Thyroid Adenocarcinoma: Mutation Analysis (MutSig vS2N)
(classical 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: THCA-classical

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:THCA-classical.final_analysis_set.maf

- Significantly mutated genes (q ≤ 0.1): 6

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: 6. 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
--- | --- | --- | --- | --- | --- | --- | ---
BRAF | 33408 | 0 | 0 | 98 | 0 | 0 | 0
CCDC15 | 34077 | 0 | 1 | 5 | 0 | 2e-181 | 1.9e-177
ZNF845 | 32752 | 0 | 0 | 5 | 0 | 6.8e-47 | 4.3e-43
PPM1D | 22528 | 0 | 0 | 4 | 4 | 7.7e-43 | 3.6e-39
MLL3 | 207510 | 0 | 0 | 5 | 2 | 5.1e-08 | 0.00018
MUC17 | 173746 | 0 | 2 | 5 | 0 | 5.7e-08 | 0.00018
ZFHX3 | 150567 | 0 | 0 | 4 | 0 | 0.05 | 1
LRP1 | 188956 | 0 | 0 | 4 | 2 | 0.099 | 1
TTN | 1632990 | 0 | 2 | 5 | 1 | 0.12 | 1
MUC16 | 590609 | 0 | 4 | 5 | 1 | 0.35 | 1
ASH1L | 135090 | 0 | 0 | 3 | 0 | 1 | 1
ATM | 153834 | 0 | 0 | 3 | 1 | 1 | 1
CCDC39 | 34883 | 0 | 1 | 3 | 1 | 1 | 1
COL5A3 | 46319 | 0 | 0 | 3 | 1 | 1 | 1
CSMD3 | 170785 | 0 | 0 | 3 | 0 | 1 | 1
CTTNBP2 | 71602 | 0 | 0 | 3 | 0 | 1 | 1
DNAH9 | 204672 | 0 | 0 | 3 | 0 | 1 | 1
FLG | 139965 | 0 | 0 | 3 | 0 | 1 | 1
MYH6 | 92110 | 0 | 0 | 3 | 0 | 1 | 1
NBPF10 | 33553 | 0 | 0 | 3 | 0 | 1 | 1
NISCH | 60354 | 0 | 1 | 3 | 0 | 1 | 1
OBSCN | 218568 | 0 | 0 | 3 | 0 | 1 | 1
PKHD1L1 | 180085 | 0 | 0 | 3 | 2 | 1 | 1
PLXNB1 | 67889 | 0 | 0 | 3 | 0 | 1 | 1
PRDM9 | 39168 | 0 | 1 | 3 | 0 | 1 | 1
PRG4 | 58852 | 0 | 1 | 3 | 0 | 1 | 1
PTPRZ1 | 108388 | 0 | 0 | 3 | 0 | 1 | 1
STXBP5L | 55602 | 0 | 0 | 3 | 0 | 1 | 1
VWA3B | 59637 | 0 | 0 | 3 | 0 | 1 | 1
ZNF185 | 17052 | 0 | 0 | 3 | 1 | 1 | 1
ZNF799 | 29095 | 0 | 1 | 3 | 0 | 1 | 1
ABL2 | 49152 | 0 | 0 | 2 | 2 | 1 | 1
ACD | 22845 | 0 | 0 | 2 | 1 | 1 | 1
ACRC | 26040 | 0 | 0 | 2 | 0 | 1 | 1
ADAMTS19 | 47154 | 0 | 0 | 2 | 0 | 1 | 1

BRAF

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

CCDC15

Figure S2. This figure depicts the distribution of mutations and mutation types across the CCDC15 significant gene.

ZNF845

Figure S3. This figure depicts the distribution of mutations and mutation types across the ZNF845 significant gene.

PPM1D

Figure S4. This figure depicts the distribution of mutations and mutation types across the PPM1D significant gene.

MLL3

Figure S5. This figure depicts the distribution of mutations and mutation types across the MLL3 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)
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