Mutation Analysis (MutSigCV v0.6)
Uterine Corpus Endometrioid Carcinoma (Primary solid tumor)
22 February 2013  |  analyses__2013_02_22
Maintainer Information
Citation Information
doi:10.7908/C10P0X95
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/C10P0X95
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: 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: 19. 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
PIK3R1 462272 118792 0 118 83 89 2 0 20 1.5 0 400 0.24 0
PTEN 241552 58032 0 255 161 149 5 0 20 1.1 0 780 0.3 0
TP53 234360 68448 0 74 69 50 2 0 4 0.8 0 240 0.24 0
CTNNB1 456072 136400 0 80 74 25 7 0 20 1.6 5.6e-16 170 0.25 2.5e-12
ARID1A 1107816 326368 0 107 83 87 5 0 2 0.72 1.2e-15 400 0.24 4.5e-12
KRAS 150040 36704 0 53 53 11 2 0 1 1.8 3.9e-15 120 0.24 1.2e-11
PIK3CA 644552 164920 0 172 132 76 3 0 20 1.1 4.6e-15 340 0.24 1.2e-11
CTCF 437472 112096 0 52 45 41 1 0 20 0.54 8e-15 200 0.24 1.8e-11
FBXW7 481616 132184 0 47 39 31 1 0 20 1.4 8.7e-11 100 0.24 1.8e-07
ARID5B 692912 194432 0 35 29 34 9 0 20 1.6 2.2e-06 95 0.24 0.004
FGFR2 518320 145080 0 35 31 20 3 0 18 1.2 2.6e-06 81 0.24 0.0043
SPOP 226920 59520 0 23 21 18 0 0 20 1.2 3.9e-06 59 0.23 0.0059
PPP2R1A 328104 102672 0 30 27 18 3 0 17 1.2 0.000012 66 0.23 0.017
MORC4 534936 136896 0 28 20 26 2 0 15 0.89 0.000018 67 0.24 0.023
RG9MTD3 177816 46872 0 9 8 9 0 0 6 0 0.000023 33 0.23 0.028
SLC48A1 13144 3720 0 5 5 5 0 0 10 0.82 0.000072 19 0.21 0.08
CHD4 1150472 307024 0 44 35 39 2 0 20 0.58 0.000074 74 0.24 0.08
FAM9A 154008 38192 0 21 14 20 1 0 14 1.3 0.000097 45 0.23 0.099
SMTNL2 159216 47864 0 9 9 3 2 0 12 1 0.0001 44 0.23 0.099
CCND1 145328 41664 0 15 15 13 1 0 20 1.5 0.00013 48 0.23 0.12
LRCH2 181288 48112 0 23 17 21 4 0 3 0.62 0.00014 42 0.23 0.12
MTM1 362080 95232 0 22 15 20 3 0 4 0.44 0.00044 46 0.23 0.37
RBMX 245024 51832 0 14 13 8 0 0 20 1.1 0.00071 46 0.24 0.56
FOXA2 199392 55056 0 13 12 13 1 0 20 1.5 0.00073 51 0.24 0.56
ETV3 87048 21824 0 11 9 11 0 0 11 0.77 0.00099 26 0.22 0.72
ZFHX3 2120648 616032 0 82 44 74 13 0 4 1.3 0.0011 120 0.25 0.79
TIAL1 238328 61256 0 15 11 15 2 0 20 0.59 0.0012 34 0.24 0.81
NFE2L2 349432 92504 0 15 15 12 0 0 20 0.84 0.0012 44 0.23 0.81
CHIC1 31744 7936 0 4 4 4 0 0 20 0.79 0.0015 16 0.21 0.97
CASP8 361088 84568 0 21 17 19 6 0 20 1.2 0.0016 50 0.23 0.99
C11orf80 285944 82088 0 11 9 10 0 0 2 0 0.0017 31 0.22 1
ADSS 259408 71920 0 6 6 6 4 0 20 0.24 0.002 22 0.21 1
CHEK2 350176 96720 0 14 13 13 0 0 0 0 0.002 46 0.24 1
RASA1 575856 157976 0 31 22 29 3 0 1 0.68 0.0023 67 0.24 1
BRS3 229400 69440 0 17 15 17 2 0 20 0.9 0.0024 36 0.23 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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