185871 38 38 22 3 1 20 0.84 5.1e-13 98 0.42 4.6e-10
ZFP36L2 199870 64385 5936 21 17 16 4 0 20 0.89 7.9e-13 70 0.25 6.9e-10
PTEN 384730 92430 64554 16 14 15 0 0 20 0.46 7.8e-12 65 0.25 6.4e-09
CREBBP 2128260 610670 228907 51 48 48 8 0 11 1.5 1.9e-11 170 0.26 1.5e-08
RHOA 262280 76235 41181 19 18 15 1 3 20 0.51 1e-10 57 0.25 7.9e-08
NFE2L2 556555 147335 30051 25 24 16 0 0 20 0.86 1.4e-10 76 0.25 1e-07
ASXL2 1291255 388680 73829 45 36 40 4 0 17 0.91 1.5e-10 110 0.25 1.1e-07
ATM 2949465 758005 457443 66 53 63 6 0 2 0.53 2.4e-10 150 0.25 1.6e-07
ERBB3 1244250 363005 197372 48 41 38 8 0 20 0.9 1.6e-09 98 0.26 1e-06
TXNIP 369325 105070 60844 20 17 19 4 0 6 0.74 3.1e-09 66 0.25 2e-06
FOXA1 322320 94405 15953 14 14 13 2 0 20 1.3 1.1e-08 68 0.24 6.6e-06
PSIP1 528115 128770 146545 21 20 20 1 0 2 0.72 1.5e-08 84 0.25 9e-06
C3orf70 213695 58065 11872 17 17 10 0 0 20 1.4 2.5e-08 54 0.26 0.000014
ACTB 342465 100725 36358 20 17 16 4 0 20 1 3.4e-08 60 0.25 0.000019
HRAS 182885 52930 31906 16 16 10 1 5 20 1.4 6.7e-08 52 0.25 0.000036
FAT1 4200035 1214230 144319 57 50 56 8 0 2 0.66 1e-07 170 0.26 0.000053
CDKN1A

Figure S1.  This figure depicts the distribution of mutations and mutation types across the CDKN1A significant gene.

FGFR3

Figure S2.  This figure depicts the distribution of mutations and mutation types across the FGFR3 significant gene.

RB1

Figure S3.  This figure depicts the distribution of mutations and mutation types across the RB1 significant gene.

TBC1D12

Figure S4.  This figure depicts the distribution of mutations and mutation types across the TBC1D12 significant gene.

STAG2

Figure S5.  This figure depicts the distribution of mutations and mutation types across the STAG2 significant gene.

ARID1A

Figure S6.  This figure depicts the distribution of mutations and mutation types across the ARID1A significant gene.

TP53

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

ZFP36L1

Figure S8.  This figure depicts the distribution of mutations and mutation types across the ZFP36L1 significant gene.

CDKN2A

Figure S9.  This figure depicts the distribution of mutations and mutation types across the CDKN2A significant gene.

EP300

Figure S10.  This figure depicts the distribution of mutations and mutation types across the EP300 significant gene.

KDM6A

Figure S11.  This figure depicts the distribution of mutations and mutation types across the KDM6A significant gene.

PIK3CA

Figure S12.  This figure depicts the distribution of mutations and mutation types across the PIK3CA significant gene.

FBXW7

Figure S13.  This figure depicts the distribution of mutations and mutation types across the FBXW7 significant gene.

KLF5

Figure S14.  This figure depicts the distribution of mutations and mutation types across the KLF5 significant gene.

RHOB

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

TSC1

Figure S16.  This figure depicts the distribution of mutations and mutation types across the TSC1 significant gene.

FOXQ1

Figure S17.  This figure depicts the distribution of mutations and mutation types across the FOXQ1 significant gene.

RBM10

Figure S18.  This figure depicts the distribution of mutations and mutation types across the RBM10 significant gene.

ERCC2

Figure S19.  This figure depicts the distribution of mutations and mutation types across the ERCC2 significant gene.

ZFP36L2

Figure S20.  This figure depicts the distribution of mutations and mutation types across the ZFP36L2 significant gene.

PTEN

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

CREBBP

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

RHOA

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

NFE2L2

Figure S24.  This figure depicts the distribution of mutations and mutation types across the NFE2L2 significant gene.

ASXL2

Figure S25.  This figure depicts the distribution of mutations and mutation types across the ASXL2 significant gene.

ATM

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

ERBB3

Figure S27.  This figure depicts the distribution of mutations and mutation types across the ERBB3 significant gene.

TXNIP

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

FOXA1

Figure S29.  This figure depicts the distribution of mutations and mutation types across the FOXA1 significant gene.

PSIP1

Figure S30.  This figure depicts the distribution of mutations and mutation types across the PSIP1 significant gene.

C3orf70

Figure S31.  This figure depicts the distribution of mutations and mutation types across the C3orf70 significant gene.

ACTB

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

HRAS

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