Mutation Analysis (MutSigCV v0.9)
Bladder Urothelial Carcinoma (Primary solid tumor)
17 October 2014  |  analyses__2014_10_17
Maintainer Information
Citation Information
doi:10.7908/C1DB80NS
Maintained by David Heiman (Broad Institute)
Cite as Broad Institute TCGA Genome Data Analysis Center (2014): Mutation Analysis (MutSigCV v0.9). Broad Institute of MIT and Harvard. doi:10.7908/C1DB80NS
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: 130

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): 16

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: 16. 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 47190 15860 0 18 18 17 0 0 20 1.5 3.7e-15 99 0.13 4.6e-11
TP53 122850 35880 0 75 64 50 1 0 4 1.6 5e-15 180 0.14 4.6e-11
RB1 370240 97630 0 19 17 17 0 0 20 0.69 1.9e-14 82 0.44 1e-10
ARID1A 580710 171080 0 38 32 36 2 0 2 1.1 2.3e-14 130 0.29 1e-10
MLL2 1376830 455130 0 40 36 40 5 0 20 1.1 9.7e-14 130 0.44 3.5e-10
KDM6A 402090 110110 0 32 31 26 2 0 1 1.4 2.1e-12 130 0.29 6.3e-09
ELF3 115570 31720 0 15 11 14 0 0 20 1.1 2.3e-10 54 0.29 5.9e-07
FBXW7 252460 69290 0 16 13 12 0 0 20 0.51 7.4e-09 53 0.44 0.000017
FOXQ1 30030 9230 0 7 7 4 1 0 20 0.44 1.2e-08 34 0.29 0.000024
STAG2 406250 100880 0 14 14 13 3 0 20 0.98 4.6e-08 67 0.13 0.000085
PIK3CA 337870 86450 0 26 26 11 1 0 20 0.85 3.4e-07 53 0.24 0.00057
KLF5 112840 32760 0 11 10 10 2 0 20 1.2 0.000018 34 0.28 0.027
TSC1 360360 102310 0 11 11 11 0 0 20 0.8 0.000034 48 0.13 0.047
FOXA1 106080 31070 0 7 7 7 1 0 20 1.2 0.000044 34 0.28 0.058
FGFR3 161200 50310 0 21 16 11 2 0 18 1.5 0.000061 39 0.29 0.074
TXNIP 121550 34580 0 12 9 12 2 0 6 0.68 0.000081 35 0.13 0.093
ERCC2 241150 71890 0 16 16 13 2 0 20 0.81 0.00011 38 0.29 0.12
EP300 744120 209040 0 26 21 26 3 0 20 1.1 0.00015 64 0.29 0.16
HORMAD1 121680 29900 0 7 7 7 1 0 20 0.81 0.00026 26 0.28 0.25
ZFP36L1 99320 31850 0 6 6 6 0 0 20 0.88 0.0003 26 0.12 0.27
MLL3 1491750 423800 0 30 27 30 3 0 13 0.78 0.00031 73 0.44 0.27
NFE2L2 183170 48490 0 12 11 9 0 0 20 0.86 0.00051 29 0.44 0.42
TFG 123240 35880 0 4 4 4 1 0 20 0.56 0.0012 20 0.13 0.93
ZNF513 186550 59410 0 7 7 7 0 0 20 0.83 0.0013 28 0.12 0.96
HLA-A 106600 32240 0 5 5 4 0 0 20 1 0.0015 25 0.24 1
PHLDA3 31460 10660 0 4 4 3 1 0 20 0.26 0.0015 15 0.27 1
MIPOL1 140010 33930 0 7 7 6 1 0 20 0.86 0.0016 23 0.33 1
CEBPB 21190 6240 0 3 3 3 1 0 20 1.2 0.0016 13 0.11 1
MPZ 71500 21710 0 4 4 4 0 0 20 0.46 0.0017 20 0.33 1
CYP3A7 158730 43550 0 6 6 6 1 0 20 1 0.0019 24 0.43 1
CDKN1B 60450 16770 0 5 4 5 0 0 20 1 0.0021 20 0.12 1
ZFP36L2 65780 21190 0 6 5 6 0 0 20 1 0.0024 20 0.12 1
FAM43B 28340 8970 0 2 2 1 0 0 20 0.6 0.0031 13 0.22 1
WAC 197730 56940 0 9 7 9 1 0 15 0.77 0.0035 26 0.12 1
RHOB 57980 17290 0 7 7 6 1 0 20 1.2 0.0037 18 0.28 1
CDKN1A

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

TP53

Figure S2.  This figure depicts the distribution of mutations and mutation types across the TP53 significant gene.

RB1

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

ARID1A

Figure S4.  This figure depicts the distribution of mutations and mutation types across the ARID1A significant gene.

MLL2

Figure S5.  This figure depicts the distribution of mutations and mutation types across the MLL2 significant gene.

KDM6A

Figure S6.  This figure depicts the distribution of mutations and mutation types across the KDM6A significant gene.

ELF3

Figure S7.  This figure depicts the distribution of mutations and mutation types across the ELF3 significant gene.

FBXW7

Figure S8.  This figure depicts the distribution of mutations and mutation types across the FBXW7 significant gene.

FOXQ1

Figure S9.  This figure depicts the distribution of mutations and mutation types across the FOXQ1 significant gene.

STAG2

Figure S10.  This figure depicts the distribution of mutations and mutation types across the STAG2 significant gene.

PIK3CA

Figure S11.  This figure depicts the distribution of mutations and mutation types across the PIK3CA significant gene.

KLF5

Figure S12.  This figure depicts the distribution of mutations and mutation types across the KLF5 significant gene.

TSC1

Figure S13.  This figure depicts the distribution of mutations and mutation types across the TSC1 significant gene.

FOXA1

Figure S14.  This figure depicts the distribution of mutations and mutation types across the FOXA1 significant gene.

FGFR3

Figure S15.  This figure depicts the distribution of mutations and mutation types across the FGFR3 significant gene.

TXNIP

Figure S16.  This figure depicts the distribution of mutations and mutation types across the TXNIP 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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