Mutation Analysis (MutSigCV v0.6)
Bladder Urothelial Carcinoma (Primary solid tumor)
22 February 2013  |  analyses__2013_02_22
Maintainer Information
Citation Information
doi:10.7908/C13X84TR
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/C13X84TR
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: BLCA-TP

  • Number of patients in set: 28

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: BLCA-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: 1. 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
FBXW7 54376 14924 1195 6 5 5 0 0 20 0 2e-06 20 0.025 0.036
TP53 26460 7728 1030 14 11 13 1 0 4 2.9 0.000015 29 0.026 0.13
HLA-A 22960 6944 770 3 3 3 0 0 20 0.68 0.00052 14 0.023 1
TMCO2 12040 3388 220 2 2 1 0 0 20 0.55 0.00056 12 0.022 1
CAMKK2 33684 9268 2150 2 2 2 0 0 18 0 0.00063 12 0.023 1
KLF5 24304 7056 305 2 2 2 1 0 20 0.53 0.0021 11 0.023 1
RFTN2 31528 8484 815 3 3 3 0 0 20 1.2 0.0023 13 0.024 1
NFE2L2 39452 10444 405 4 4 4 0 0 20 0 0.0025 11 0.022 1
FAM57A 12516 3836 310 2 2 2 0 0 20 0 0.0033 6.4 0.018 1
XPR1 46508 12880 1470 5 4 5 1 0 20 1.1 0.0039 14 0.024 1
ELF3 24892 6832 790 3 3 3 0 0 20 2.4 0.0042 13 0.024 1
C11orf85 15064 3864 790 2 2 2 0 0 20 0.6 0.0048 8.7 0.021 1
ZNF263 44716 12600 595 3 3 3 0 0 20 0.92 0.0054 12 0.025 1
CTF1 2688 756 100 1 1 1 0 0 20 1.3 0.0057 6.5 0.017 1
PYGO1 27580 7868 320 3 3 3 0 0 20 1.4 0.0058 11 0.024 1
GPS2 24836 7196 1020 4 3 4 0 0 20 2.4 0.0059 12 0.027 1
LASP1 15008 3780 590 2 2 2 0 0 20 0.79 0.0068 8.5 0.021 1
FEZ2 18116 4536 495 2 2 2 0 0 20 0.53 0.0071 8.5 0.021 1
ARID1A 125076 36848 1880 8 6 8 1 0 2 1.6 0.0085 24 0.026 1
GABRB2 33180 9296 925 2 2 2 1 0 20 0.37 0.0097 8.4 0.021 1
FIGN 48888 14924 220 2 2 2 0 0 20 0.81 0.0098 11 0.023 1
SETD2 138124 36988 1845 5 5 5 0 0 7 0 0.01 18 0.026 1
MLL2 296548 98028 3855 6 5 6 0 0 20 0.84 0.011 23 0.026 1
HOXB4 12936 3836 205 2 2 2 0 0 20 0 0.012 6.1 0.019 1
NME4 9268 2772 360 1 1 1 0 0 20 0.65 0.012 6.1 0.018 1
A2M 89628 26012 2470 3 3 3 0 0 20 0 0.012 10 0.027 1
ZNF555 42252 10584 305 3 3 3 1 0 20 0.54 0.013 9.8 0.022 1
FOXP2 49616 13188 1600 2 2 2 0 0 3 0 0.013 11 0.023 1
MGP 6888 1792 380 1 1 1 0 0 20 0 0.013 6.4 0.018 1
NUDT14 10836 3528 335 1 1 1 0 0 20 0.57 0.015 6.1 0.019 1
EPRS 102956 27244 3200 3 3 3 0 0 20 0 0.015 10 0.023 1
AMACR 30940 5908 560 2 2 2 0 0 20 0.44 0.016 8.1 0.021 1
TNFSF4 12236 3388 435 1 1 1 0 0 20 1 0.016 6 0.018 1
ATXN7 54264 16492 965 3 2 3 0 0 20 0.33 0.016 8.2 0.021 1
MTX3 15232 4452 450 1 1 1 0 0 20 0 0.017 3.8 0.011 1
FBXW7

Figure S1.  This figure depicts the distribution of mutations and mutation types across the FBXW7 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