Ovarian Serous Cystadenocarcinoma: 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: OV-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

- MAF used for this analysis:OV-TP.final_analysis_set.maf

- Significantly mutated genes (q ≤ 0.1): 51

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: 51. 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
--- | --- | --- | --- | --- | --- | --- | ---
TP53 | 39816 | 0 | 2 | 247 | 101 | 0 | 0
BRCA1 | 224044 | 0 | 0 | 11 | 11 | 9.4e-108 | 8.9e-104
BRCA2 | 421544 | 0 | 0 | 11 | 10 | 8.3e-40 | 5.2e-36
CDK12 | 147256 | 0 | 0 | 8 | 5 | 4.6e-23 | 2.2e-19
CYP11B1 | 52456 | 0 | 0 | 6 | 0 | 2.9e-22 | 1.1e-18
C9orf171 | 28440 | 0 | 0 | 5 | 1 | 3.6e-21 | 1.1e-17
PXN | 40764 | 0 | 0 | 5 | 0 | 5.5e-15 | 1.5e-11
RB1CC1 | 194340 | 0 | 1 | 6 | 5 | 8.8e-13 | 2.1e-09
TBP | 36024 | 0 | 0 | 4 | 4 | 1.6e-12 | 3.3e-09
OTOF | 206348 | 0 | 0 | 8 | 2 | 6.1e-12 | 1.1e-08
ADAMTS14 | 103964 | 0 | 0 | 6 | 0 | 1.4e-11 | 2.3e-08
NF1 | 471788 | 0 | 0 | 14 | 9 | 2.2e-10 | 3.5e-07
NBPF16 | 44240 | 0 | 0 | 4 | 4 | 2.4e-10 | 3.5e-07
KIT | 119132 | 0 | 1 | 6 | 1 | 3.3e-10 | 4.4e-07
RASAL1 | 66044 | 0 | 1 | 6 | 2 | 5.7e-10 | 6.8e-07
ADAMTS16 | 122292 | 0 | 0 | 6 | 1 | 5.8e-10 | 6.8e-07
SON | 252168 | 0 | 0 | 8 | 4 | 6.6e-10 | 7.4e-07
HYDIN | 412696 | 0 | 2 | 9 | 0 | 7.6e-10 | 8e-07
CRTAC1 | 66992 | 0 | 1 | 5 | 1 | 2.1e-09 | 2.1e-06
FAT1 | 514448 | 0 | 1 | 8 | 0 | 2.4e-09 | 2.3e-06
L3MBTL2 | 71100 | 0 | 0 | 5 | 0 | 6.6e-09 | 6e-06
GPRIN3 | 74260 | 0 | 0 | 5 | 0 | 1.5e-08 | 0.000013
DST | 777992 | 0 | 2 | 13 | 2 | 6.5e-08 | 0.000053
PLB1 | 163056 | 0 | 0 | 6 | 0 | 1.2e-07 | 0.000093
GRLF1 | 167796 | 0 | 1 | 6 | 3 | 1.9e-07 | 0.00014
TOP2A | 167480 | 0 | 1 | 6 | 4 | 5.1e-07 | 0.00037
DIDO1 | 188336 | 0 | 1 | 6 | 0 | 1e-06 | 0.0007
HKDC1 | 103332 | 0 | 0 | 5 | 1 | 2.4e-06 | 0.0016
SALL4 | 103648 | 0 | 0 | 5 | 1 | 2.4e-06 | 0.0016
IRS1 | 106176 | 0 | 0 | 5 | 1 | 3.3e-06 | 0.0021
IRS4 | 107124 | 0 | 0 | 5 | 1 | 3.7e-06 | 0.0022
HUWE1 | 427232 | 0 | 1 | 8 | 2 | 3.8e-06 | 0.0022
NCAN | 107440 | 0 | 0 | 5 | 0 | 3.9e-06 | 0.0022
SLIT3 | 155788 | 0 | 0 | 6 | 1 | 4.3e-06 | 0.0024
PLXNA4 | 223096 | 0 | 0 | 6 | 1 | 8.6e-06 | 0.0047

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.

- Analysis Results (MD5 checksum)

- Auxiliary Data (MD5 checksum)

- MAGE-TAB File (MD5 checksum)

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