Mutation Analysis (MutSig vS2N)
Acute Myeloid Leukemia (Primary blood derived cancer - Peripheral blood)
22 February 2013 | analyses__2013_02_22
Maintainer Information
Citation Information
doi:10.7908/C1571978
Maintained by Dan DiCara (Broad Institute)
Cite as Broad Institute TCGA Genome Data Analysis Center (2013): Mutation Analysis (MutSig vS2N). Broad Institute of MIT and Harvard. doi:10.7908/C1571978
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: LAML-TB

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:LAML-TB.final_analysis_set.maf

- Significantly mutated genes (q ≤ 0.1): 0

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: 0. 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
--- | --- | --- | --- | --- | --- | --- | ---
A1BG | 20882 | 0 | 0 | 0 | 0 | 1 | 1
A1CF | 42946 | 0 | 0 | 0 | 0 | 1 | 1
A2BP1 | 28762 | 0 | 0 | 0 | 0 | 1 | 1
A2LD1 | 0 | 0 | 0 | 0 | 0 | 1 | 1
A2M | 93969 | 0 | 0 | 0 | 0 | 1 | 1
A2ML1 | 104804 | 0 | 0 | 0 | 0 | 1 | 1
A4GALT | 19306 | 0 | 0 | 0 | 0 | 1 | 1
A4GNT | 24822 | 0 | 0 | 0 | 0 | 1 | 1
AAAS | 39400 | 0 | 0 | 0 | 0 | 1 | 1
AACS | 45901 | 0 | 0 | 0 | 0 | 1 | 1
AADAC | 29747 | 0 | 0 | 0 | 0 | 1 | 1
AADACL2 | 29747 | 0 | 0 | 0 | 0 | 1 | 1
AADACL3 | 25216 | 0 | 0 | 0 | 0 | 1 | 1
AADACL4 | 28762 | 0 | 0 | 0 | 0 | 1 | 1
AADAT | 31520 | 0 | 0 | 0 | 0 | 1 | 1
AAGAB | 22655 | 0 | 0 | 0 | 0 | 1 | 1
AAK1 | 48462 | 0 | 0 | 0 | 0 | 1 | 1
AAMP | 31914 | 0 | 0 | 0 | 0 | 1 | 1
AANAT | 8274 | 0 | 0 | 0 | 0 | 1 | 1
AARS | 65207 | 0 | 0 | 0 | 0 | 1 | 1
AARS2 | 54175 | 0 | 0 | 0 | 0 | 1 | 1
AARSD1 | 38809 | 0 | 0 | 0 | 0 | 1 | 1
AASDH | 81558 | 0 | 0 | 0 | 0 | 1 | 1
AASDHPPT | 22458 | 0 | 0 | 0 | 0 | 1 | 1
AASS | 66980 | 0 | 0 | 0 | 0 | 1 | 1
AATF | 36642 | 0 | 0 | 0 | 0 | 1 | 1
AATK | 22458 | 0 | 0 | 0 | 0 | 1 | 1
ABAT | 35854 | 0 | 0 | 0 | 0 | 1 | 1
ABCA1 | 164889 | 0 | 0 | 0 | 0 | 1 | 1
ABCA10 | 124307 | 1 | 0 | 0 | 0 | 1 | 1
ABCA12 | 204092 | 0 | 0 | 0 | 0 | 1 | 1
ABCA13 | 363662 | 0 | 0 | 0 | 0 | 1 | 1
ABCA2 | 114260 | 0 | 0 | 0 | 0 | 1 | 1
ABCA3 | 106183 | 0 | 0 | 0 | 0 | 1 | 1
ABCA4 | 158388 | 0 | 0 | 0 | 0 | 1 | 1

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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