Mutation Analysis (MutSigCV v0.9)
Kidney Renal Clear Cell Carcinoma (Primary solid tumor)
21 April 2013  |  analyses__2013_04_21
Maintainer Information
Citation Information
doi:10.7908/C1C24TD0
Maintained by Dan DiCara (Broad Institute)
Cite as Broad Institute TCGA Genome Data Analysis Center (2013): Kidney Renal Clear Cell Carcinoma (Primary solid tumor cohort) - 21 April 2013: Mutation Analysis (MutSigCV v0.9). Broad Institute of MIT and Harvard. doi:10.7908/C1C24TD0
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: 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: 6. 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
PBRM1 1197433 310826 1687298 110 108 106 1 7 20 0.82 0 510 0.21 0
VHL 90250 28493 151790 140 139 91 5 2 13 1.1 1e-15 740 0.26 9.1e-12
BAP1 489516 147172 815975 28 27 25 1 2 20 0.78 6.2e-15 120 0.21 3.2e-11
SETD2 1484839 398175 1135969 37 35 36 1 4 7 0.96 7e-15 140 0.22 3.2e-11
KDM5C 891702 265950 774079 18 18 18 0 1 20 1.2 1.1e-07 81 0.21 0.00041
PTEN 278992 66996 435874 10 9 10 0 3 20 0.91 1.1e-06 43 0.21 0.0033
EBPL 109536 30572 183047 8 6 4 0 0 20 0.74 0.000089 23 0.19 0.23
C5orf13 51046 13365 245300 3 3 3 0 6 20 0.76 0.00027 17 0.18 0.62
CR1 1108753 310536 1489703 10 10 7 0 2 7 0.44 0.0013 41 0.21 1
MTOR 2045413 578183 3743376 26 24 22 2 6 6 0.73 0.0016 63 0.28 1
GAGE12J 19880 5327 76255 2 2 2 0 1 14 0.76 0.0031 9.1 0.14 1
FAM200A 46237 12158 31086 4 3 4 0 0 20 0.92 0.0041 12 0.17 1
TSGA10IP 268485 83635 195160 4 4 3 0 2 20 0.4 0.0044 18 0.2 1
CCDC75 95432 21125 144203 2 2 2 1 1 20 0.84 0.0048 13 0.31 1
C13orf15 56651 15128 193017 2 2 2 0 1 20 0.45 0.0049 11 0.16 1
C1orf159 52144 17276 149250 2 2 2 0 1 20 0.65 0.0053 11 0.16 1
SLC36A1 333234 102168 596237 6 6 6 3 1 19 1 0.0067 25 0.2 1
UXT 95957 27122 156095 2 2 2 0 0 20 0.39 0.0075 11 0.29 1
GFRA4 28600 10913 36653 1 1 1 0 0 20 0.57 0.0081 7.2 0.12 1
TSPAN19 97214 23779 129222 4 4 4 0 0 13 2.4 0.0086 19 0.17 1
UBE2D1 104152 27008 251905 2 2 2 1 0 20 0.92 0.0096 13 0.16 1
GATA2 265991 84215 167429 4 4 4 0 0 19 0.79 0.0098 19 0.19 1
TP53 280665 81972 378936 7 6 7 1 1 4 0.45 0.01 21 0.19 1
OPTC 228638 72556 339639 4 4 4 2 1 20 0.75 0.01 17 0.18 1
PCP4L1 43122 11880 65306 2 2 2 0 0 20 1.4 0.013 11 0.16 1
GSPT1 314088 85056 545450 4 4 4 1 3 8 0.57 0.013 18 0.19 1
TPTE2 386295 100013 1166619 8 7 8 1 3 14 1.1 0.014 25 0.19 1
CPLX2 54681 13833 46649 2 2 2 0 1 20 0.58 0.014 8.3 0.25 1
C3orf45 204505 66319 259045 3 3 2 0 0 20 0.51 0.015 14 0.18 1
SPCS1 76101 20398 189220 2 2 2 0 1 20 0.52 0.015 7.8 0.13 1
B2M 85795 23760 199152 2 2 2 0 0 20 0.83 0.016 11 0.18 1
TPRX1 126572 46515 35831 2 2 2 0 0 20 0.55 0.017 11 0.16 1
C7orf23 85220 23760 266233 2 2 2 0 1 20 0.52 0.018 8 0.15 1
ADAMTSL5 177193 56423 171701 3 3 3 0 1 18 0.59 0.018 13 0.17 1
MRPL9 160342 47204 365272 3 3 3 0 0 20 0.49 0.018 12 0.17 1
PBRM1

Figure S1.  This figure depicts the distribution of mutations and mutation types across the PBRM1 significant gene.

VHL

Figure S2.  This figure depicts the distribution of mutations and mutation types across the VHL 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.

KDM5C

Figure S5.  This figure depicts the distribution of mutations and mutation types across the KDM5C significant gene.

PTEN

Figure S6.  This figure depicts the distribution of mutations and mutation types across the PTEN 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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