Mutation Analysis (MutSigCV v0.6)
Cervical Squamous Cell Carcinoma (Primary solid tumor)
22 February 2013  |  analyses__2013_02_22
Maintainer Information
Citation Information
doi:10.7908/C13N21KB
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/C13N21KB
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: 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: 5. 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
TMCC1 59670 17160 3108 4 4 3 0 0 20 0 2.9e-06 21 0.035 0.031
PTEN 37986 9126 6438 3 3 3 0 0 20 0 3.4e-06 18 0.034 0.031
PLAC4 5928 2145 333 3 2 2 0 0 20 0 0.000014 14 0.031 0.066
PIK3CA 101361 25935 14652 11 9 4 0 0 20 0.3 0.000015 21 0.036 0.066
PRB2 34398 12519 1961 6 4 5 0 0 12 1.3 0.000023 20 0.035 0.083
CDC27 75972 20553 12987 7 5 4 0 0 20 0.36 0.000055 19 0.035 0.17
ARID1A 174213 51324 13912 9 6 8 0 0 2 0 0.00011 27 0.036 0.26
NFE2L2 54951 14547 2997 7 6 6 0 0 20 1.2 0.00011 19 0.035 0.26
TMEM51 22503 6864 1517 3 3 3 0 0 20 0 0.00024 10 0.03 0.4
MAPK1 30615 7956 5143 3 3 1 0 0 20 0 0.00024 11 0.031 0.4
NFYB 20202 4992 5291 2 2 1 0 0 20 0.43 0.00024 12 0.032 0.4
UGT3A2 48516 13533 5328 3 3 2 0 0 20 0.29 0.0003 14 0.033 0.45
CSAG1 7293 2262 2368 3 2 3 0 0 13 0 0.00037 7.7 0.026 0.49
C11orf52 11739 3159 3071 2 2 2 0 0 20 0 0.00039 10 0.029 0.49
NCKAP1 105846 27573 22459 4 4 4 0 0 8 0 0.00041 16 0.034 0.49
C15orf56 2769 1014 296 1 1 1 0 0 20 0.32 0.00065 7.3 0.025 0.74
TMCO2 16770 4719 1628 2 2 2 0 0 20 0.36 0.00074 9.8 0.03 0.79
IFNGR2 29211 8229 4440 2 2 2 0 0 20 0.87 0.00099 12 0.033 1
MLL3 447525 127140 45880 10 8 10 2 0 13 1.1 0.0011 31 0.037 1
TDGF1 17784 5070 4588 2 2 2 0 0 20 0 0.0016 7.1 0.026 1
DHRS12 23517 6318 4847 2 2 2 0 0 20 0.86 0.0017 11 0.032 1
C20orf134 12987 4290 1184 2 2 2 0 0 20 0.31 0.0017 8.8 0.028 1
SEH1L 39312 10959 8103 2 2 1 0 0 20 0.35 0.0018 11 0.031 1
PRRG1 19890 5538 2220 2 2 2 0 0 8 0.32 0.0018 9.4 0.029 1
IL13RA1 38571 9438 7400 2 2 1 0 0 20 0.56 0.0019 11 0.032 1
AQP2 20826 7449 2331 3 3 3 0 0 20 0.38 0.002 9.4 0.029 1
MTL5 39078 10569 6031 2 2 2 0 0 20 0.59 0.0024 11 0.033 1
SPANXN5 7098 1599 1628 1 1 1 0 0 20 0.63 0.0025 6.8 0.025 1
OR1J1 28626 8853 962 2 2 2 0 0 20 0 0.0027 9.4 0.029 1
P2RY13 30771 8697 444 2 2 2 0 0 20 0 0.0029 7 0.026 1
ZNF645 38844 10920 888 2 2 1 0 0 20 0 0.0033 6.8 0.025 1
B3GNT8 36816 12792 1591 2 2 2 0 0 20 0 0.0039 9.2 0.03 1
B2M 11193 3120 2368 2 2 2 0 0 20 1.2 0.0041 8.3 0.028 1
PDK1 36153 9711 10471 2 2 2 0 0 20 0 0.0043 6.6 0.025 1
TMEM47 7566 2223 1036 1 1 1 0 0 20 1.7 0.0054 6.6 0.025 1
TMCC1

Figure S1.  This figure depicts the distribution of mutations and mutation types across the TMCC1 significant gene.

PTEN

Figure S2.  This figure depicts the distribution of mutations and mutation types across the PTEN significant gene.

PLAC4

Figure S3.  This figure depicts the distribution of mutations and mutation types across the PLAC4 significant gene.

PIK3CA

Figure S4.  This figure depicts the distribution of mutations and mutation types across the PIK3CA significant gene.

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)
Copyright © 2013 Broad Institute TCGA GDAC as part of the TCGA Research Network. All rights reserved.
Made with Nozzle