Mutation Analysis (MutSigCV v0.9)
Colon Adenocarcinoma (Primary solid tumor)
23 May 2013  |  analyses__2013_05_23
Maintainer Information
Citation Information
doi:10.7908/C10V89T6
Maintained by Dan DiCara (Broad Institute)
Cite as Broad Institute TCGA Genome Data Analysis Center (2013): Mutation Analysis (MutSigCV v0.9). Broad Institute of MIT and Harvard. doi:10.7908/C10V89T6
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: COAD-TP

  • Number of patients in set: 155

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: COAD-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: 12. 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 146475 42780 206 77 75 50 1 0 4 1 1.9e-15 240 0.13 2.6e-11
APC 1034160 289850 291 163 107 108 4 0 4 1 2.9e-15 490 0.11 2.6e-11
KRAS 93775 22940 106 59 59 9 0 0 1 0 7.1e-15 130 0.11 4.3e-11
FBXW7 301010 82615 239 33 29 21 2 0 20 1.5 1.9e-13 86 0.11 8.6e-10
NRAS 71455 18910 82 15 15 7 0 0 20 0.59 5.4e-11 47 0.11 2e-07
FAM123B 383780 113770 98 19 19 17 1 0 20 2 1.1e-08 79 0.11 0.000033
SMAD4 205220 57195 222 22 18 18 0 0 20 1.2 1.5e-08 56 0.11 4e-05
SOX9 146010 42935 52 9 9 9 0 0 20 1.5 5.2e-07 48 0.11 0.0012
PIK3CA 402845 103075 396 33 26 18 1 0 20 1.2 1.2e-06 57 0.13 0.0025
BRAF 267685 76415 339 21 20 3 0 0 19 1.2 0.000013 44 0.11 0.023
ACVR2A 192820 50840 222 10 9 8 1 0 10 1.1 0.000022 38 0.11 0.037
TXNDC3 224905 54715 294 13 10 13 2 0 20 1.1 0.000061 38 0.11 0.093
SMAD2 173135 48360 199 11 10 8 1 0 20 1.4 0.0001 36 0.11 0.14
CASP8 225680 52855 213 11 10 10 0 0 20 0.88 0.00013 34 0.11 0.17
TCF7L2 230175 64945 273 13 11 13 3 0 20 1.4 0.00033 39 0.12 0.4
MGC26647 92070 25420 24 7 7 7 0 0 13 1.4 0.00035 26 0.11 0.4
SAT1 64790 15500 117 4 4 2 0 0 20 0.91 0.00037 21 0.1 0.4
WBSCR17 214055 61690 211 17 17 16 2 0 18 1.5 0.00043 41 0.11 0.41
CCDC160 60295 14570 5 7 5 7 0 0 20 1.2 0.00045 19 0.099 0.41
ESR1 188635 53475 146 12 11 12 0 0 20 0.67 0.00046 30 0.11 0.41
MIER3 206460 53165 236 10 10 10 0 0 20 1.1 0.00047 32 0.11 0.41
ZNF593 25885 7750 43 3 3 3 0 0 20 0.75 0.001 15 0.094 0.85
TBC1D10C 86800 28830 92 4 4 2 0 0 20 1.1 0.0013 23 0.11 1
TMEM105 41230 14570 35 3 3 3 0 0 19 0.4 0.0017 15 0.11 1
CRTC1 201190 63550 274 5 5 3 1 0 20 0.45 0.0017 25 0.11 1
ELF3 137795 37820 158 5 5 5 0 0 20 0.82 0.0019 24 0.1 1
C6orf211 164610 41850 100 5 5 5 0 0 19 0.41 0.002 20 0.1 1
CELA1 84320 25110 138 6 5 6 0 0 20 1.1 0.0021 20 0.11 1
RNF43 258075 81685 175 11 10 10 1 0 8 0.64 0.0021 27 0.12 1
INSL6 77345 21235 40 5 5 5 1 0 20 0.91 0.0022 18 0.1 1
GGA2 217465 62775 320 8 8 8 1 0 20 0.91 0.0026 28 0.11 1
OR2M4 110670 33635 27 8 8 8 0 0 19 1.7 0.0026 24 0.1 1
HSPA1L 247380 74555 35 8 8 8 1 0 20 0.32 0.004 23 0.11 1
B2M 44485 12400 64 3 3 3 0 0 20 1.1 0.0046 14 0.095 1
SLC16A7 172205 50375 82 10 8 9 2 0 20 1.8 0.0047 28 0.12 1
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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