Cervical Squamous Cell Carcinoma: Mutation Analysis (MutSig)
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: CESC

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:CESC.final_analysis_set.maf

- Significantly mutated genes (q ≤ 0.1): 15

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: 15. 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
--- | --- | --- | --- | --- | --- | --- | ---
PIK3CA | 15190 | 1 | 0 | 11 | 0 | 2.2e-226 | 4.2e-222
NFE2L2 | 7740 | 0 | 0 | 6 | 1 | 4.3e-36 | 4.1e-32
DNAJB1 | 4013 | 0 | 0 | 5 | 1 | 4.8e-17 | 3e-13
FLG | 39325 | 0 | 0 | 7 | 1 | 7.2e-12 | 3.4e-08
TEX15 | 40166 | 0 | 0 | 7 | 0 | 6.2e-09 | 0.000023
DNMBP | 18959 | 0 | 0 | 5 | 2 | 1.4e-08 | 0.000044
MYH9 | 25514 | 0 | 1 | 6 | 2 | 1e-07 | 0.00027
MLL3 | 58314 | 0 | 2 | 10 | 7 | 1.6e-06 | 0.0037
CHD8 | 25927 | 0 | 0 | 5 | 0 | 1.8e-06 | 0.0037
ARID1A | 20952 | 0 | 0 | 6 | 4 | 3.6e-06 | 0.0067
MLL2 | 44628 | 1 | 2 | 7 | 5 | 4.3e-06 | 0.0074
YTHDC1 | 8765 | 0 | 0 | 4 | 0 | 0.000015 | 0.023
BRWD1 | 31388 | 0 | 0 | 5 | 0 | 0.000018 | 0.026
PCLO | 59036 | 0 | 0 | 7 | 1 | 0.000029 | 0.039
ODZ1 | 35119 | 0 | 0 | 5 | 0 | 0.000057 | 0.072
RYR2 | 59155 | 0 | 1 | 8 | 1 | 0.0002 | 0.24
SYNE2 | 96789 | 1 | 0 | 9 | 1 | 0.00024 | 0.26
APOB | 63231 | 0 | 0 | 7 | 0 | 0.00034 | 0.36
PRKDC | 46106 | 1 | 1 | 5 | 1 | 0.00058 | 0.58
SPEN | 40212 | 0 | 0 | 8 | 3 | 0.0009 | 0.85
AGBL5 | 10205 | 0 | 4 | 6 | 2 | 0.0011 | 1
SRRM2 | 26028 | 0 | 0 | 5 | 1 | 0.0014 | 1
FAT2 | 53153 | 0 | 2 | 5 | 1 | 0.0016 | 1
ARFGEF2 | 23705 | 1 | 1 | 4 | 0 | 0.0059 | 1
NOTCH1 | 19555 | 0 | 2 | 6 | 1 | 0.0065 | 1
PTPN13 | 27104 | 0 | 1 | 5 | 0 | 0.015 | 1
CELSR2 | 29059 | 0 | 1 | 6 | 1 | 0.021 | 1
SRCAP | 29937 | 0 | 0 | 7 | 0 | 0.038 | 1
PLEC | 39253 | 2 | 2 | 7 | 0 | 0.04 | 1
ADAMTS16 | 13813 | 1 | 0 | 4 | 0 | 0.041 | 1
FNDC1 | 14359 | 0 | 0 | 4 | 0 | 0.046 | 1
NRIP1 | 14813 | 0 | 0 | 4 | 0 | 0.051 | 1
TIE1 | 11414 | 0 | 0 | 4 | 1 | 0.052 | 1
ZBTB38 | 15552 | 1 | 0 | 5 | 0 | 0.059 | 1
TTN | 459166 | 2 | 9 | 29 | 2 | 0.059 | 1

PIK3CA

Figure S1. This figure depicts the distribution of mutations and mutation types across the PIK3CA significant gene.

NFE2L2

Figure S2. This figure depicts the distribution of mutations and mutation types across the NFE2L2 significant gene.

DNAJB1

Figure S3. This figure depicts the distribution of mutations and mutation types across the DNAJB1 significant gene.

FLG

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

TEX15

Figure S5. This figure depicts the distribution of mutations and mutation types across the TEX15 significant gene.

DNMBP

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

MYH9

Figure S7. This figure depicts the distribution of mutations and mutation types across the MYH9 significant gene.

MLL3

Figure S8. This figure depicts the distribution of mutations and mutation types across the MLL3 significant gene.

CHD8

Figure S9. This figure depicts the distribution of mutations and mutation types across the CHD8 significant gene.

ARID1A

Figure S10. This figure depicts the distribution of mutations and mutation types across the ARID1A significant gene.

MLL2

Figure S11. This figure depicts the distribution of mutations and mutation types across the MLL2 significant gene.

YTHDC1

Figure S12. This figure depicts the distribution of mutations and mutation types across the YTHDC1 significant gene.

BRWD1

Figure S13. This figure depicts the distribution of mutations and mutation types across the BRWD1 significant gene.

PCLO

Figure S14. This figure depicts the distribution of mutations and mutation types across the PCLO 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.

- 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)
Copyright © 2012 Broad Institute TCGA GDAC as part of the TCGA Research Network. All rights reserved.
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