Mutation Analysis (MutSig 2CV v3.1)
Liver Hepatocellular Carcinoma (Primary solid tumor)
15 July 2014  |  analyses__2014_07_15
Maintainer Information
Citation Information
doi:10.7908/C1D7995K
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/C1D7995K
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: LIHC-TP

  • Number of patients in set: 202

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:LIHC-TP.final_analysis_set.maf

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

  • Significantly mutated genes (q ≤ 0.1): 71

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: 71. 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 21 0 2 44 8 5 10 67 65 53 1e-16 0.00085 0.00027 1e-16 9.2e-13
2 CTNNB1 catenin (cadherin-associated protein), beta 1, 88kDa 2406 62 0 2 56 0 0 5 61 57 29 1.1e-15 1e-05 0.1 1e-16 9.2e-13
3 ARID1A AT rich interactive domain 1A (SWI-like) 6934 0 0 4 8 5 1 12 26 25 24 3.1e-12 0.017 0.92 2.4e-12 1.2e-08
4 RB1 retinoblastoma 1 (including osteosarcoma) 3711 1 0 1 5 1 3 11 20 18 20 8.4e-14 1 0.89 2.6e-12 1.2e-08
5 AXIN1 axin 1 2629 4 0 2 4 1 3 6 14 12 14 2e-10 1 0.35 2.5e-09 9.3e-06
6 KRTAP5-11 keratin associated protein 5-11 473 0 0 0 1 0 0 4 5 5 3 5e-07 0.0018 0.94 3.4e-08 0.0001
7 AHCTF1 AT hook containing transcription factor 1 6970 0 0 4 6 0 0 8 14 13 8 0.00046 1e-05 1 9.3e-08 0.00024
8 GPATCH4 G patch domain containing 4 1176 556 0 1 11 0 0 0 11 11 2 0.0012 1e-05 1 2.3e-07 0.00053
9 CD207 CD207 molecule, langerin 1009 2 0 3 6 0 5 0 11 8 5 0.002 1e-05 0.12 3.7e-07 0.00075
10 EEF1A1 eukaryotic translation elongation factor 1 alpha 1 1417 37 0 1 10 0 0 0 10 9 6 0.0028 0.00025 0.27 9.9e-07 0.0018
11 BAP1 BRCA1 associated protein-1 (ubiquitin carboxy-terminal hydrolase) 2254 53 0 1 3 2 1 5 11 11 11 5.1e-06 0.15 0.061 1.5e-06 0.0025
12 CHIT1 chitinase 1 (chitotriosidase) 1443 15 0 0 7 2 0 0 9 8 4 0.011 1e-05 0.49 1.8e-06 0.0028
13 PPIAL4G peptidylprolyl isomerase A (cyclophilin A)-like 4G 497 65 0 0 9 0 0 0 9 7 3 0.0027 1e-05 0.94 3.1e-06 0.0043
14 ALB albumin 1888 6 0 4 11 0 2 14 27 24 26 1.1e-06 0.45 0.25 3.4e-06 0.0045
15 PABPC1 poly(A) binding protein, cytoplasmic 1 1966 22 0 3 9 0 0 0 9 8 6 0.031 2e-05 0.23 5e-06 0.0061
16 TREML2 triggering receptor expressed on myeloid cells-like 2 982 19 0 1 7 0 0 0 7 6 4 0.033 6e-05 0.077 5.3e-06 0.0061
17 PRH2 proline-rich protein HaeIII subfamily 2 516 37 0 0 6 0 0 0 6 6 3 0.0024 0.00011 1 7e-06 0.0076
18 MUC17 mucin 17, cell surface associated 13532 2 0 35 84 1 2 1 88 28 72 0.11 1e-05 1 0.000016 0.015
19 AZIN1 antizyme inhibitor 1 1387 3 0 4 13 0 0 0 13 13 4 0.11 1e-05 0.99 0.000016 0.015
20 NBPF3 neuroblastoma breakpoint family, member 3 1954 16 0 1 8 0 0 0 8 7 5 0.12 2e-05 0.056 0.000018 0.016
21 BCLAF1 BCL2-associated transcription factor 1 2807 25 0 1 11 0 3 0 14 14 12 0.00017 0.0077 0.63 0.000022 0.019
22 SCRN3 secernin 3 1376 31 0 0 9 0 0 0 9 9 5 0.0086 0.00014 1 0.000023 0.019
23 MUC6 mucin 6, oligomeric mucus/gel-forming 7450 2 0 17 32 1 0 5 38 25 31 0.22 1e-05 0.97 3e-05 0.024
24 UGT2B28 UDP glucuronosyltransferase 2 family, polypeptide B28 1612 28 0 2 11 1 0 1 13 11 9 0.23 1e-05 0.28 0.000032 0.024
25 CDHR5 cadherin-related family member 5 2594 1 0 1 12 0 0 1 13 11 6 0.24 1e-05 1 0.000033 0.024
26 KCTD3 potassium channel tetramerisation domain containing 3 2516 1 0 0 2 0 0 4 6 6 3 0.016 0.00012 1 0.000034 0.024
27 CDC27 cell division cycle 27 homolog (S. cerevisiae) 2565 4 0 9 14 0 1 1 16 14 7 0.25 1e-05 0.49 0.000035 0.024
28 CR1 complement component (3b/4b) receptor 1 (Knops blood group) 7654 14 0 3 13 5 2 3 23 19 20 0.00033 0.021 0.029 0.000037 0.024
29 TCEAL6 transcription elongation factor A (SII)-like 6 556 56 0 0 14 0 0 0 14 4 6 0.28 1e-05 1 0.000038 0.024
30 LILRA6 leukocyte immunoglobulin-like receptor, subfamily A (with TM domain), member 6 1474 29 0 3 10 1 0 2 13 11 9 0.0043 0.00045 1 0.000042 0.025
31 BIK BCL2-interacting killer (apoptosis-inducing) 499 0 0 0 1 0 0 2 3 3 2 0.00042 0.024 0.22 0.000043 0.025
32 SRRM3 serine/arginine repetitive matrix 3 2015 46 0 0 4 1 0 0 5 4 3 0.033 0.00071 0.003 0.000049 0.027
33 MKI67 antigen identified by monoclonal antibody Ki-67 9827 21 0 8 19 0 0 5 24 17 20 0.36 1e-05 0.95 0.000049 0.027
34 ALDH3B1 aldehyde dehydrogenase 3 family, member B1 1437 0 0 0 0 0 6 0 6 5 3 0.00025 0.047 0.017 0.000054 0.029
35 POTEG POTE ankyrin domain family, member G 1568 42 0 1 11 1 0 2 14 13 10 0.048 5e-05 0.98 0.000064 0.033
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)
Copyright © 2014 Broad Institute TCGA GDAC as part of the TCGA Research Network. All rights reserved.
Made with Nozzle