Mutation Analysis (MutSigCV v0.9)
Cervical Squamous Cell Carcinoma and Endocervical Adenocarcinoma (Primary solid tumor)
17 October 2014  |  analyses__2014_10_17
Maintainer Information
Citation Information
doi:10.7908/C12N514B
Maintained by David Heiman (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/C12N514B
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: 194

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:CESC-TP.final_analysis_set.maf

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

  • Significantly mutated genes (q ≤ 0.1): 0

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
A1BG 155394 50634 213982 0 0 0 0 1 20 1.8 1 0 NaN 1
A1CF 293134 85360 463466 0 0 0 0 2 0 0.75 1 0 NaN 1
A2BP1 212818 58782 754854 0 0 0 0 0 10 1.9 1 0 NaN 1
A2M 605474 175570 941870 0 0 0 0 3 20 0.76 1 0 NaN 1
A2ML1 678030 194194 1467998 0 0 0 0 3 3 0.72 1 0 NaN 1
A4GALT 131920 42874 15520 0 0 0 0 1 20 1 1 0 NaN 1
A4GNT 156170 43262 97582 0 0 0 0 1 20 0.51 1 0 NaN 1
AAAS 301670 96806 593446 0 0 0 0 3 7 0.81 1 0 NaN 1
AACS 294880 82062 659018 0 0 0 0 4 20 0.71 1 0 NaN 1
AADAC 183524 51992 173824 0 0 0 0 1 20 1.6 1 0 NaN 1
AADACL2 185464 51216 173436 0 0 0 0 2 20 1.2 1 0 NaN 1
AADACL3 161796 45396 200596 0 0 0 0 1 20 1.5 1 0 NaN 1
AADACL4 184106 55096 187404 0 0 0 0 1 20 1.5 1 0 NaN 1
AADAT 196716 52186 450080 0 0 0 0 2 0 0.82 1 0 NaN 1
AAGAB 151708 40158 436306 0 0 0 0 1 19 1.2 1 0 NaN 1
AAK1 334262 99522 686954 0 0 0 0 6 20 1 1 0 NaN 1
AAMP 249096 77018 481314 0 0 0 0 2 20 1.1 1 0 NaN 1
AANAT 62662 19982 74690 0 0 0 0 0 20 1.1 1 0 NaN 1
AARS 441156 127652 730022 0 0 0 0 3 20 1 1 0 NaN 1
AARS2 421562 138516 779492 0 0 0 0 0 20 0.89 1 0 NaN 1
AARSD1 262870 73332 661928 0 0 0 0 0 14 0.88 1 0 NaN 1
AASDH 503818 141232 411086 0 0 0 0 3 4 0.7 1 0 NaN 1
AASDHPPT 143366 37636 188374 0 0 0 0 0 11 1.9 1 0 NaN 1
AASS 435918 120862 881536 0 0 0 0 2 9 1.2 1 0 NaN 1
AATF 253364 66154 453960 0 0 0 0 1 20 0.67 1 0 NaN 1
AATK 178480 58394 96418 0 0 0 0 7 20 0.93 1 0 NaN 1
ABAT 232412 63438 599072 0 0 0 0 0 20 0.92 1 0 NaN 1
ABCA1 1037124 293134 2016436 0 0 0 0 6 0 0.53 1 0 NaN 1
ABCA10 730798 190896 1364596 0 0 0 0 6 9 0.88 1 0 NaN 1
ABCA12 1218320 336202 1937090 0 0 0 0 21 5 1.8 1 0 NaN 1
ABCA13 2144476 575598 1722720 0 0 0 0 19 19 1.1 1 0 NaN 1
ABCA2 758152 229308 625844 0 0 0 0 9 20 1.7 1 0 NaN 1
ABCA3 703832 214952 1123066 0 0 0 0 6 20 1.4 1 0 NaN 1
ABCA4 1025484 295656 1855804 0 0 0 0 10 13 1 1 0 NaN 1
ABCA5 762614 199626 1234034 0 0 0 0 6 2 0.98 1 0 NaN 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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