Mutation Analysis (MutSigCV v0.9)
Adrenocortical Carcinoma (Primary solid tumor)
21 August 2015  |  analyses__2015_08_21
Maintainer Information
Citation Information
doi:10.7908/C16T0KR3
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/C16T0KR3
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: ACC-TP

  • Number of patients in set: 90

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:ACC-TP.final_analysis_set.maf

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

  • Significantly mutated genes (q ≤ 0.1): 73

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: ACC-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: 73. 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
ASPDH 25200 8640 3100 19 19 2 0 0 20 2.2 0 59 0.067 0
ZNF517 61830 18540 3500 34 33 2 0 0 20 0.96 0 100 0.068 0
LACTB 93060 24480 4900 27 27 3 0 0 20 0.93 2.2e-16 73 0.069 1.4e-12
MAL2 27180 8280 2250 23 22 2 1 0 20 1 1.9e-15 140 0.069 8.6e-12
ZFPM1 57420 17010 4250 112 47 6 0 0 20 0.97 2.7e-15 270 0.069 9.7e-12
GLTPD2 23310 8190 2450 19 19 1 2 0 20 0.66 4.2e-15 56 0.067 1.3e-11
KCNK17 64620 19530 4750 19 19 2 0 0 20 0.44 6e-15 57 0.068 1.6e-11
TOR3A 69750 19800 4800 25 25 1 0 0 20 1.1 8.2e-15 72 0.068 1.7e-11
ZAR1 24750 5670 3100 19 19 2 1 0 20 0.29 8.2e-15 65 0.093 1.7e-11
IRX3 48420 14400 2000 21 21 1 0 0 20 1.4 9.3e-15 63 0.07 1.7e-11
CCDC102A 73890 21510 5650 26 26 1 0 0 20 0.34 1.1e-14 66 0.085 1.7e-11
KBTBD13 16380 5220 0 15 15 5 6 0 20 1.4 1.3e-14 52 0.069 2e-11
GARS 148770 40410 16100 35 34 3 6 0 18 1.1 1.4e-14 85 0.069 2e-11
OPRD1 51840 16650 1650 26 26 1 1 0 20 0.41 1.9e-14 80 0.073 2.5e-11
CLDN23 21150 7650 300 13 13 1 0 0 20 0.4 3.9e-14 46 0.1 4.7e-11
RINL 79470 25020 7650 19 19 1 0 0 20 0 4.6e-14 55 0.067 5.3e-11
TP53 85050 24840 10300 20 18 20 0 0 4 0.94 3e-12 73 0.068 3.2e-09
ATXN1 156060 51120 2150 15 14 9 1 0 20 1.2 5.3e-12 62 0.068 5.4e-09
FPGS 92070 29430 10650 14 14 2 0 0 20 0 9.7e-12 44 0.066 9.3e-09
ERCC2 166950 49770 25050 19 19 1 0 0 20 0 1.4e-10 48 0.067 1.3e-07
MEN1 121410 38250 9350 8 8 7 0 0 20 0.68 6.6e-10 45 0.068 5.7e-07
BHLHE22 23310 7920 500 11 10 3 0 0 20 0.54 6.9e-10 35 0.066 5.7e-07
PANK2 87660 26190 11250 15 15 2 0 0 20 0.47 8.6e-10 42 0.067 6.8e-07
NMU 29610 7560 7100 10 10 2 0 0 20 0.57 1.7e-09 34 0.064 1.3e-06
KRTAP5-5 47880 14040 1200 8 6 5 2 0 20 0.85 1.8e-09 36 0.064 1.3e-06
C4orf32 17460 4860 1100 9 9 1 0 0 20 0.84 2.3e-09 30 0.067 1.6e-06
C14orf180 8550 2520 1550 4 4 1 2 0 20 1.2 8e-09 27 0.062 5.4e-06
CTNNB1 165510 49500 14100 14 14 9 0 0 20 0.84 1.1e-08 47 0.068 7e-06
B3GNT6 38250 12690 750 5 5 2 0 0 20 0.36 1.2e-08 31 0.064 7.3e-06
SYT8 60480 20610 6150 14 14 3 0 0 20 1.3 1.9e-08 37 0.068 0.000012
C19orf10 25110 6840 4400 10 10 1 0 0 10 0.26 2.2e-08 31 0.064 0.000013
UQCRFS1 42480 12600 1100 12 12 1 10 0 14 2.4 2.4e-08 36 0.067 0.000014
CRIPAK 88560 29430 1150 22 17 9 41 0 20 4.2 2.7e-08 49 0.074 0.000015
THEM4 46080 11520 5050 14 14 1 0 0 20 3.2 6.9e-08 36 0.068 0.000037
AMDHD1 80910 23040 7750 18 18 1 15 0 20 3.3 7.4e-08 44 0.067 0.000039
ASPDH

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

ZNF517

Figure S2.  This figure depicts the distribution of mutations and mutation types across the ZNF517 significant gene.

LACTB

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

MAL2

Figure S4.  This figure depicts the distribution of mutations and mutation types across the MAL2 significant gene.

ZFPM1

Figure S5.  This figure depicts the distribution of mutations and mutation types across the ZFPM1 significant gene.

GLTPD2

Figure S6.  This figure depicts the distribution of mutations and mutation types across the GLTPD2 significant gene.

KCNK17

Figure S7.  This figure depicts the distribution of mutations and mutation types across the KCNK17 significant gene.

TOR3A

Figure S8.  This figure depicts the distribution of mutations and mutation types across the TOR3A significant gene.

ZAR1

Figure S9.  This figure depicts the distribution of mutations and mutation types across the ZAR1 significant gene.

IRX3

Figure S10.  This figure depicts the distribution of mutations and mutation types across the IRX3 significant gene.

CCDC102A

Figure S11.  This figure depicts the distribution of mutations and mutation types across the CCDC102A significant gene.

KBTBD13

Figure S12.  This figure depicts the distribution of mutations and mutation types across the KBTBD13 significant gene.

GARS

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

OPRD1

Figure S14.  This figure depicts the distribution of mutations and mutation types across the OPRD1 significant gene.

CLDN23

Figure S15.  This figure depicts the distribution of mutations and mutation types across the CLDN23 significant gene.

RINL

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

TP53

Figure S17.  This figure depicts the distribution of mutations and mutation types across the TP53 significant gene.

ATXN1

Figure S18.  This figure depicts the distribution of mutations and mutation types across the ATXN1 significant gene.

FPGS

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

ERCC2

Figure S20.  This figure depicts the distribution of mutations and mutation types across the ERCC2 significant gene.

MEN1

Figure S21.  This figure depicts the distribution of mutations and mutation types across the MEN1 significant gene.

BHLHE22

Figure S22.  This figure depicts the distribution of mutations and mutation types across the BHLHE22 significant gene.

PANK2

Figure S23.  This figure depicts the distribution of mutations and mutation types across the PANK2 significant gene.

KRTAP5-5

Figure S24.  This figure depicts the distribution of mutations and mutation types across the KRTAP5-5 significant gene.

C4orf32

Figure S25.  This figure depicts the distribution of mutations and mutation types across the C4orf32 significant gene.

CTNNB1

Figure S26.  This figure depicts the distribution of mutations and mutation types across the CTNNB1 significant gene.

B3GNT6

Figure S27.  This figure depicts the distribution of mutations and mutation types across the B3GNT6 significant gene.

SYT8

Figure S28.  This figure depicts the distribution of mutations and mutation types across the SYT8 significant gene.

C19orf10

Figure S29.  This figure depicts the distribution of mutations and mutation types across the C19orf10 significant gene.

CRIPAK

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

THEM4

Figure S31.  This figure depicts the distribution of mutations and mutation types across the THEM4 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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