Mutation Analysis (MutSigCV v0.9)
Uterine Corpus Endometrioid Carcinoma (Primary solid tumor)
23 May 2013  |  analyses__2013_05_23
Maintainer Information
Citation Information
doi:10.7908/C1M906R3
Maintained by Dan DiCara (Broad Institute)
Cite as Broad Institute TCGA Genome Data Analysis Center (2013): Mutation Analysis (MutSigCV v0.9). Broad Institute of MIT and Harvard. doi:10.7908/C1M906R3
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: UCEC-TP

  • Number of patients in set: 248

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: UCEC-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: 26. 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
PTEN 241552 58032 0 255 161 149 5 0 20 1.1 0 760 0.29 0
ARID1A 1107816 326368 0 107 83 87 5 0 2 0.72 1.1e-15 380 0.25 8.1e-12
RPL22 74896 18104 0 32 31 7 0 0 20 1.3 1.3e-15 170 0.25 8.1e-12
PIK3CA 644552 164920 0 172 132 76 3 0 20 1.1 2.4e-15 350 0.25 1e-11
PIK3R1 462272 118792 0 118 83 89 2 0 20 1.5 2.8e-15 400 0.25 1e-11
CTNNB1 456072 136400 0 80 74 25 7 0 20 1.6 4.9e-15 180 0.27 1.4e-11
TP53 234360 68448 0 74 69 50 2 0 4 0.8 5.3e-15 220 0.24 1.4e-11
CTCF 437472 112096 0 52 45 41 1 0 20 0.54 6.2e-15 200 0.26 1.4e-11
FBXW7 481616 132184 0 47 39 31 1 0 20 1.4 3.7e-14 110 0.27 7.5e-11
KRAS 150040 36704 0 53 53 11 2 0 1 1.8 3.1e-12 110 0.25 5.6e-09
ARID5B 692912 194432 0 35 29 34 9 0 20 1.6 1.4e-09 100 0.25 2.2e-06
SPOP 226920 59520 0 23 21 18 0 0 20 1.2 5.2e-09 65 0.24 7.9e-06
FGFR2 518320 145080 0 35 31 20 3 0 18 1.2 1.2e-08 82 0.24 0.000017
PPP2R1A 328104 102672 0 30 27 18 3 0 17 1.2 9.7e-08 68 0.24 0.00013
MORC4 534936 136896 0 28 20 26 2 0 15 0.89 6.2e-07 68 0.26 0.00075
CCND1 145328 41664 0 15 15 13 1 0 20 1.5 1e-06 51 0.24 0.0011
CHD4 1150472 307024 0 44 35 39 2 0 20 0.58 1.1e-06 78 0.24 0.0012
FAM9A 154008 38192 0 21 14 20 1 0 14 1.3 1.6e-06 48 0.28 0.0017
SMTNL2 159216 47864 0 9 9 3 2 0 12 1 0.000012 45 0.24 0.011
CASP8 361088 84568 0 21 17 19 6 0 20 1.2 0.000015 54 0.26 0.014
FOXA2 199392 55056 0 13 12 13 1 0 20 1.5 0.000016 52 0.24 0.014
RBMX 245024 51832 0 14 13 8 0 0 20 1.1 0.000022 49 0.24 0.018
SLC48A1 13144 3720 0 5 5 5 0 0 10 0.82 0.000025 20 0.22 0.02
BRS3 229400 69440 0 17 15 17 2 0 20 0.9 0.000051 40 0.26 0.039
ADSS 259408 71920 0 6 6 6 4 0 20 0.24 0.000094 23 0.24 0.066
NFE2L2 349432 92504 0 15 15 12 0 0 20 0.84 0.000095 44 0.24 0.066
RB1 706304 186248 0 29 20 27 4 0 20 0.81 0.00017 55 0.24 0.12
TIAL1 238328 61256 0 15 11 15 2 0 20 0.59 0.00019 37 0.23 0.13
CDHR4 58528 19592 0 8 7 8 4 0 20 0.93 0.00029 22 0.23 0.19
CHIC1 31744 7936 0 4 4 4 0 0 20 0.79 0.00033 18 0.22 0.2
ZFHX3 2120648 616032 0 82 44 74 13 0 4 1.3 0.00034 120 0.25 0.2
SGK1 364312 97216 0 16 15 14 3 0 20 1.7 0.00039 53 0.24 0.22
RNF43 412920 130696 0 14 12 14 3 0 8 0.67 0.00043 42 0.24 0.24
ETV3 87048 21824 0 11 9 11 0 0 11 0.77 0.00047 28 0.23 0.25
LEPREL2 242792 76136 0 10 10 7 2 0 20 0.64 0.00049 36 0.24 0.25
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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