Mutation Analysis (MutSigCV v0.9)
Breast Invasive Carcinoma (Primary solid tumor)
21 August 2015  |  analyses__2015_08_21
Maintainer Information
Citation Information
doi:10.7908/C13J3C40
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/C13J3C40
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: BRCA-TP

  • Number of patients in set: 988

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:BRCA-TP.final_analysis_set.maf

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

  • Significantly mutated genes (q ≤ 0.1): 40

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: BRCA-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: 40. 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
PTEN 962090 231138 175506 37 36 33 0 0 20 0.61 0 200 0.87 0
TP53 933660 272688 204824 305 302 161 4 0 4 1.6 0 1300 0.94 0
PIK3CA 2567890 657032 399432 355 320 53 6 0 20 1.4 3e-15 1000 1 1.4e-11
GATA3 838770 267736 80348 101 97 56 2 0 20 1.2 3.1e-15 620 0.86 1.4e-11
CDH1 1930552 574028 348772 110 108 90 1 1 20 0.83 4.7e-15 630 0.99 1.5e-11
RUNX1 759778 238108 196803 32 31 23 2 0 13 0.96 4.9e-15 170 0.96 1.5e-11
CBFB 403230 101812 91860 23 23 21 1 0 20 0.9 8.2e-15 130 0.89 2.1e-11
MAP3K1 3153762 896134 375727 100 72 88 1 0 9 1 9.1e-15 390 0.98 2.1e-11
MAP2K4 875392 226264 296010 32 32 28 0 1 10 1.7 1.3e-14 170 0.86 2.7e-11
TBX3 993712 282490 127511 27 27 26 1 0 1 0.44 2e-14 140 0.87 3.7e-11
NCOR1 5631684 1643068 884710 41 40 39 2 0 1 0.32 7.4e-13 160 0.93 1.2e-09
RB1 2813992 742030 501072 22 19 21 3 0 20 0.87 7.8e-13 100 0.92 1.2e-09
FOXA1 805962 236054 42763 24 23 16 0 0 20 1.5 1.3e-12 88 2 1.8e-09
GPS2 876362 253916 203532 10 10 10 1 0 20 0.99 1.9e-10 66 0.84 2.5e-07
CTCF 1742838 446576 204861 17 17 15 3 0 20 0.96 6.4e-10 80 0.82 7.8e-07
CDKN1B 459456 127458 170292 12 10 11 1 0 20 2.2 5.5e-09 63 0.82 6.2e-06
TBL1XR1 1054076 287478 178905 12 10 10 0 0 20 1 1.4e-07 56 0.88 0.00015
HIST1H3B 303322 101764 24522 11 11 11 2 0 20 1.5 4.2e-07 45 0.84 0.00042
ZFP36L1 754844 242066 45128 8 8 8 0 1 20 0.89 6.1e-07 49 0.82 0.00058
DNAH12 1068082 277640 199198 19 16 19 3 2 20 1.3 7.5e-07 55 0.82 0.00068
TMEM151B 160056 49400 22198 6 6 6 0 0 20 1 2.4e-06 28 0.94 0.0021
MYH9 4581782 1230168 814449 21 19 20 5 0 20 0.64 2.5e-06 81 0.86 0.0021
CASP8 1438546 336908 214887 10 10 10 1 2 20 0.62 5.4e-06 46 0.87 0.0043
ARID1A 4413420 1300214 380578 28 27 26 3 0 2 1.1 9.1e-06 120 0.91 0.007
MYB 1796172 490048 359321 12 12 12 0 0 20 1.4 0.000011 62 0.81 0.0082
FAM86B1 250892 80010 22754 7 6 6 1 5 20 0.99 0.000016 28 0.82 0.011
OR2T35 232096 74070 1165 4 4 2 0 0 20 0.89 2e-05 26 0.84 0.014
GRHL2 1523490 385320 330070 9 9 9 0 0 20 0.56 0.000029 42 0.84 0.019
PIK3R1 1841698 473264 350187 16 14 15 2 1 20 1.4 0.000031 61 0.84 0.019
GPRIN2 929666 316148 10480 11 11 7 2 0 20 1.1 0.000044 41 0.82 0.027
HMGB3 484078 111638 79902 6 6 4 0 0 12 0.9 0.000061 31 0.92 0.036
AQP12A 297418 104740 29652 7 7 4 0 0 20 1.2 0.000098 27 0.83 0.056
COL6A5 1336632 351514 85032 26 21 26 12 0 7 2.6 0.00011 67 0.84 0.058
NF1 9299368 2606410 1203926 30 28 29 3 0 0 0.39 0.00011 120 0.87 0.059
ANKRD12 4840368 1206378 240923 19 18 19 1 0 17 0.8 0.00011 73 0.86 0.059
PTEN

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

TP53

Figure S2.  This figure depicts the distribution of mutations and mutation types across the TP53 significant gene.

PIK3CA

Figure S3.  This figure depicts the distribution of mutations and mutation types across the PIK3CA significant gene.

GATA3

Figure S4.  This figure depicts the distribution of mutations and mutation types across the GATA3 significant gene.

CDH1

Figure S5.  This figure depicts the distribution of mutations and mutation types across the CDH1 significant gene.

RUNX1

Figure S6.  This figure depicts the distribution of mutations and mutation types across the RUNX1 significant gene.

CBFB

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

MAP3K1

Figure S8.  This figure depicts the distribution of mutations and mutation types across the MAP3K1 significant gene.

MAP2K4

Figure S9.  This figure depicts the distribution of mutations and mutation types across the MAP2K4 significant gene.

TBX3

Figure S10.  This figure depicts the distribution of mutations and mutation types across the TBX3 significant gene.

NCOR1

Figure S11.  This figure depicts the distribution of mutations and mutation types across the NCOR1 significant gene.

RB1

Figure S12.  This figure depicts the distribution of mutations and mutation types across the RB1 significant gene.

FOXA1

Figure S13.  This figure depicts the distribution of mutations and mutation types across the FOXA1 significant gene.

GPS2

Figure S14.  This figure depicts the distribution of mutations and mutation types across the GPS2 significant gene.

CTCF

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

CDKN1B

Figure S16.  This figure depicts the distribution of mutations and mutation types across the CDKN1B significant gene.

TBL1XR1

Figure S17.  This figure depicts the distribution of mutations and mutation types across the TBL1XR1 significant gene.

HIST1H3B

Figure S18.  This figure depicts the distribution of mutations and mutation types across the HIST1H3B significant gene.

ZFP36L1

Figure S19.  This figure depicts the distribution of mutations and mutation types across the ZFP36L1 significant gene.

DNAH12

Figure S20.  This figure depicts the distribution of mutations and mutation types across the DNAH12 significant gene.

TMEM151B

Figure S21.  This figure depicts the distribution of mutations and mutation types across the TMEM151B significant gene.

MYH9

Figure S22.  This figure depicts the distribution of mutations and mutation types across the MYH9 significant gene.

ARID1A

Figure S23.  This figure depicts the distribution of mutations and mutation types across the ARID1A significant gene.

MYB

Figure S24.  This figure depicts the distribution of mutations and mutation types across the MYB significant gene.

FAM86B1

Figure S25.  This figure depicts the distribution of mutations and mutation types across the FAM86B1 significant gene.

OR2T35

Figure S26.  This figure depicts the distribution of mutations and mutation types across the OR2T35 significant gene.

GRHL2

Figure S27.  This figure depicts the distribution of mutations and mutation types across the GRHL2 significant gene.

PIK3R1

Figure S28.  This figure depicts the distribution of mutations and mutation types across the PIK3R1 significant gene.

GPRIN2

Figure S29.  This figure depicts the distribution of mutations and mutation types across the GPRIN2 significant gene.

HMGB3

Figure S30.  This figure depicts the distribution of mutations and mutation types across the HMGB3 significant gene.

AQP12A

Figure S31.  This figure depicts the distribution of mutations and mutation types across the AQP12A significant gene.

COL6A5

Figure S32.  This figure depicts the distribution of mutations and mutation types across the COL6A5 significant gene.

NF1

Figure S33.  This figure depicts the distribution of mutations and mutation types across the NF1 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)
Copyright © 2015 Broad Institute TCGA GDAC as part of the TCGA Research Network. All rights reserved.
Made with Nozzle