Thyroid Adenocarcinoma: Mutation Analysis (MutSig vS2N)
(follicular 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-follicular

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: 4. 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
NRAS 5230 0 0 18 0 0 0
BRAF 18531 0 0 12 0 0 0
HRAS 4969 0 0 8 0 0 0
TG 70075 0 2 6 3 4.9e-41 2.3e-37
MUC16 327620 0 4 4 0 0.88 1
ADAMTS2 22292 0 0 3 0 1 1
KRAS 7360 0 0 3 0 1 1
NSD1 64302 0 0 3 1 1 1
R3HDM2 13156 0 0 3 3 1 1
RPTN 18436 0 0 3 2 1 1
SACS 121805 0 0 3 2 1 1
ZNF211 14626 0 0 3 0 1 1
ADAM15 17703 0 0 2 0 1 1
ADAMTS3 30435 0 0 2 0 1 1
ALPP 9750 0 0 2 1 1 1
ANK1 46175 0 0 2 0 1 1
APOB 124746 0 0 2 0 1 1
CHEK2 14744 0 0 2 1 1 1
CNNM1 13424 0 0 2 0 1 1
COL4A1 27239 0 0 2 1 1 1
CPE 10698 0 0 2 0 1 1
CSMD2 85366 0 0 2 1 1 1
CYB5R4 14177 0 0 2 0 1 1
DCAF13 15241 0 0 2 0 1 1
DGCR8 20069 0 0 2 0 1 1
DNAH5 125055 0 0 2 0 1 1
EIF1AX 3976 0 0 2 0 1 1
FAM13A 27193 0 0 2 0 1 1
GABRR2 12995 0 0 2 1 1 1
GBF1 45085 0 0 2 1 1 1
GIGYF1 19452 0 0 2 1 1 1
GON4L 50080 0 0 2 0 1 1
GRIA2 25087 0 0 2 0 1 1
HIF3A 12142 0 0 2 0 1 1
HMCN1 140128 0 0 2 0 1 1
NRAS

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

BRAF

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

HRAS

Figure S3.  This figure depicts the distribution of mutations and mutation types across the HRAS 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.

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