Mutation Analysis (MutSigCV v0.9)
Cervical Squamous Cell Carcinoma and Endocervical Adenocarcinoma (Primary solid tumor)
15 January 2014  |  analyses__2014_01_15
Maintainer Information
Citation Information
doi:10.7908/C1NP22VN
Maintained by Dan DiCara (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/C1NP22VN
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: CESC-TP

  • Number of patients in set: 39

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). 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: CESC-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: 0. 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
PRB2 34398 12519 1961 5 4 4 0 0 12 1 0.000036 20 0.021 0.66
PTEN 37986 9126 6438 3 3 3 0 0 20 0 0.00015 17 0.02 1
PLAC4 5928 2145 333 2 2 1 0 0 20 0 0.00019 13 0.018 1
TMCC1 59670 17160 3108 4 4 3 0 0 20 0 0.00023 19 0.021 1
PIK3CA 101361 25935 14652 11 9 4 0 0 20 0.31 0.00038 20 0.021 1
NFE2L2 54951 14547 2997 7 6 6 0 0 20 1.2 0.0004 19 0.021 1
C11orf52 11739 3159 3071 2 2 2 0 0 20 0 0.0019 9.3 0.018 1
C15orf56 2769 1014 296 1 1 1 0 0 20 0.32 0.002 6.8 0.014 1
UGT3A2 48516 13533 5328 3 3 2 0 0 20 0.3 0.0022 14 0.02 1
IFNGR2 29211 8229 4440 2 2 2 0 0 20 0.89 0.004 11 0.02 1
MAPK1 30615 7956 5143 3 3 1 0 0 20 0 0.0046 9.2 0.018 1
CSAG1 7293 2262 2368 3 2 3 0 0 13 0 0.005 6.6 0.015 1
IL13RA1 38571 9438 7400 2 2 1 0 0 20 0.57 0.0051 11 0.019 1
DHRS12 23517 6318 4847 2 2 2 0 0 20 0.87 0.0058 11 0.019 1
SEH1L 39312 10959 8103 2 2 1 0 0 20 0.36 0.0059 11 0.019 1
B2M 11193 3120 2368 2 2 2 0 0 20 1.2 0.0062 8.5 0.017 1
PRRG1 19890 5538 2220 2 2 2 0 0 8 0.33 0.0063 8.9 0.017 1
SPANXN5 7098 1599 1628 1 1 1 0 0 20 0.65 0.0069 6.4 0.014 1
XAGE5 10374 2808 2960 3 2 3 0 0 20 0.65 0.0069 6.4 0.014 1
C20orf134 12987 4290 1184 2 2 2 0 0 20 0.32 0.0078 8.5 0.018 1
MTL5 39078 10569 6031 2 2 2 0 0 20 0.6 0.0078 11 0.019 1
TMEM47 7566 2223 1036 1 1 1 0 0 20 1.8 0.0093 6.3 0.014 1
SPATA7 54912 14391 7770 2 2 2 0 0 20 1.1 0.011 11 0.019 1
TREML4 18252 5538 3663 5 2 4 3 0 20 1.4 0.011 8.5 0.017 1
MLL3 447525 127140 45880 10 8 10 2 0 13 1.1 0.012 30 0.023 1
TMEM51 22503 6864 1517 3 3 3 0 0 20 0 0.015 8.6 0.017 1
CTNNBIP1 5187 1443 1665 1 1 1 0 0 20 0.42 0.017 6.4 0.015 1
OR1J1 28626 8853 962 2 2 2 0 0 20 0 0.018 8.4 0.017 1
DNAJB1 29562 8580 1961 5 3 5 0 0 20 1.7 0.02 9.8 0.019 1
FAM24A 9984 2652 1554 1 1 1 0 0 20 2.1 0.024 6.2 0.015 1
NCKAP1 105846 27573 22459 4 4 4 0 0 8 0 0.025 14 0.02 1
IQCG 59553 15600 11359 3 3 3 0 0 20 0.72 0.027 10 0.019 1
RNF149 32526 9672 4884 2 2 2 0 0 20 0.32 0.027 8.3 0.017 1
DNLZ 7956 2535 1295 1 1 1 0 0 20 1 0.029 6.1 0.015 1
ATP5J 10179 2691 1924 1 1 1 0 0 20 0 0.03 6.2 0.014 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

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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