Mutation Analysis (MutSigCV v0.6)
Kidney Renal Clear Cell Carcinoma (Primary solid tumor)
22 February 2013  |  analyses__2013_02_22
Maintainer Information
Citation Information
doi:10.7908/C1PG1PXV
Maintained by Dan DiCara (Broad Institute)
Cite as Broad Institute TCGA Genome Data Analysis Center (2013): Mutation Analysis (MutSigCV v0.6). Broad Institute of MIT and Harvard. doi:10.7908/C1PG1PXV
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 v0.6 was used to generate the results found in this report.

  • Working with individual set: KIRC-TP

  • Number of patients in set: 297

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: KIRC-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: 4. 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
VHL 90250 28493 151790 140 139 91 5 2 13 1.1 0 710 0.33 0
PBRM1 1197433 310826 1687298 110 108 106 1 7 20 0.82 1.9e-15 490 0.3 1.7e-11
BAP1 489516 147172 815975 28 27 25 1 2 20 0.78 1e-14 120 0.28 6.3e-11
SETD2 1484839 398175 1135969 37 35 36 1 4 7 0.96 4.5e-10 140 0.29 2e-06
PTEN 278992 66996 435874 10 9 10 0 3 20 0.91 0.000082 41 0.27 0.3
KDM5C 891702 265950 774079 18 18 18 0 1 20 1.2 0.00017 77 0.3 0.53
EBPL 109536 30572 183047 8 6 4 0 0 20 0.74 0.00066 23 0.26 1
ZFY 221253 54626 85526 3 3 3 0 0 7 0 0.0009 15 0.24 1
C5orf13 51046 13365 245300 3 3 3 0 6 20 0.76 0.0015 16 0.25 1
ZNF653 365809 108070 355701 4 4 4 0 0 2 0 0.002 15 0.24 1
SEPT3 279767 74155 615578 3 3 3 0 0 2 0 0.0045 14 0.24 1
SFRS15 796585 242276 893042 9 9 9 0 1 2 0.34 0.0057 33 0.28 1
GAGE12J 19880 5327 76255 2 2 2 0 1 14 0.76 0.0062 9 0.19 1
CR1 1108753 310536 1489703 10 10 7 0 2 7 0.44 0.0067 40 0.28 1
TP53 280665 81972 378936 7 6 7 1 1 4 0.45 0.0068 22 0.26 1
MS4A14 472363 130124 276899 5 5 5 0 0 1 0 0.008 17 0.25 1
C13orf15 56651 15128 193017 2 2 2 0 1 20 0.45 0.011 10 0.22 1
TLCD1 178775 53738 316162 2 2 2 0 0 2 0 0.011 8 0.2 1
COL2A1 895897 307616 2270523 6 6 5 0 1 5 0.12 0.012 19 0.28 1
C1orf159 52144 17276 149250 2 2 2 0 1 20 0.65 0.013 11 0.22 1
FAM200A 46237 12158 31086 4 3 4 0 0 20 0.92 0.015 12 0.23 1
TSGA10IP 268485 83635 195160 4 4 3 0 2 20 0.4 0.016 17 0.25 1
GFRA4 28600 10913 36653 1 1 1 0 0 20 0.57 0.016 6.9 0.18 1
CCDC75 95432 21125 144203 2 2 2 1 1 20 0.84 0.019 13 0.24 1
MESP1 34053 12025 68269 1 1 1 0 0 2 0 0.019 4.6 0.12 1
UXT 95957 27122 156095 2 2 2 0 0 20 0.39 0.022 10 0.21 1
FCN1 221246 64727 486356 3 3 3 0 0 1 0 0.025 10 0.23 1
CPLX2 54681 13833 46649 2 2 2 0 1 20 0.58 0.025 8.4 0.19 1
MRPL9 160342 47204 365272 3 3 3 0 0 20 0.49 0.026 12 0.25 1
SDR16C5 221486 60885 359567 4 4 4 0 0 3 0.53 0.027 17 0.25 1
TTC3 1507805 386005 2390885 5 5 5 0 1 2 0.076 0.028 19 0.26 1
SPCS1 76101 20398 189220 2 2 2 0 1 20 0.52 0.036 7.5 0.19 1
C3orf45 204505 66319 259045 3 3 2 0 0 20 0.51 0.037 14 0.24 1
UBE2D1 104152 27008 251905 2 2 2 1 0 20 0.92 0.038 12 0.23 1
PCP4L1 43122 11880 65306 2 2 2 0 0 20 1.4 0.039 10 0.22 1
VHL

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

PBRM1

Figure S2.  This figure depicts the distribution of mutations and mutation types across the PBRM1 significant gene.

BAP1

Figure S3.  This figure depicts the distribution of mutations and mutation types across the BAP1 significant gene.

SETD2

Figure S4.  This figure depicts the distribution of mutations and mutation types across the SETD2 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

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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