Colon Adenocarcinoma: Mutation Analysis (MutSig vS2N)
(primary solid tumor 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: COAD-TP

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:COAD-TP.final_analysis_set.maf

- Significantly mutated genes (q ≤ 0.1): 46

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: 46. 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 | 15965 | 0 | 0 | 43 | 0 | 5.3e-249 | 1e-244
APC | 153140 | 0 | 4 | 157 | 140 | 8.5e-126 | 8e-122
TP53 | 19530 | 0 | 1 | 66 | 26 | 2.8e-83 | 1.8e-79
NRAS | 11315 | 0 | 0 | 11 | 0 | 1.2e-80 | 5.5e-77
SMAD4 | 28210 | 0 | 0 | 20 | 5 | 3.1e-67 | 1.2e-63
FAM22F | 17205 | 0 | 1 | 9 | 1 | 2.3e-29 | 7.2e-26
FAM123B | 48050 | 0 | 1 | 18 | 14 | 4.2e-21 | 1.1e-17
SOX9 | 19375 | 0 | 0 | 9 | 8 | 3.4e-16 | 8.1e-13
SMAD2 | 25420 | 0 | 0 | 11 | 4 | 4.5e-12 | 9.5e-09
EYS | 34875 | 0 | 1 | 8 | 3 | 7.5e-12 | 1.4e-08
ZNF14 | 37665 | 0 | 0 | 7 | 6 | 1.4e-10 | 2.5e-07
CDC27 | 46345 | 0 | 4 | 11 | 2 | 3.3e-10 | 5.3e-07
HLA-B | 14880 | 0 | 0 | 5 | 5 | 1.6e-09 | 2.3e-06
ACTBL2 | 20305 | 0 | 1 | 8 | 0 | 4.5e-09 | 6e-06
HCLS1 | 24335 | 0 | 0 | 6 | 3 | 1.7e-08 | 0.000021
TCERG1 | 56265 | 0 | 0 | 11 | 3 | 5.4e-08 | 6e-05
NID2 | 70370 | 0 | 0 | 10 | 3 | 5.4e-08 | 6e-05
GOLGB1 | 192200 | 0 | 0 | 15 | 7 | 6e-08 | 0.000063
TBC1D10C | 10385 | 0 | 0 | 4 | 4 | 8.4e-08 | 0.000084
FBXW11 | 30845 | 0 | 0 | 6 | 0 | 6.1e-07 | 0.00058
TGFBR1 | 26660 | 0 | 1 | 6 | 0 | 8.9e-07 | 0.0008
ZC3H13 | 81840 | 0 | 1 | 16 | 12 | 1.1e-06 | 0.00098
ACOT4 | 16430 | 0 | 0 | 6 | 6 | 1.6e-06 | 0.0013
CASP8 | 36425 | 0 | 0 | 8 | 4 | 4.1e-06 | 0.0032
TXNDC3 | 35495 | 0 | 0 | 12 | 5 | 5.5e-06 | 0.0042
COL11A2 | 52235 | 0 | 1 | 8 | 2 | 5.8e-06 | 0.0042
OR2T33 | 17360 | 0 | 1 | 5 | 0 | 6.1e-06 | 0.0042
VAV3 | 50840 | 0 | 1 | 8 | 0 | 8e-06 | 0.0054
FAT2 | 228780 | 0 | 4 | 26 | 1 | 9.4e-06 | 0.0061
PIK3CA | 65255 | 0 | 0 | 28 | 0 | 1e-05 | 0.0064
ZMYM6 | 54560 | 0 | 0 | 10 | 2 | 0.000014 | 0.0081
OR2M4 | 18910 | 0 | 0 | 8 | 2 | 0.000014 | 0.0081
TM9SF1 | 36425 | 0 | 1 | 7 | 0 | 0.000014 | 0.0081
SCN11A | 111135 | 0 | 3 | 13 | 0 | 0.000016 | 0.009
ZFP3 | 28520 | 0 | 1 | 7 | 0 | 0.000018 | 0.0099

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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