Rectum 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: READ

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:READ.final_analysis_set.maf

- Significantly mutated genes (q ≤ 0.1): 204

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: 204. 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 | 7519 | 0 | 0 | 39 | 1 | 0 | 0
APC | 72124 | 0 | 0 | 94 | 81 | 4.2e-161 | 3.9e-157
POTEB | 1387 | 0 | 2 | 6 | 1 | 4.8e-98 | 3e-94
TP53 | 9198 | 0 | 1 | 47 | 12 | 2.4e-72 | 1.1e-68
LRRC40 | 16717 | 0 | 0 | 7 | 1 | 5.8e-27 | 2.2e-23
ZNF549 | 17009 | 0 | 0 | 10 | 0 | 4.3e-26 | 1.3e-22
KIF5B | 27083 | 0 | 0 | 13 | 4 | 1.3e-25 | 3.6e-22
YIPF1 | 8322 | 0 | 0 | 4 | 0 | 3.9e-25 | 9.1e-22
PCCA | 18250 | 0 | 0 | 10 | 2 | 4.5e-23 | 9.4e-20
UPF2 | 35551 | 0 | 0 | 9 | 0 | 1.1e-21 | 2.1e-18
TMPO | 23725 | 0 | 0 | 6 | 5 | 1.4e-21 | 2.5e-18
PTPRR | 18469 | 0 | 0 | 9 | 4 | 6.7e-20 | 1.1e-16
ZNHIT6 | 13286 | 0 | 0 | 6 | 5 | 2.9e-18 | 4.2e-15
DGKH | 30952 | 0 | 0 | 7 | 0 | 2.6e-16 | 3.5e-13
RTN4 | 28324 | 0 | 0 | 6 | 0 | 3.4e-16 | 4.2e-13
TGM5 | 19272 | 0 | 0 | 8 | 0 | 3.4e-15 | 4e-12
CCBP2 | 10001 | 0 | 0 | 6 | 0 | 2.5e-14 | 2.8e-11
NFKB1 | 24163 | 0 | 0 | 6 | 0 | 1e-13 | 1.1e-10
KRT84 | 12483 | 0 | 0 | 7 | 0 | 1.1e-13 | 1.1e-10
CCDC99 | 17082 | 0 | 0 | 5 | 0 | 1.4e-13 | 1.3e-10
UBOX5 | 32485 | 0 | 0 | 7 | 0 | 1.5e-13 | 1.4e-10
TP53BP1 | 47085 | 0 | 0 | 12 | 3 | 2.7e-13 | 2.3e-10
PSMD1 | 39566 | 0 | 0 | 7 | 0 | 3.1e-13 | 2.6e-10
KBTBD10 | 16571 | 0 | 0 | 7 | 2 | 3.8e-13 | 2.9e-10
HSPA4 | 22484 | 0 | 0 | 8 | 0 | 4e-13 | 3e-10
RBPJ | 13140 | 0 | 0 | 6 | 0 | 8.4e-13 | 6.1e-10
AKAP3 | 21827 | 0 | 0 | 9 | 5 | 5.2e-12 | 3.7e-09
PEX3 | 11461 | 0 | 1 | 6 | 0 | 7.4e-12 | 5e-09
FRMPD1 | 37303 | 0 | 4 | 10 | 0 | 2.2e-11 | 1.4e-08
ARHGAP12 | 23579 | 0 | 0 | 7 | 2 | 5.9e-11 | 3.7e-08
ZC3HC1 | 11680 | 0 | 0 | 7 | 0 | 6.4e-11 | 3.9e-08
TLK1 | 20805 | 0 | 0 | 7 | 0 | 1.3e-10 | 7.5e-08
NCOA3 | 35843 | 0 | 1 | 9 | 2 | 1.3e-10 | 7.5e-08
ARID1A | 42486 | 0 | 0 | 5 | 5 | 2.3e-10 | 1.3e-07
TTC27 | 21608 | 0 | 0 | 7 | 0 | 2.9e-10 | 1.6e-07

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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