Kidney Renal Clear Cell Carcinoma: Mutation Analysis (MutSig vS2N)
(primary solid tumor cohort)
Maintained by Dan DiCara (Broad Institute)
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. MutSig vS2N was used to generate the results found in this report.

  • Working with individual set: KIRC-TP

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
Significantly Mutated Genes

Column Descriptions:

  • N = number of sequenced bases in this gene across the individual set

  • nnon = number of (nonsilent) mutations in this gene across the individual set

  • nnull = number of (nonsilent) null mutations in this gene across the individual set

  • 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: 11. 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 N nflank nsil nnon nnull p q
PBRM1 184917 7 1 110 88 9.6e-288 1.8e-283
VHL 13049 2 5 140 86 2.2e-261 2.1e-257
KIAA1731 2502 2 1 5 0 9.4e-145 5.9e-141
BAP1 69308 2 1 28 16 1.6e-83 7.4e-80
SETD2 222244 4 1 37 24 6.5e-48 2.4e-44
KDM5C 121556 1 0 18 12 3.6e-26 1.1e-22
PTEN 46149 3 0 10 6 7.2e-15 1.9e-11
EBPL 17820 0 0 8 0 4.4e-07 0.001
MUC17 403288 0 3 18 0 2.9e-06 0.006
WDR52 119653 6 1 10 0 8.3e-06 0.016
TP53 37422 1 1 7 1 0.000014 0.025
UNC80 28790 4 1 5 0 7e-05 0.11
MTOR 303793 6 2 26 0 0.000078 0.11
CR1 154851 2 0 10 5 0.0005 0.67
ANKRD30B 66998 4 1 5 0 0.00057 0.72
MUC2 174261 1 2 11 1 0.00083 0.98
GRIN2B 160955 5 1 11 0 0.0035 1
ZNF799 67438 2 1 8 1 0.004 1
SFRS15 101239 1 0 9 3 0.0053 1
ACSBG2 76291 2 1 5 0 0.0062 1
DNAH6 50319 4 2 5 0 0.009 1
MUC16 1369897 8 10 36 1 0.0094 1
NBPF10 104806 47 5 25 0 0.0098 1
HSPA8 69182 0 3 6 2 0.012 1
DNAH9 474903 7 0 17 3 0.013 1
PIK3CA 125593 3 0 10 1 0.015 1
MUC4 190073 8 17 63 3 0.018 1
MCM7 81637 0 0 6 1 0.02 1
COL11A1 145416 6 1 8 5 0.021 1
ABCB1 161252 5 0 9 2 0.025 1
POTEC 53098 5 3 6 0 0.029 1
CNTNAP4 127976 4 0 9 0 0.03 1
COL5A3 107975 2 1 8 3 0.031 1
TPTE2 65858 3 1 8 1 0.034 1
SPEN 331749 7 2 15 2 0.035 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.

KIAA1731

Figure S3.  This figure depicts the distribution of mutations and mutation types across the KIAA1731 significant gene.

BAP1

Figure S4.  This figure depicts the distribution of mutations and mutation types across the BAP1 significant gene.

SETD2

Figure S5.  This figure depicts the distribution of mutations and mutation types across the SETD2 significant gene.

KDM5C

Figure S6.  This figure depicts the distribution of mutations and mutation types across the KDM5C significant gene.

PTEN

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

EBPL

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

MUC17

Figure S9.  This figure depicts the distribution of mutations and mutation types across the MUC17 significant gene.

WDR52

Figure S10.  This figure depicts the distribution of mutations and mutation types across the WDR52 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)