Kidney Renal Clear Cell Carcinoma: Mutation Analysis (MutSig vS2N)
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

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: 19. 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 254033 7 2 122 95 7.1e-250 1.3e-245
VHL 17867 1 6 180 102 5.3e-179 5e-175
KIAA1731 2520 2 1 5 0 1.2e-160 7.8e-157
ZNF717 280 2 2 4 3 4.8e-123 2.2e-119
BAP1 94416 2 1 34 18 2.8e-82 1.1e-78
POTED 20730 0 0 6 0 8.3e-66 2.6e-62
FAM200A 9687 0 0 5 1 1.5e-42 4.1e-39
SETD2 304922 4 2 46 25 6e-42 1.4e-38
PTEN 64169 3 4 24 12 4.4e-23 9.3e-20
KDM5C 169452 1 1 22 13 1.8e-22 3.4e-19
CT47B1 19880 0 1 5 0 4e-21 6.9e-18
ANKRD30B 67480 4 1 7 0 9.4e-11 1.5e-07
PIK3CA 172749 3 2 19 1 3.6e-07 0.00052
TP53 51534 1 5 19 2 1.3e-06 0.0017
VCX2 6415 0 0 5 2 5.1e-06 0.0064
EBPL 24540 0 0 8 0 6.7e-06 0.0079
CR1 213863 2 0 12 6 0.000015 0.017
MUC17 555164 0 3 22 0 0.000027 0.029
WDR52 164569 6 1 10 0 0.000088 0.087
MTOR 418149 6 3 28 0 0.0002 0.19
UNC80 39544 4 2 6 0 0.00037 0.33
XPOT 151890 1 3 9 1 0.00044 0.36
DNAH6 68369 4 2 6 0 0.00044 0.36
MUC16 1887211 8 18 46 1 0.00047 0.37
COL11A1 199636 6 1 10 6 0.003 1
HSPA8 95168 0 3 7 2 0.0039 1
NBPF10 105560 47 5 25 0 0.0098 1
GRIN2B 221549 5 2 11 0 0.01 1
SMC3 196040 11 2 7 1 0.012 1
DNHD1 181401 2 3 9 1 0.013 1
ACSBG2 104855 2 1 5 0 0.018 1
DNAH9 653991 7 1 18 2 0.021 1
ZNF799 92972 2 1 7 0 0.023 1
PRPF8 358306 1 0 9 0 0.023 1
COL2A1 111657 1 0 7 0 0.024 1
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)