Mutation Analysis (MutSig 2CV v3.1)
Stomach Adenocarcinoma (Primary solid tumor)
17 October 2014  |  analyses__2014_10_17
Maintainer Information
Citation Information
Maintained by David Heiman (Broad Institute)
Cite as Broad Institute TCGA Genome Data Analysis Center (2014): Mutation Analysis (MutSig 2CV v3.1). Broad Institute of MIT and Harvard. doi:10.7908/C1XG9Q3Q
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. MutSig 2CV v3.1 was used to generate the results found in this report.

  • Working with individual set: STAD-TP

  • Number of patients in set: 221

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
  • MAF used for this analysis:STAD-TP.final_analysis_set.maf

  • Blacklist used for this analysis: pancan_mutation_blacklist.v14.hg19.txt

  • Significantly mutated genes (q ≤ 0.1): 23

Results
Lego Plots

The mutation spectrum is depicted in the lego plots below in which the 96 possible mutation types are subdivided into six large blocks, color-coded to reflect the base substitution type. Each large block is further subdivided into the 16 possible pairs of 5' and 3' neighbors, as listed in the 4x4 trinucleotide context legend. The height of each block corresponds to the mutation frequency for that kind of mutation (counts of mutations normalized by the base coverage in a given bin). The shape of the spectrum is a signature for dominant mutational mechanisms in different tumor types.

Figure 1.  Get High-res Image SNV Mutation rate lego plot for entire set. Each bin is normalized by base coverage for that bin. Colors represent the six SNV types on the upper right. The three-base context for each mutation is labeled in the 4x4 legend on the lower right. The fractional breakdown of SNV counts is shown in the pie chart on the upper left. If this figure is blank, not enough information was provided in the MAF to generate it.

Figure 2.  Get High-res Image SNV Mutation rate lego plots for 4 slices of mutation allele fraction (0<=AF<0.1, 0.1<=AF<0.25, 0.25<=AF<0.5, & 0.5<=AF) . The color code and three-base context legends are the same as the previous figure. If this figure is blank, not enough information was provided in the MAF to generate it.

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

  • 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: 23. 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).

rank gene longname codelen nnei nncd nsil nmis nstp nspl nind nnon npat nsite pCV pCL pFN p q
1 TP53 tumor protein p53 1890 66 0 1 65 17 6 16 104 99 67 1e-16 1e-05 1e-05 1e-16 4.6e-13
2 PIK3CA phosphoinositide-3-kinase, catalytic, alpha polypeptide 3287 22 0 2 61 1 0 0 62 48 31 4.5e-14 1e-05 0.047 1e-16 4.6e-13
3 CBWD1 COBW domain containing 1 1296 46 0 0 2 0 28 0 30 28 3 1e-16 1e-05 1e-05 1e-16 4.6e-13
4 KRAS v-Ki-ras2 Kirsten rat sarcoma viral oncogene homolog 709 7 0 0 25 0 0 0 25 25 6 2.9e-14 1e-05 0.29 1e-16 4.6e-13
5 ARID1A AT rich interactive domain 1A (SWI-like) 6934 11 0 2 16 15 4 12 47 41 47 7.1e-16 0.8 0.29 1.7e-14 6.2e-11
6 PGM5 phosphoglucomutase 5 1744 32 0 1 23 2 0 0 25 22 7 1.8e-08 1e-05 1 5.6e-12 1.7e-08
7 RHOA ras homolog gene family, member A 918 120 0 0 14 0 0 0 14 13 10 9.8e-09 0.0073 0.5 1.6e-09 4.2e-06
8 SMAD4 SMAD family member 4 1699 21 0 1 17 1 0 4 22 19 19 8e-09 0.016 0.46 2.8e-09 6.5e-06
9 IRF2 interferon regulatory factor 2 1082 32 0 1 11 2 2 2 17 14 15 5.1e-08 0.1 0.0012 4e-09 8.1e-06
10 LARP4B La ribonucleoprotein domain family, member 4B 2283 1 0 1 6 1 0 7 14 12 8 3.3e-06 2e-05 0.51 4.6e-09 8.4e-06
11 APC adenomatous polyposis coli 8592 2 0 5 18 11 0 9 38 33 33 1.2e-07 0.0062 0.98 3e-08 5e-05
12 FBXW7 F-box and WD repeat domain containing 7 2580 2 0 1 15 3 1 1 20 19 13 2.5e-07 0.0083 0.29 3.8e-08 0.000057
13 CDH1 cadherin 1, type 1, E-cadherin (epithelial) 2709 30 0 4 15 0 4 0 19 18 18 5e-06 0.2 0.0004 1.2e-07 0.00016
14 HLA-B major histocompatibility complex, class I, B 1119 26 0 0 7 2 3 1 13 12 13 4.7e-07 1 0.026 4.7e-07 0.00061
15 BCOR BCL6 co-repressor 5324 0 0 3 8 7 0 3 18 16 18 2.6e-07 1 0.22 1.8e-06 0.0022
16 C13orf33 chromosome 13 open reading frame 33 928 41 0 1 0 1 0 5 6 6 2 0.0036 2e-05 0.51 2.4e-06 0.0028
17 CIC capicua homolog (Drosophila) 4905 0 0 7 8 2 0 6 16 14 13 0.00073 0.00038 0.97 7.5e-06 0.0078
18 ACVR1B activin A receptor, type IB 1679 21 0 1 7 3 0 2 12 10 8 0.00021 0.002 0.38 7.7e-06 0.0078
19 ZBTB20 zinc finger and BTB domain containing 20 2238 0 0 7 13 0 0 9 22 16 15 0.00099 0.00053 0.91 0.000019 0.018
20 C16orf74 chromosome 16 open reading frame 74 243 3 0 0 0 0 0 2 2 2 1 0.000041 0.043 0.99 0.000025 0.023
21 MVK mevalonate kinase 1397 8 0 0 5 0 0 3 8 8 6 0.00057 0.0049 0.19 0.000043 0.037
22 ERBB2 v-erb-b2 erythroblastic leukemia viral oncogene homolog 2, neuro/glioblastoma derived oncogene homolog (avian) 3887 0 0 1 12 0 0 0 12 11 8 0.37 1e-05 0.47 5e-05 0.042
23 CR1 complement component (3b/4b) receptor 1 (Knops blood group) 7654 12 0 2 19 3 0 1 23 20 21 0.0016 0.02 0.07 0.00012 0.095
24 C1R complement component 1, r subcomponent 1839 7 0 3 0 0 0 4 4 3 2 0.15 0.00011 0.11 0.00018 0.13
25 CTNND1 catenin (cadherin-associated protein), delta 1 2983 17 0 2 7 4 0 2 13 13 13 0.0003 1 0.017 0.00026 0.19
26 MLXIPL MLX interacting protein-like 2625 15 0 0 11 0 1 1 13 13 13 0.000033 0.55 0.94 0.00027 0.19
27 MLL4 myeloid/lymphoid or mixed-lineage leukemia 2 8293 33 0 6 14 2 2 10 28 20 27 0.000077 0.21 0.98 0.00029 0.2
28 NLK nemo-like kinase 1624 74 0 1 3 1 0 2 6 5 4 0.059 0.00036 0.89 0.00034 0.22
29 MMEL1 membrane metallo-endopeptidase-like 1 2434 2 0 0 3 2 1 0 6 6 6 0.00023 1 0.086 0.00036 0.22
30 FAM113B family with sequence similarity 113, member B 1303 5 0 0 9 0 0 1 10 10 10 0.000032 1 0.82 0.00036 0.22
31 ZNF48 zinc finger protein 48 1863 68 0 2 1 0 0 3 4 4 2 0.37 0.0001 0.26 0.00042 0.24
32 MAP7D1 MAP7 domain containing 1 2590 37 0 2 5 0 1 2 8 8 6 0.0029 0.0068 0.69 0.00042 0.24
33 KCNJ6 potassium inwardly-rectifying channel, subfamily J, member 6 1284 6 0 0 7 1 0 0 8 8 8 0.0018 0.097 0.1 0.00048 0.26
34 GTF2I general transcription factor II, i 3133 9 0 0 6 0 0 0 6 6 3 0.046 0.0012 0.68 0.0005 0.27
35 C7orf50 chromosome 7 open reading frame 50 2545 93 0 1 2 0 0 3 5 5 3 0.014 0.0018 0.14 0.00051 0.27
TP53

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

PIK3CA

Figure S2.  This figure depicts the distribution of mutations and mutation types across the PIK3CA significant gene.

CBWD1

Figure S3.  This figure depicts the distribution of mutations and mutation types across the CBWD1 significant gene.

KRAS

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

ARID1A

Figure S5.  This figure depicts the distribution of mutations and mutation types across the ARID1A significant gene.

PGM5

Figure S6.  This figure depicts the distribution of mutations and mutation types across the PGM5 significant gene.

RHOA

Figure S7.  This figure depicts the distribution of mutations and mutation types across the RHOA significant gene.

SMAD4

Figure S8.  This figure depicts the distribution of mutations and mutation types across the SMAD4 significant gene.

IRF2

Figure S9.  This figure depicts the distribution of mutations and mutation types across the IRF2 significant gene.

LARP4B

Figure S10.  This figure depicts the distribution of mutations and mutation types across the LARP4B significant gene.

APC

Figure S11.  This figure depicts the distribution of mutations and mutation types across the APC significant gene.

FBXW7

Figure S12.  This figure depicts the distribution of mutations and mutation types across the FBXW7 significant gene.

CDH1

Figure S13.  This figure depicts the distribution of mutations and mutation types across the CDH1 significant gene.

HLA-B

Figure S14.  This figure depicts the distribution of mutations and mutation types across the HLA-B significant gene.

BCOR

Figure S15.  This figure depicts the distribution of mutations and mutation types across the BCOR significant gene.

C13orf33

Figure S16.  This figure depicts the distribution of mutations and mutation types across the C13orf33 significant gene.

CIC

Figure S17.  This figure depicts the distribution of mutations and mutation types across the CIC significant gene.

ACVR1B

Figure S18.  This figure depicts the distribution of mutations and mutation types across the ACVR1B significant gene.

ZBTB20

Figure S19.  This figure depicts the distribution of mutations and mutation types across the ZBTB20 significant gene.

C16orf74

Figure S20.  This figure depicts the distribution of mutations and mutation types across the C16orf74 significant gene.

MVK

Figure S21.  This figure depicts the distribution of mutations and mutation types across the MVK significant gene.

ERBB2

Figure S22.  This figure depicts the distribution of mutations and mutation types across the ERBB2 significant gene.

CR1

Figure S23.  This figure depicts the distribution of mutations and mutation types across the CR1 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

In addition to the links below, the full results of the analysis summarized in this report can also be downloaded programmatically using firehose_get, or interactively from either the Broad GDAC website or TCGA Data Coordination Center Portal.

References
[1] TCGA, Integrated genomic analyses of ovarian carcinoma, Nature 474:609 - 615 (2011)