Mutation Analysis (MutSigCV v0.9)
Lung Squamous Cell Carcinoma (Primary solid tumor)
21 August 2015  |  analyses__2015_08_21
Maintainer Information
Citation Information
doi:10.7908/C1HT2NMP
Maintained by David Heiman (Broad Institute)
Cite as Broad Institute TCGA Genome Data Analysis Center (2015): Mutation Analysis (MutSigCV v0.9). Broad Institute of MIT and Harvard. doi:10.7908/C1HT2NMP
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 v0.9 was used to generate the results found in this report.

  • Working with individual set: LUSC-TP

  • Number of patients in set: 178

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:LUSC-TP.final_analysis_set.maf

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

  • Significantly mutated genes (q ≤ 0.1): 14

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). If the figure is unpopulated, then full coverage is assumed (e.g. MutSig CV doesn't use WIGs and assumes full coverage).

Figure 1. 

Distribution of Mutation Counts, Coverage, and Mutation Rates Across Samples

Figure 2.  Patients counts and rates file used to generate this plot: LUSC-TP.patients.counts_and_rates.txt

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 3.  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 4.  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 5.  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: 14. 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 168210 49128 6592 150 145 97 1 0 4 1.1 1e-15 490 0.28 1.8e-11
CDKN2A 107156 30438 1984 26 26 23 1 0 6 2.7 6e-15 110 0.26 5.5e-11
PTEN 173372 41652 5568 16 14 15 0 0 20 0.67 2.4e-12 64 0.16 1.5e-08
NFE2L2 250802 66394 2592 28 27 15 0 0 20 1.3 1.4e-10 70 0.24 6.5e-07
KEAP1 231400 67640 2784 24 22 21 0 0 20 0.64 6e-10 61 0.21 2.2e-06
CSMD3 1583488 442508 45504 121 81 119 21 0 5 2.9 2.8e-08 160 0.21 0.000085
PIK3CA 462622 118370 12672 29 27 16 1 0 20 0.89 4.9e-08 65 0.22 0.00013
RB1 506944 133678 15552 12 12 12 0 0 20 0.65 5.9e-08 60 0.18 0.00013
ELTD1 288894 77252 9216 18 18 18 1 0 15 1.3 1.3e-07 60 0.24 0.00025
DCDC1 155216 42186 4832 18 18 18 4 0 20 1.7 5.4e-07 46 0.25 0.00098
COL11A1 762018 239232 40672 45 34 45 7 0 18 2.1 3.8e-06 93 0.26 0.0063
OR2G6 128694 40228 768 17 16 17 3 0 20 1.9 6.2e-06 42 0.17 0.0095
ASCL4 31328 11392 320 6 6 6 0 0 20 1.1 0.000015 25 0.2 0.021
COL22A1 597902 200428 36672 36 30 36 4 0 11 2.1 0.000058 80 0.2 0.076
FBXW7 345676 94874 7648 10 10 8 3 0 20 0.51 0.00012 36 0.2 0.15
SPANXN1 32396 7120 1408 5 5 5 0 0 20 2.9 0.00015 23 0.17 0.16
CUL3 325562 83482 9568 12 11 12 1 0 20 1.1 0.00015 43 0.21 0.16
GPR174 135458 38270 768 6 5 6 0 0 19 0.67 0.00019 27 0.28 0.19
LRRC4C 262728 78676 768 19 17 19 1 0 13 1.1 0.00027 42 0.19 0.26
OR9G1 124422 38092 864 11 11 11 4 0 20 1.2 0.00029 28 0.24 0.26
ALPK2 908512 255252 7776 18 18 17 2 0 15 0.65 0.00037 54 0.23 0.33
EPB41L3 460308 132966 13376 20 18 20 2 0 16 1.6 0.00056 55 0.2 0.46
NOTCH1 710754 205412 12160 16 14 16 3 0 20 0.82 0.00059 54 0.2 0.46
SLC13A1 251158 73692 9504 12 12 12 1 0 20 1.1 0.0006 33 0.2 0.46
OR6F1 124600 40050 768 13 13 13 2 0 20 2.1 0.00066 30 0.19 0.47
HLA-A 145960 44144 4928 7 6 7 0 0 20 1.1 0.00072 30 0.3 0.47
APOBEC1 102350 26522 3296 7 7 7 1 0 20 0.78 0.00072 23 0.24 0.47
ADAM2 322536 79210 12576 12 12 12 2 0 12 1.4 0.00073 42 0.3 0.47
LEPROT 53400 16198 2048 4 4 4 0 0 15 0.99 0.00079 19 0.19 0.47
TGIF2LX 99324 28658 768 11 9 11 1 0 20 2.1 0.0008 30 0.21 0.47
ZBBX 349414 85974 11392 17 17 17 1 0 20 2.1 0.00082 47 0.2 0.47
PI16 169278 57138 3424 7 7 7 1 0 20 0.49 0.00083 25 0.22 0.47
CERK 193308 53400 6656 6 6 6 1 0 20 0.65 0.00084 26 0.19 0.47
ZNF80 116234 29548 768 7 7 7 1 0 20 1.2 0.00088 25 0.35 0.47
C8orf34 186010 49306 8288 8 8 8 0 0 20 1.7 0.00093 33 0.32 0.49
TP53

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

CDKN2A

Figure S2.  This figure depicts the distribution of mutations and mutation types across the CDKN2A significant gene.

PTEN

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

NFE2L2

Figure S4.  This figure depicts the distribution of mutations and mutation types across the NFE2L2 significant gene.

KEAP1

Figure S5.  This figure depicts the distribution of mutations and mutation types across the KEAP1 significant gene.

CSMD3

Figure S6.  This figure depicts the distribution of mutations and mutation types across the CSMD3 significant gene.

PIK3CA

Figure S7.  This figure depicts the distribution of mutations and mutation types across the PIK3CA significant gene.

RB1

Figure S8.  This figure depicts the distribution of mutations and mutation types across the RB1 significant gene.

ELTD1

Figure S9.  This figure depicts the distribution of mutations and mutation types across the ELTD1 significant gene.

DCDC1

Figure S10.  This figure depicts the distribution of mutations and mutation types across the DCDC1 significant gene.

COL11A1

Figure S11.  This figure depicts the distribution of mutations and mutation types across the COL11A1 significant gene.

OR2G6

Figure S12.  This figure depicts the distribution of mutations and mutation types across the OR2G6 significant gene.

ASCL4

Figure S13.  This figure depicts the distribution of mutations and mutation types across the ASCL4 significant gene.

COL22A1

Figure S14.  This figure depicts the distribution of mutations and mutation types across the COL22A1 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)
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