Mutation Analysis (MutSigCV v0.9)
Acute Myeloid Leukemia (Primary blood derived cancer - Peripheral blood)
15 July 2014  |  analyses__2014_07_15
Maintainer Information
Citation Information
doi:10.7908/C1FJ2FJX
Maintained by David Heiman (Broad Institute)
Cite as Broad Institute TCGA Genome Data Analysis Center (2014): Mutation Analysis (MutSigCV v0.9). Broad Institute of MIT and Harvard. doi:10.7908/C1FJ2FJX
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. MutSigCV v0.9 was used to generate the results found in this report.

  • Working with individual set: LAML-TB

  • Number of patients in set: 197

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

  • Blacklist used for this analysis: pancan_mutation_blacklist.v14.hg19.txt

  • Significantly mutated genes (q ≤ 0.1): 0

Results
Target Coverage for Each Individual

The x axis represents the samples. The y axis represents the exons, one row per exon, and they are sorted by average coverage across samples. For exons with exactly the same average coverage, they are sorted next by the %GC of the exon. (The secondary sort is especially useful for the zero-coverage exons at the bottom). If the figure is unpopulated, then full coverage is assumed (e.g. MutSig CV doesn't use WIGs and assumes full coverage).

Figure 1. 

Distribution of Mutation Counts, Coverage, and Mutation Rates Across Samples

Figure 2.  Patients counts and rates file used to generate this plot: LAML-TB.patients.counts_and_rates.txt

Lego Plots

The mutation spectrum is depicted in the lego plots below in which the 96 possible mutation types are subdivided into six large blocks, color-coded to reflect the base substitution type. Each large block is further subdivided into the 16 possible pairs of 5' and 3' neighbors, as listed in the 4x4 trinucleotide context legend. The height of each block corresponds to the mutation frequency for that kind of mutation (counts of mutations normalized by the base coverage in a given bin). The shape of the spectrum is a signature for dominant mutational mechanisms in different tumor types.

Figure 3.  Get High-res Image SNV Mutation rate lego plot for entire set. Each bin is normalized by base coverage for that bin. Colors represent the six SNV types on the upper right. The three-base context for each mutation is labeled in the 4x4 legend on the lower right. The fractional breakdown of SNV counts is shown in the pie chart on the upper left. If this figure is blank, not enough information was provided in the MAF to generate it.

Figure 4.  Get High-res Image SNV Mutation rate lego plots for 4 slices of mutation allele fraction (0<=AF<0.1, 0.1<=AF<0.25, 0.25<=AF<0.5, & 0.5<=AF) . The color code and three-base context legends are the same as the previous figure. If this figure is blank, not enough information was provided in the MAF to generate it.

Significantly Mutated Genes

Column Descriptions:

  • nnon = number of (nonsilent) mutations in this gene across the individual set

  • npat = number of patients (individuals) with at least one nonsilent mutation

  • nsite = number of unique sites having a non-silent mutation

  • 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 Nnon Nsil Nflank nnon npat nsite nsil nflank nnei fMLE p score time q
A1BG 157797 51417 217291 0 0 0 0 0 20 2.1 1 0 NaN 1
A1CF 297667 86680 470633 0 0 0 0 0 0 0 1 0 NaN 1
A2BP1 216109 59691 766527 0 0 0 0 0 10 2.1 1 0 NaN 1
A2M 614837 178285 956435 0 0 0 0 0 20 0 1 0 NaN 1
A2ML1 688515 197197 1490699 0 0 0 0 0 3 0 1 0 NaN 1
A4GALT 133960 43537 15760 0 0 0 0 0 20 3.9 1 0 NaN 1
A4GNT 158585 43931 99091 0 0 0 0 0 20 0 1 0 NaN 1
AAAS 306335 98303 602623 0 0 0 0 0 7 0.99 1 0 NaN 1
AACS 299440 83331 669209 0 0 0 0 0 20 0 1 0 NaN 1
AADAC 186362 52796 176512 0 0 0 0 0 20 2.3 1 0 NaN 1
AADACL2 188332 52008 176118 0 0 0 0 0 20 0 1 0 NaN 1
AADACL3 164298 46098 203698 0 0 0 0 0 20 1.5 1 0 NaN 1
AADACL4 186953 55948 190302 0 0 0 0 0 20 1.5 1 0 NaN 1
AADAT 199758 52993 457040 0 0 0 0 0 0 0 1 0 NaN 1
AAGAB 154054 40779 443053 0 0 0 0 0 19 2.9 1 0 NaN 1
AAK1 339431 101061 697577 0 0 0 0 0 20 0.57 1 0 NaN 1
AAMP 252948 78209 488757 0 0 0 0 0 20 1.2 1 0 NaN 1
AANAT 63631 20291 75845 0 0 0 0 0 20 2.4 1 0 NaN 1
AARS 447978 129626 741311 0 0 0 0 0 20 0.75 1 0 NaN 1
AARS2 428081 140658 791546 0 0 0 0 0 20 0 1 0 NaN 1
AARSD1 266935 74466 672164 0 0 0 0 0 14 0 1 0 NaN 1
AASDH 511609 143416 417443 0 0 0 0 0 4 0 1 0 NaN 1
AASDHPPT 145583 38218 191287 0 0 0 0 0 11 0.9 1 0 NaN 1
AASS 442659 122731 895168 0 0 0 0 0 9 0.97 1 0 NaN 1
AATF 257282 67177 460980 0 0 0 0 0 20 0 1 0 NaN 1
AATK 181240 59297 97909 0 0 0 0 0 20 0.9 1 0 NaN 1
ABAT 236006 64419 608336 0 0 0 0 0 20 0.78 1 0 NaN 1
ABCA1 1053162 297667 2047618 0 0 0 0 0 0 0 1 0 NaN 1
ABCA10 742099 193848 1385698 0 0 0 0 1 9 1.9 1 0 NaN 1
ABCA12 1237160 341401 1967045 0 0 0 0 0 5 0 1 0 NaN 1
ABCA13 2177638 584499 1749360 0 0 0 0 0 19 0.77 1 0 NaN 1
ABCA2 769876 232854 635522 0 0 0 0 0 20 1.1 1 0 NaN 1
ABCA3 714716 218276 1140433 0 0 0 0 0 20 1.9 1 0 NaN 1
ABCA4 1041342 300228 1884502 0 0 0 0 1 13 1.4 1 0 NaN 1
ABCA5 774407 202713 1253117 0 0 0 0 0 2 0 1 0 NaN 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

In addition to the links below, the full results of the analysis summarized in this report can also be downloaded programmatically using firehose_get, or interactively from either the Broad GDAC website or TCGA Data Coordination Center Portal.

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