Mutation Analysis (MutSigCV v0.9)
Cervical Squamous Cell Carcinoma (Primary solid tumor)
21 April 2013  |  analyses__2013_04_21
Maintainer Information
Citation Information
doi:10.7908/C15D8PSC
Maintained by Dan DiCara (Broad Institute)
Cite as Broad Institute TCGA Genome Data Analysis Center (2013): Cervical Squamous Cell Carcinoma (Primary solid tumor cohort) - 21 April 2013: Mutation Analysis (MutSigCV v0.9). Broad Institute of MIT and Harvard. doi:10.7908/C15D8PSC
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).

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

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: 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 6 4 5 0 0 12 1.3 0.000055 19 0.036 0.93
PTEN 37986 9126 6438 3 3 3 0 0 20 0 0.00015 17 0.035 0.93
PLAC4 5928 2145 333 3 2 2 0 0 20 0 0.00019 13 0.032 0.93
TMCC1 59670 17160 3108 4 4 3 0 0 20 0 0.00023 19 0.038 0.93
CDC27 75972 20553 12987 7 5 4 0 0 20 0.36 0.00025 20 0.036 0.93
PIK3CA 101361 25935 14652 11 9 4 0 0 20 0.3 0.00037 20 0.038 1
NFE2L2 54951 14547 2997 7 6 6 0 0 20 1.2 0.0004 19 0.037 1
NFYB 20202 4992 5291 2 2 1 0 0 20 0.43 0.0016 12 0.033 1
C11orf52 11739 3159 3071 2 2 2 0 0 20 0 0.0019 9.3 0.03 1
C15orf56 2769 1014 296 1 1 1 0 0 20 0.32 0.0022 6.8 0.027 1
UGT3A2 48516 13533 5328 3 3 2 0 0 20 0.29 0.0023 14 0.037 1
IFNGR2 29211 8229 4440 2 2 2 0 0 20 0.87 0.004 11 0.034 1
MAPK1 30615 7956 5143 3 3 1 0 0 20 0 0.0046 9.2 0.031 1
TMCO2 16770 4719 1628 2 2 2 0 0 20 0.36 0.0047 8.9 0.037 1
CSAG1 7293 2262 2368 3 2 3 0 0 13 0 0.005 6.6 0.027 1
IL13RA1 38571 9438 7400 2 2 1 0 0 20 0.56 0.0053 11 0.033 1
DHRS12 23517 6318 4847 2 2 2 0 0 20 0.86 0.0059 11 0.035 1
CRIPAK 38376 12753 851 5 2 5 0 0 20 0.98 0.0059 11 0.034 1
SEH1L 39312 10959 8103 2 2 1 0 0 20 0.35 0.0061 11 0.033 1
B2M 11193 3120 2368 2 2 2 0 0 20 1.2 0.0062 8.5 0.031 1
PRRG1 19890 5538 2220 2 2 2 0 0 8 0.32 0.0063 8.9 0.031 1
SPANXN5 7098 1599 1628 1 1 1 0 0 20 0.63 0.0069 6.4 0.024 1
XAGE5 10374 2808 2960 3 2 3 0 0 20 0.63 0.0071 6.4 0.025 1
C20orf134 12987 4290 1184 2 2 2 0 0 20 0.31 0.0078 8.5 0.03 1
MTL5 39078 10569 6031 2 2 2 0 0 20 0.59 0.0079 11 0.033 1
TMEM47 7566 2223 1036 1 1 1 0 0 20 1.7 0.0093 6.3 0.029 1
SPATA7 54912 14391 7770 2 2 2 0 0 20 1.1 0.011 11 0.034 1
MLL3 447525 127140 45880 10 8 10 2 0 13 1.1 0.012 30 0.037 1
TREML4 18252 5538 3663 5 2 4 3 0 20 1.3 0.012 8.5 0.038 1
TMEM51 22503 6864 1517 3 3 3 0 0 20 0 0.015 8.6 0.036 1
OR1J1 28626 8853 962 2 2 2 0 0 20 0 0.018 8.4 0.032 1
VEZF1 46761 13611 3774 2 2 1 0 0 20 0.83 0.018 11 0.033 1
AQP2 20826 7449 2331 3 3 3 0 0 20 0.38 0.019 8.4 0.03 1
CTNNBIP1 5187 1443 1665 1 1 1 0 0 20 1.2 0.019 6.3 0.027 1
DNAJB1 29562 8580 1961 5 3 5 0 0 20 1.7 0.02 9.8 0.034 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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