Colon/Rectal Adenocarcinoma: 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: COADREAD

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:COADREAD.final_analysis_set.maf

- Significantly mutated genes (q ≤ 0.1): 49

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: 49. 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
--- | --- | --- | --- | --- | --- | --- | ---
KRAS | 23484 | 0 | 0 | 98 | 1 | 0 | 0
APC | 225264 | 0 | 4 | 257 | 221 | 2.1e-83 | 1.9e-79
TP53 | 28728 | 0 | 2 | 124 | 38 | 9.9e-74 | 6.2e-70
BRAF | 59508 | 0 | 0 | 23 | 0 | 9.6e-46 | 4.5e-42
POTED | 11400 | 0 | 1 | 9 | 0 | 8.1e-33 | 3.1e-29
NRAS | 16644 | 0 | 0 | 21 | 0 | 2.2e-27 | 6.9e-24
PIK3CA | 95988 | 0 | 2 | 40 | 0 | 4.2e-20 | 1.1e-16
SOX9 | 28500 | 0 | 0 | 11 | 10 | 7e-15 | 1.7e-11
FAM123B | 70680 | 0 | 3 | 27 | 19 | 3.4e-11 | 7.2e-08
EYS | 51300 | 1 | 1 | 11 | 3 | 5.1e-11 | 9.7e-08
FAM22F | 25308 | 0 | 1 | 10 | 1 | 1.1e-09 | 1.9e-06
PCBP1 | 26220 | 0 | 0 | 6 | 0 | 4.2e-09 | 6.6e-06
FBXW7 | 65436 | 1 | 2 | 48 | 10 | 8.7e-08 | 0.00013
ELF3 | 28272 | 0 | 0 | 8 | 6 | 1.6e-07 | 0.0002
ANKRD20A3 | 50616 | 0 | 0 | 7 | 1 | 1.6e-07 | 0.0002
ARID1A | 132696 | 0 | 3 | 22 | 13 | 1.8e-07 | 0.00021
ACOT4 | 24168 | 0 | 1 | 6 | 6 | 4.9e-07 | 0.00055
ZNF14 | 55404 | 0 | 0 | 10 | 9 | 5.3e-07 | 0.00056
RBBP7 | 35112 | 0 | 0 | 8 | 0 | 2.6e-06 | 0.0025
ZC3H13 | 120384 | 0 | 1 | 30 | 16 | 2.6e-06 | 0.0025
LGR4 | 76380 | 0 | 2 | 11 | 2 | 5.3e-06 | 0.0047
ACVR2A | 43092 | 0 | 1 | 14 | 10 | 5.8e-06 | 0.0049
NCOA3 | 111948 | 0 | 1 | 15 | 2 | 6.7e-06 | 0.0053
SMAD4 | 41496 | 0 | 0 | 31 | 5 | 6.8e-06 | 0.0053
PCDHGC4 | 120384 | 0 | 3 | 13 | 0 | 7.5e-06 | 0.0057
KPNA1 | 45828 | 1 | 0 | 8 | 0 | 7.9e-06 | 0.0057
RUVBL1 | 38532 | 0 | 2 | 9 | 0 | 9.9e-06 | 0.0069
PIK3R1 | 67260 | 0 | 0 | 13 | 8 | 0.000012 | 0.008
HLA-B | 21888 | 0 | 0 | 5 | 5 | 0.000021 | 0.014
USP40 | 80028 | 0 | 0 | 9 | 1 | 0.000027 | 0.017
TAT | 35112 | 0 | 1 | 7 | 0 | 0.000037 | 0.023
ZNF439 | 42864 | 0 | 1 | 9 | 0 | 0.000044 | 0.026
UPF2 | 111036 | 1 | 1 | 16 | 0 | 0.000046 | 0.026
TLK1 | 64980 | 0 | 0 | 11 | 0 | 0.000051 | 0.028
SCAND3 | 113316 | 0 | 4 | 13 | 9 | 0.000051 | 0.028

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.
Made with Nozzle