Thyroid Adenocarcinoma: Mutation Analysis (MutSigCV v0.9)
(tall-cell 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. MutSigCV v0.9 was used to generate the results found in this report.

  • Working with individual set: THCA-tall-cell

  • Number of patients in set: 23

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
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).

Figure 1. 

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

Figure 2.  Patients counts and rates file used to generate this plot: THCA-tall-cell.patients.counts_and_rates.txt

CoMut Plot

Figure 3.  Get High-res Image The matrix in the center of the figure represents individual mutations in patient samples, color-coded by type of mutation, for the significantly mutated genes. The rate of synonymous and non-synonymous mutations is displayed at the top of the matrix. The barplot on the left of the matrix shows the number of mutations in each gene. The percentages represent the fraction of tumors with at least one mutation in the specified gene. The barplot to the right of the matrix displays the q-values for the most significantly mutated genes. The purple boxplots below the matrix (only displayed if required columns are present in the provided MAF) represent the distributions of allelic fractions observed in each sample. The plot at the bottom represents the base substitution distribution of individual samples, using the same categories that were used to calculate significance.

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: 1. 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
BRAF 39721 11339 7797 21 21 1 0 0 19 0 3.9e-14 46 0.013 7.2e-10
C17orf82 6463 2438 368 1 1 1 0 0 20 0 0.028 6 0.0085 1
IL32 9384 2461 2507 1 1 1 0 0 20 7.7 0.037 5.7 0.0085 1
LYPD6B 10534 2691 1955 1 1 1 0 0 20 0 0.039 5.8 0.0089 1
NKX6-1 9453 2622 920 1 1 1 0 0 20 0 0.045 5.7 0.0086 1
EMG1 15640 4761 2829 1 1 1 0 0 20 0 0.046 5.7 0.0085 1
TFAM 12259 2944 2783 1 1 1 0 0 20 0 0.049 5.7 0.012 1
C19orf60 2047 552 598 1 1 1 0 0 20 0 0.05 3.3 0.0044 1
NDUFA6 8464 2392 1472 1 1 1 0 0 20 0 0.052 5.7 0.0087 1
OR5H15 16606 4807 598 1 1 1 0 0 20 0 0.058 5.6 0.0082 1
ZNF467 14996 4508 1311 1 1 1 0 0 20 0 0.067 5.6 0.0088 1
LYPD3 17641 5934 2139 1 1 1 0 0 15 0 0.076 5.5 0.0088 1
LUC7L3 23598 5934 4462 1 1 1 0 0 20 0 0.078 5.5 0.0087 1
CBLN3 7613 2691 1173 1 1 1 0 0 20 0 0.082 3 0.0047 1
IFT52 24817 6440 5980 1 1 1 0 0 20 0 0.083 5.5 0.0086 1
KRTAP10-3 11684 3611 552 1 1 1 0 0 20 0 0.087 2.9 0.005 1
DNTTIP1 17089 4784 5474 1 1 1 0 0 20 0 0.087 5.5 0.0087 1
RNF7 5957 805 1173 1 1 1 0 0 20 0 0.091 3.1 0.0045 1
C19orf35 7705 2645 690 1 1 1 0 0 20 0 0.099 2.9 0.0051 1
C15orf52 22586 7084 4301 1 1 1 0 0 20 0 0.1 5.4 0.0087 1
CD74 13915 3565 3266 1 1 1 0 0 20 0 0.11 2.8 0.0048 1
EOMES 24495 6992 2622 1 1 1 0 0 20 0 0.12 5.4 0.0087 1
OR6C3 16537 4853 621 1 1 1 0 0 20 0 0.12 3.1 0.0056 1
CT45A5 6141 1610 874 2 1 2 0 0 20 0 0.12 2.9 0.0045 1
TK1 10511 2967 2047 1 1 1 0 0 20 0 0.13 2.8 0.0063 1
TMEM71 15778 4278 4002 1 1 1 0 0 20 0 0.13 2.8 0.0049 1
TTC39C 29417 7843 5681 1 1 1 0 0 20 0 0.13 5.3 0.011 1
SHROOM1 28451 9706 2484 1 1 1 0 0 20 0 0.13 5.3 0.0088 1
SPATS1 16721 4416 3611 1 1 1 0 0 18 0 0.14 2.8 0.0048 1
CDKL2 27508 7084 4554 1 1 1 0 0 20 0 0.14 5.3 0.0086 1
FAM35A 49680 13593 3266 1 1 1 0 0 20 0 0.15 5.3 0.0087 1
ADAM33 26335 7751 6463 1 1 1 0 0 20 14 0.15 5.2 0.0089 1
EIF3G 27922 8671 4669 1 1 1 0 0 20 0 0.16 5.3 0.0089 1
DMAP1 25001 7429 4646 1 1 1 0 0 20 0 0.16 5.3 0.009 1
OR5B3 16744 4876 621 1 1 1 0 0 20 0 0.17 2.6 0.0048 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.

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