Mutation Analysis (MutSig 2CV v3.1)
Cholangiocarcinoma (Primary solid tumor)
02 April 2015  |  analyses__2015_04_02
Maintainer Information
Citation Information
doi:10.7908/C1J67FWS
Maintained by David Heiman (Broad Institute)
Cite as Broad Institute TCGA Genome Data Analysis Center (2015): Mutation Analysis (MutSig 2CV v3.1). Broad Institute of MIT and Harvard. doi:10.7908/C1J67FWS
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: CHOL-TP

  • Number of patients in set: 35

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:CHOL-TP.final_analysis_set.maf

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

  • Significantly mutated genes (q ≤ 0.1): 16

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: 16. 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 BAP1 BRCA1 associated protein-1 (ubiquitin carboxy-terminal hydrolase) 2254 87 0 1 3 2 1 3 9 8 9 9.2e-14 1 0.46 1.6e-12 2e-08
2 PBRM1 polybromo 1 5417 23 0 0 0 6 0 2 8 8 8 7e-14 1 0.76 2.2e-12 2e-08
3 MLL3 myeloid/lymphoid or mixed-lineage leukemia 3 14968 3 0 0 2 4 1 0 7 7 4 0.000021 8e-05 0.99 8.2e-08 0.0005
4 TP53 tumor protein p53 1889 123 0 0 4 0 0 2 6 5 6 1.5e-08 1 0.32 1.1e-07 0.00052
5 HLA-B major histocompatibility complex, class I, B 1119 1000 0 0 5 0 0 0 5 5 3 7e-06 0.0018 0.97 3.2e-07 0.0012
6 FTH1 ferritin, heavy polypeptide 1 564 125 0 0 3 0 0 0 3 3 1 0.000064 0.001 0.078 1.1e-06 0.0034
7 ARID1A AT rich interactive domain 1A (SWI-like) 6934 166 0 1 1 0 0 5 6 5 6 3.8e-06 1 0.026 2.7e-06 0.0072
8 DDHD1 DDHD domain containing 1 2776 22 0 0 4 0 0 0 4 4 1 0.0046 0.0001 1 7.2e-06 0.017
9 IDH1 isocitrate dehydrogenase 1 (NADP+), soluble 1277 543 0 0 4 0 0 0 4 4 1 0.000046 0.0059 0.95 1e-05 0.021
10 MUC2 mucin 2, oligomeric mucus/gel-forming 8640 123 0 2 8 0 0 0 8 7 7 0.000037 0.032 0.63 0.000018 0.032
11 MUC21 mucin 21, cell surface associated 1709 74 0 0 3 0 0 0 3 3 2 0.00029 0.007 0.83 0.000033 0.053
12 PAXIP1 PAX interacting (with transcription-activation domain) protein 1 3292 371 0 0 3 0 1 0 4 4 4 0.00011 1 0.0074 0.000036 0.053
13 EPHA2 EPH receptor A2 2995 72 0 0 2 1 0 1 4 4 4 0.000013 1 0.17 0.000037 0.053
14 OTOP1 otopetrin 1 1861 162 0 0 4 0 0 0 4 4 3 0.00014 0.032 0.57 0.000046 0.06
15 IQSEC1 IQ motif and Sec7 domain 1 3514 18 0 0 0 0 2 0 2 2 1 0.00045 0.012 0.99 0.000075 0.091
16 CDC27 cell division cycle 27 homolog (S. cerevisiae) 2565 21 0 0 5 0 0 0 5 5 5 0.000012 1 0.53 0.000087 0.1
17 FAM35A family with sequence similarity 35, member A 2781 55 0 0 3 0 0 0 3 3 2 0.0036 0.0099 0.13 0.00021 0.22
18 MGA MAX gene associated 9290 14 0 0 2 0 1 0 3 3 3 0.00026 1 0.048 0.00027 0.27
19 TCHH trichohyalin 5836 39 0 0 5 0 0 0 5 5 4 0.0039 0.0049 0.96 0.00029 0.28
20 BCL6B B-cell CLL/lymphoma 6, member B (zinc finger protein) 1472 63 0 0 2 0 0 0 2 2 1 0.0028 0.01 0.72 0.00032 0.29
21 IL12RB2 interleukin 12 receptor, beta 2 2649 37 0 0 2 0 0 0 2 2 1 0.003 0.032 0.45 0.00043 0.35
22 ATM ataxia telangiectasia mutated 9438 70 0 1 2 0 2 0 4 4 4 0.00022 1 0.17 0.00044 0.35
23 CLDN16 claudin 16 934 173 0 0 2 0 0 0 2 2 1 0.004 0.01 0.96 0.00044 0.35
24 ZNF676 zinc finger protein 676 1775 262 0 0 3 0 0 0 3 3 2 0.045 0.001 0.99 0.0005 0.38
25 PRG4 proteoglycan 4 4319 753 0 1 4 0 0 0 4 4 3 0.0091 0.0046 0.96 0.00056 0.41
26 BCOR BCL6 co-repressor 5324 63 0 0 3 0 0 0 3 3 2 0.024 0.0019 0.93 0.00058 0.41
27 SMG1 smg-1 homolog, phosphatidylinositol 3-kinase-related kinase (C. elegans) 11234 44 0 0 4 0 0 0 4 4 3 0.031 0.0042 0.3 0.00079 0.53
28 NBN nibrin 2325 54 0 0 2 0 0 0 2 2 1 0.0086 0.01 0.012 0.00089 0.58
29 NF2 neurofibromin 2 (merlin) 1894 55 0 0 1 0 2 0 3 3 3 0.000097 1 0.94 0.001 0.62
30 NAP1L1 nucleosome assembly protein 1-like 1 1236 100 0 0 3 0 0 0 3 3 3 0.000099 1 0.82 0.001 0.62
31 HTT huntingtin 9693 18 0 1 3 0 0 2 5 4 4 0.022 0.004 1 0.0011 0.63
32 SLC19A3 solute carrier family 19, member 3 1511 195 0 0 2 0 0 0 2 2 1 0.011 0.01 0.026 0.0011 0.65
33 DBNDD2 dysbindin (dystrobrevin binding protein 1) domain containing 2 562 109 0 0 2 0 0 0 2 2 2 0.0013 NaN NaN 0.0013 0.71
34 PLEKHH3 pleckstrin homology domain containing, family H (with MyTH4 domain) member 3 2430 130 0 0 2 0 1 0 3 3 3 0.0003 1 0.43 0.0014 0.77
35 CYP3A5 cytochrome P450, family 3, subfamily A, polypeptide 5 1559 14 0 1 0 0 0 3 3 1 3 0.1 0.0058 0.02 0.0015 0.78
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)
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