Mutation Analysis (MutSigCV v0.6)
Rectum Adenocarcinoma (Primary solid tumor)
22 February 2013  |  analyses__2013_02_22
Maintainer Information
Citation Information
doi:10.7908/C1XG9PDB
Maintained by Dan DiCara (Broad Institute)
Cite as Broad Institute TCGA Genome Data Analysis Center (2013): Mutation Analysis (MutSigCV v0.6). Broad Institute of MIT and Harvard. doi:10.7908/C1XG9PDB
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 v0.6 was used to generate the results found in this report.

  • Working with individual set: READ-TP

  • Number of patients in set: 73

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: READ-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: 4. 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
KRAS 44165 10804 0 39 39 8 0 0 1 0 1.3e-15 96 0.07 1.4e-11
APC 487056 136510 0 94 60 69 0 0 4 0 1.8e-15 300 0.071 1.4e-11
TP53 68985 20148 0 47 47 30 1 0 4 0.86 2.3e-15 150 0.071 1.4e-11
SMAD4 96652 26937 0 9 9 6 0 0 20 0.7 0.000017 26 0.091 0.078
NRAS 33653 8906 0 6 6 4 0 0 20 0.82 5e-05 18 0.062 0.18
FBXW7 141766 38909 0 15 11 10 0 1 20 0.97 0.000073 27 0.066 0.22
NUP107 166367 43654 0 5 4 4 0 0 20 0 0.00019 20 0.064 0.46
NUCB1 75044 21243 0 3 3 2 0 0 20 0 0.0002 16 0.061 0.46
RBM10 112712 31901 0 5 5 4 0 0 16 0.52 0.00024 24 0.065 0.49
KCTD20 73803 19710 0 3 3 2 0 0 20 0 0.0003 13 0.061 0.55
MARCKSL1 33799 10147 0 2 2 1 0 0 20 0.25 0.00045 13 0.06 0.68
ELF3 64897 17812 0 3 3 3 0 0 20 0.59 0.00047 17 0.063 0.68
MPHOSPH9 180310 48545 0 3 3 2 0 0 20 0 0.00049 17 0.066 0.68
SYTL3 85483 24455 0 4 4 3 0 0 20 0.39 0.00055 18 0.063 0.69
WDR69 73949 19856 0 8 5 6 0 0 20 0.43 0.0006 17 0.065 0.69
FAM9B 33069 7154 0 3 3 2 0 0 6 0.41 0.00063 15 0.062 0.69
PPPDE1 34310 9417 0 3 2 2 0 0 20 0.078 0.00065 7.9 0.045 0.69
MAPK10 84023 21170 0 5 5 4 0 0 16 1 0.00074 19 0.065 0.73
ELL 79059 23871 0 3 3 2 0 0 20 0.27 0.0008 16 0.065 0.73
PPP6C 53874 14746 0 3 3 2 0 0 20 0 0.00088 10 0.058 0.73
KIAA1804 132130 39055 0 13 10 9 0 0 20 0.76 0.0009 22 0.07 0.73
GLT8D2 62123 16644 0 4 4 2 2 0 20 0.37 0.0009 15 0.063 0.73
MAP3K12 143080 46136 0 3 3 2 0 0 20 0 0.00097 15 0.065 0.73
SMAD2 81541 22776 0 6 6 5 0 0 20 0.69 0.001 17 0.062 0.73
LDB1 67744 17812 0 3 3 2 0 0 20 0.14 0.001 13 0.059 0.73
FKBP11 53728 15841 0 3 3 2 0 0 20 0.19 0.0011 13 0.063 0.73
SIP1 49859 13213 0 3 3 2 0 0 20 0.73 0.0011 14 0.062 0.73
FAM123B 180748 53582 0 8 6 8 2 0 20 1.3 0.0012 26 0.066 0.77
RPE65 94754 25404 0 5 4 4 0 0 20 0.64 0.0013 18 0.062 0.85
CDKN1B 33945 9417 0 2 2 2 0 0 20 0.21 0.0015 12 0.059 0.89
TCF7L2 108405 30587 0 7 7 7 2 0 20 1.7 0.0015 23 0.07 0.89
PFDN1 17593 4307 0 2 2 1 0 0 20 0.62 0.0019 10 0.055 1
ARHGEF6 138116 36792 0 5 3 3 0 0 20 0 0.002 12 0.059 1
CXCL11 17082 4453 0 2 2 1 0 0 20 0 0.0023 7.4 0.047 1
ARG2 64970 20075 0 2 2 1 0 0 20 0 0.0024 12 0.058 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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