Uterine Corpus Endometrioid 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: UCEC

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:UCEC.final_analysis_set.maf

- Significantly mutated genes (q ≤ 0.1): 55

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: 55. 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
--- | --- | --- | --- | --- | --- | --- | ---
C14orf38 | 248 | 0 | 2 | 13 | 1 | 0 | 0
ZNF860 | 496 | 0 | 2 | 8 | 0 | 9.980126e-322 | 9.899998e-318
PTEN | 39928 | 0 | 5 | 255 | 152 | 3e-267 | 1.9e-263
KRAS | 25544 | 0 | 2 | 53 | 0 | 5.9e-64 | 2.3e-60
GOLGA6L1 | 1240 | 0 | 1 | 6 | 2 | 6.1e-64 | 2.3e-60
SRRM5 | 1984 | 0 | 2 | 7 | 0 | 8.7e-61 | 2.7e-57
PIK3R1 | 73160 | 0 | 2 | 118 | 96 | 3.2e-46 | 8.6e-43
ARID1A | 144336 | 0 | 5 | 107 | 92 | 2.7e-42 | 6.4e-39
HMGXB3 | 1984 | 0 | 2 | 6 | 0 | 2.2e-40 | 4.7e-37
LRCH2 | 27280 | 0 | 4 | 22 | 3 | 1e-31 | 2e-28
FAM71E2 | 3224 | 0 | 2 | 6 | 0 | 3.5e-25 | 6e-22
PIK3CA | 104408 | 0 | 3 | 172 | 9 | 6.5e-24 | 1e-20
FAM178B | 8928 | 0 | 1 | 9 | 2 | 9e-24 | 1.3e-20
GOLGA8A | 6944 | 0 | 1 | 6 | 0 | 2.5e-21 | 3.3e-18
DPCR1 | 21576 | 0 | 3 | 14 | 5 | 4.1e-21 | 5.1e-18
SLC48A1 | 1984 | 0 | 0 | 5 | 1 | 4.4e-21 | 5.2e-18
RNPC3 | 3968 | 0 | 1 | 6 | 1 | 1.3e-20 | 1.4e-17
CTCF | 62992 | 0 | 1 | 52 | 33 | 1.1e-19 | 1.1e-16
VWA5B2 | 8928 | 0 | 3 | 8 | 0 | 7.2e-19 | 7.1e-16
PARG | 14880 | 0 | 2 | 10 | 3 | 1.4e-17 | 1.3e-14
DNAH12 | 43152 | 0 | 6 | 54 | 9 | 4.6e-16 | 4.1e-13
XKR5 | 14136 | 0 | 2 | 9 | 2 | 2.7e-15 | 2.4e-12
FSIP2 | 160952 | 0 | 5 | 30 | 4 | 4.1e-13 | 3.4e-10
CTNNB1 | 62992 | 0 | 7 | 80 | 0 | 1e-12 | 7.8e-10
DNAH6 | 39928 | 0 | 6 | 42 | 10 | 2.3e-12 | 1.8e-09
TP53 | 31248 | 0 | 2 | 74 | 17 | 1.4e-11 | 1e-08
ATAD3C | 3968 | 0 | 2 | 5 | 0 | 6e-11 | 4.2e-08
CDR2L | 8432 | 0 | 1 | 6 | 1 | 4.2e-10 | 2.9e-07
CYLC1 | 54312 | 0 | 2 | 27 | 4 | 1.2e-09 | 7.7e-07
NXF2 | 19344 | 0 | 3 | 8 | 0 | 4.2e-09 | 2.5e-06
NXF2B | 19344 | 0 | 3 | 8 | 0 | 4.2e-09 | 2.5e-06
CDHR4 | 8184 | 0 | 4 | 8 | 1 | 3.6e-08 | 0.000021
FAM200A | 5704 | 0 | 2 | 5 | 0 | 7.6e-08 | 0.000043
LRRC8D | 83328 | 0 | 3 | 23 | 2 | 4.1e-07 | 0.00023
MRC1 | 62000 | 0 | 0 | 13 | 2 | 4.8e-07 | 0.00026

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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