Mutation Analysis (MutSigCV v0.6)
Stomach Adenocarcinoma (Primary solid tumor)
22 February 2013  |  analyses__2013_02_22
Maintainer Information
Citation Information
doi:10.7908/C14Q7S7V
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/C14Q7S7V
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: STAD-TP

  • Number of patients in set: 116

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: STAD-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: 4. 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
TP53 109620 32016 87904 57 52 42 1 1 4 0.82 1.9e-15 180 0.12 3.4e-11
CBWD1 86584 22748 133628 15 14 2 0 3 5 0.62 1.7e-09 60 0.11 0.000016
KRAS 70516 17224 61632 14 14 6 0 0 1 0 4e-09 41 0.11 0.000024
RPL22 35088 8468 33712 9 9 1 0 1 20 1.2 5.3e-06 41 0.11 0.024
ARID1A 518396 152712 223208 26 22 25 1 5 2 0.53 0.000093 73 0.12 0.34
ACVR2A 144752 38160 133944 14 13 5 0 7 10 1.1 0.0011 48 0.11 1
REG1A 47960 12064 78648 3 3 3 0 0 2 0 0.0035 10 0.091 1
RNF43 192524 60852 112588 14 13 9 2 4 8 0.87 0.0062 44 0.11 1
POTEG 111536 27260 94704 6 6 6 0 0 0 0 0.0095 19 0.1 1
TMEM98 57028 17928 68364 5 4 5 0 0 1 0 0.0097 15 0.1 1
P2RY12 357328 99468 261692 7 6 7 0 0 0 0 0.011 19 0.1 1
FGF22 14324 4812 3192 3 3 1 1 0 20 1.2 0.018 15 0.1 1
PPPDE1 54576 14964 85192 3 3 3 0 5 20 0.16 0.021 10 0.088 1
FCRL3 200620 60668 182348 8 8 8 1 0 0 0.16 0.03 22 0.13 1
PARP11 96740 22040 266780 5 5 5 0 1 2 0.19 0.033 14 0.11 1
RAB34 82476 23756 78836 2 2 2 0 0 3 0 0.034 6.8 0.074 1
SAGE1 250772 69436 318912 4 4 4 0 0 1 0 0.035 12 0.095 1
PTH2 16776 6852 13652 3 3 1 0 0 20 0.92 0.036 12 0.095 1
TM7SF4 127012 37756 40576 7 7 7 1 1 3 0.49 0.037 23 0.11 1
IL11 12748 5040 6080 2 2 2 0 0 20 0.73 0.042 8.7 0.087 1
RHOA 77360 22500 84052 8 7 4 0 5 20 0.83 0.044 22 0.11 1
CCDC153 37816 10672 57280 3 3 3 0 1 6 0.31 0.044 9.8 0.092 1
TMSB15B 13452 3132 55472 2 2 2 0 2 20 0.68 0.045 7.7 0.072 1
PRRG3 61944 19084 39508 6 6 6 2 0 20 0.81 0.049 19 0.11 1
SPRYD5 104412 26328 72100 8 8 6 0 2 0 0.78 0.049 29 0.12 1
GHRH 30324 8292 52392 3 3 3 0 2 20 0.73 0.05 12 0.097 1
WSB2 110432 32248 102788 5 5 5 0 0 17 0.28 0.05 14 0.11 1
TNFAIP2 94452 28544 75360 4 4 4 1 1 20 0.41 0.05 16 0.1 1
OCEL1 60148 17924 59204 4 4 4 0 1 20 0.63 0.051 16 0.1 1
PGM5 123172 36436 106168 19 16 5 0 4 20 0.98 0.052 30 0.11 1
C16orf74 3300 696 8580 1 1 1 0 0 20 0.95 0.052 5.5 0.057 1
OR7D4 82532 26216 11352 4 4 4 0 0 2 0 0.057 14 0.1 1
LRRC27 145748 38920 173612 3 3 3 0 0 1 0 0.058 11 0.094 1
MXRA8 61628 19692 35452 5 4 3 1 4 20 0.51 0.059 15 0.1 1
PHF2 225192 63444 193000 13 12 5 4 6 6 0.85 0.062 38 0.11 1
TP53

Figure S1.  This figure depicts the distribution of mutations and mutation types across the TP53 significant gene.

KRAS

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

RPL22

Figure S3.  This figure depicts the distribution of mutations and mutation types across the RPL22 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)
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