Mutation Analysis (MutSigCV v0.9)
Thyroid Adenocarcinoma (Primary solid tumor)
21 April 2013  |  analyses__2013_04_21
Maintainer Information
Citation Information
doi:10.7908/C1B27S8M
Maintained by Dan DiCara (Broad Institute)
Cite as Broad Institute TCGA Genome Data Analysis Center (2013): Thyroid Adenocarcinoma (Primary solid tumor cohort) - 21 April 2013: Mutation Analysis (MutSigCV v0.9). Broad Institute of MIT and Harvard. doi:10.7908/C1B27S8M
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: THCA-TP

  • Number of patients in set: 323

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
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).

Figure 1. 

Distribution of Mutation Counts, Coverage, and Mutation Rates Across Samples

Figure 2.  Patients counts and rates file used to generate this plot: THCA-TP.patients.counts_and_rates.txt

CoMut Plot

Figure 3.  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: 19. 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
BRAF 558876 159661 833099 183 183 2 1 0 19 1.7 5.8e-15 670 0.27 6.8e-11
NRAS 149325 39406 199635 26 26 2 0 0 20 0 7.4e-15 110 0.23 6.8e-11
HRAS 155035 44759 133192 12 12 2 0 0 20 2.3 2.2e-13 49 0.22 1.3e-09
EMG1 218374 66439 238157 6 6 2 0 0 20 0.98 4.8e-12 42 0.23 2.2e-08
TG 2302519 671736 2604351 16 16 16 3 0 7 2.5 5.9e-10 74 0.23 2.1e-06
PTTG1IP 114342 29393 222211 4 4 1 0 0 20 1.8 2.2e-08 29 0.21 0.000067
PRB2 293748 106426 164766 6 6 4 1 0 12 1.4 2.7e-08 32 0.21 0.000069
GPR44 102245 34152 57612 4 4 2 0 0 20 2.9 3.5e-08 28 0.22 0.000079
RPTN 619600 141797 123888 8 8 6 0 0 5 1.8 1.1e-07 46 0.22 0.00023
PPM1D 390309 111659 261876 5 5 5 0 0 20 0.98 1.7e-07 31 0.21 0.00032
TMCO2 139101 39083 102577 3 3 1 0 0 20 0 3.3e-07 22 0.2 0.00055
EIF1AX 114975 26809 280235 6 5 5 0 0 20 1.1 6.6e-07 22 0.2 0.001
MUC7 268077 99695 94559 5 5 5 1 0 20 1.1 9.1e-07 23 0.2 0.0013
IL32 137903 35616 277748 3 3 1 0 0 20 2 7.1e-06 21 0.2 0.0086
ARMCX3 285644 81719 56258 3 3 2 0 0 20 0.4 7.1e-06 21 0.21 0.0086
R3HDM2 476113 145905 519138 4 4 1 0 0 20 1.3 0.000013 26 0.21 0.015
LYPD3 248796 83756 172371 3 3 1 0 0 15 0.5 2e-05 21 0.21 0.021
DNMT3A 672210 187202 835204 5 5 5 0 0 18 0.81 0.000047 29 0.22 0.048
CRIPAK 320364 106465 52349 3 3 3 0 0 20 0.5 0.000087 16 0.2 0.084
PPTC7 177762 51034 248375 3 3 1 0 0 5 3.5 0.00014 20 0.2 0.13
ACD 508642 173821 411723 3 3 2 0 0 20 0.32 0.00017 18 0.2 0.15
COL5A3 1156489 395795 2067239 6 6 6 0 0 20 1 0.00018 26 0.22 0.15
MSI1 179575 53506 428021 3 3 3 0 1 20 1.3 0.00019 15 0.19 0.15
KCNK12 91711 30065 11238 2 2 2 0 0 20 1.1 0.00021 14 0.23 0.16
GADD45GIP1 119807 34337 71805 2 2 1 0 0 20 1.1 0.00025 15 0.27 0.18
SCUBE2 749459 199937 1113214 3 3 1 0 0 20 0.72 0.00029 20 0.2 0.2
TYSND1 151833 48205 88206 2 2 1 0 0 20 1.4 0.00064 14 0.19 0.42
TMEM90B 196806 56525 211141 3 3 1 0 0 18 4.2 0.00064 19 0.2 0.42
CHD2 1437259 367014 1661675 4 4 3 0 0 17 0.61 0.00068 25 0.22 0.43
C11orf87 134670 47942 11815 3 3 3 0 0 20 1.4 0.00071 12 0.18 0.43
ALPP 328762 105384 288105 3 3 2 0 0 20 1.7 0.00075 17 0.2 0.44
ISYNA1 310216 97132 235557 2 2 2 0 0 20 0 0.0012 14 0.27 0.62
PAWR 136952 35530 199734 2 2 2 0 0 20 1.2 0.0012 11 0.17 0.62
TCEAL3 152904 38984 40011 2 2 2 0 0 20 0 0.0012 9.1 0.16 0.62
SLC25A45 216298 69122 239423 3 3 3 0 0 20 0.61 0.0012 12 0.18 0.62
BRAF

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

NRAS

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

HRAS

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

EMG1

Figure S4.  This figure depicts the distribution of mutations and mutation types across the EMG1 significant gene.

TG

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

PTTG1IP

Figure S6.  This figure depicts the distribution of mutations and mutation types across the PTTG1IP significant gene.

GPR44

Figure S7.  This figure depicts the distribution of mutations and mutation types across the GPR44 significant gene.

RPTN

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

PPM1D

Figure S9.  This figure depicts the distribution of mutations and mutation types across the PPM1D significant gene.

TMCO2

Figure S10.  This figure depicts the distribution of mutations and mutation types across the TMCO2 significant gene.

EIF1AX

Figure S11.  This figure depicts the distribution of mutations and mutation types across the EIF1AX significant gene.

MUC7

Figure S12.  This figure depicts the distribution of mutations and mutation types across the MUC7 significant gene.

IL32

Figure S13.  This figure depicts the distribution of mutations and mutation types across the IL32 significant gene.

ARMCX3

Figure S14.  This figure depicts the distribution of mutations and mutation types across the ARMCX3 significant gene.

R3HDM2

Figure S15.  This figure depicts the distribution of mutations and mutation types across the R3HDM2 significant gene.

LYPD3

Figure S16.  This figure depicts the distribution of mutations and mutation types across the LYPD3 significant gene.

DNMT3A

Figure S17.  This figure depicts the distribution of mutations and mutation types across the DNMT3A significant gene.

CRIPAK

Figure S18.  This figure depicts the distribution of mutations and mutation types across the CRIPAK 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

This is an experimental feature. The full results of the analysis summarized in this report can be downloaded from the TCGA Data Coordination Center.

References
[1] TCGA, Integrated genomic analyses of ovarian carcinoma, Nature 474:609 - 615 (2011)
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