Mutation Analysis (MutSigCV v0.9)
Breast Invasive Carcinoma (Primary solid tumor)
23 May 2013  |  analyses__2013_05_23
Maintainer Information
Citation Information
doi:10.7908/C1DF6P7Z
Maintained by Dan DiCara (Broad Institute)
Cite as Broad Institute TCGA Genome Data Analysis Center (2013): Mutation Analysis (MutSigCV v0.9). Broad Institute of MIT and Harvard. doi:10.7908/C1DF6P7Z
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: 772

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
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).

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

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

  • 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: 67. 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
CDH1 1508488 448532 248428 56 55 49 2 0 20 0.6 0 320 0.51 0
GATA3 655428 209212 57440 85 81 50 1 0 20 1.2 0 530 0.52 0
MLL3 8858700 2516720 890320 60 56 58 1 0 13 0.7 0 250 0.5 0
PTEN 751928 180648 124932 30 29 27 0 0 20 1.1 0 170 0.5 0
RBMX 762736 161348 180936 13 13 2 1 0 20 0.86 0 85 0.5 0
RUNX1 593668 186052 140010 26 25 23 3 0 13 1 0 140 0.51 0
TP53 729540 213072 147908 261 257 145 3 0 4 2.4 0 1100 0.64 0
ZNF384 1032164 299536 121342 14 14 1 1 0 20 1 0 91 0.49 0
MAP3K1 2464224 700204 267814 85 57 79 3 0 9 1.4 1e-15 300 0.51 2e-12
NR1H2 688624 207668 96212 18 18 5 0 0 20 0.95 1.9e-15 110 0.5 3.4e-12
NCOA3 2646416 714872 296534 30 29 12 0 0 20 1.6 2.4e-15 150 0.5 3.9e-12
MAP2K4 683992 176788 211092 32 32 28 0 0 10 1.7 2.6e-15 170 0.5 3.9e-12
MEF2A 762736 220792 107700 14 14 3 0 0 20 1.8 3.7e-15 87 0.5 5.1e-12
NCOR2 3104984 944928 448750 29 29 7 1 0 20 0.93 6.3e-15 160 0.5 8.2e-12
PIK3CA 2006428 513380 284328 287 261 49 4 0 20 1 1.2e-14 900 0.6 1.4e-11
AOAH 1127892 270200 292944 19 19 1 3 0 20 0.69 1.3e-14 120 0.51 1.4e-11
CBFB 314976 79516 64620 16 16 16 1 0 20 0.62 1.5e-14 81 0.5 1.6e-11
PIK3R1 1439008 369788 247710 21 21 20 1 0 20 1.2 2.2e-14 110 0.51 2.2e-11
ATN1 1721560 608336 95494 18 17 9 1 0 20 0.83 1.8e-13 88 0.49 1.7e-10
CTCF 1361808 348944 144318 18 18 16 3 0 20 1.2 1.3e-12 85 0.5 1.2e-09
AKD1 1930000 484816 379104 19 19 10 0 0 3 0.81 2e-12 96 0.5 1.8e-09
RB1 2198656 579772 348948 16 14 15 1 0 20 0.56 8.4e-12 78 0.5 7e-09
CCDC144NL 314976 84148 43798 8 8 3 0 0 20 1.4 1.3e-10 52 0.49 1.1e-07
PHLDA1 377508 108080 8616 9 9 5 0 0 20 0.99 5.9e-10 49 0.49 4.5e-07
NCOR1 4400400 1283836 627532 32 31 32 2 0 1 0.75 7.4e-10 140 0.5 5.4e-07
FOXA1 629952 184508 30874 15 15 15 0 0 20 1.9 1.3e-09 65 0.53 8.8e-07
ZFP36L1 589808 189140 31592 10 10 10 0 0 20 1.3 1.6e-09 57 0.49 1.1e-06
TBX3 776632 220792 89750 18 18 17 0 0 1 0 1.2e-08 92 0.52 7.5e-06
TBL1XR1 823724 224652 127086 11 9 9 0 0 20 1.1 1.7e-08 53 0.49 0.000011
RPGR 1792584 463972 234068 14 14 13 0 0 11 0.78 3.9e-08 64 0.49 0.000024
MAP3K4 2897316 777404 414286 18 18 5 2 0 5 1.6 4.7e-08 99 0.51 0.000028
AQP7 585948 187596 84724 8 8 5 1 0 14 0.76 6.5e-08 47 0.48 0.000037
DNAH12 834532 216932 140728 12 12 12 2 0 20 0.73 1.1e-07 46 0.49 0.000059
TPRX1 319608 116572 9334 8 7 4 0 0 20 1.4 1.4e-07 39 0.47 0.000074
CDKN1B 358980 99588 124932 7 7 6 0 0 20 2.2 1.9e-07 47 0.48 0.0001
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

This is an experimental feature. The full results of the analysis summarized in this report can be downloaded from the TCGA Data Coordination Center.

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