(tall-cell cohort)
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.
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Working with individual set: THCA-tall-cell
The input for this pipeline is a set of individuals with the following files associated for each:
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An annotated .maf file describing the mutations called for the respective individual, and their properties.
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A .wig file that contains information about the coverage of the sample.
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MAF used for this analysis:THCA-tall-cell.final_analysis_set.maf
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Significantly mutated genes (q ≤ 0.1): 0
Column Descriptions:
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N = number of sequenced bases in this gene across the individual set
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nnon = number of (nonsilent) mutations in this gene across the individual set
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nnull = number of (nonsilent) null mutations in this gene across the individual set
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nflank = number of noncoding mutations from this gene's flanking region, across the individual set
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nsil = number of silent mutations in this gene across the individual set
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p = p-value (overall)
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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 |
|---|---|---|---|---|---|---|---|
| BRAF | 6003 | 0 | 0 | 21 | 0 | 0 | 0 |
| TG | 22627 | 0 | 1 | 3 | 2 | 1 | 1 |
| TTN | 293246 | 0 | 1 | 3 | 1 | 1 | 1 |
| ZNF28 | 5917 | 0 | 0 | 3 | 0 | 1 | 1 |
| ARID1B | 12532 | 0 | 0 | 2 | 1 | 1 | 1 |
| COL6A2 | 6244 | 0 | 0 | 2 | 0 | 1 | 1 |
| CT45A5 | 940 | 0 | 0 | 2 | 0 | 1 | 1 |
| DBN1 | 4163 | 0 | 0 | 2 | 0 | 1 | 1 |
| FANCD2 | 13188 | 0 | 0 | 2 | 0 | 1 | 1 |
| KIF2C | 6121 | 0 | 0 | 2 | 0 | 1 | 1 |
| MYOM2 | 11902 | 0 | 0 | 2 | 0 | 1 | 1 |
| NAV3 | 18567 | 0 | 0 | 2 | 0 | 1 | 1 |
| SETX | 23144 | 0 | 0 | 2 | 0 | 1 | 1 |
| TOPBP1 | 12069 | 0 | 0 | 2 | 0 | 1 | 1 |
| TRPM4 | 7130 | 0 | 0 | 2 | 0 | 1 | 1 |
| A2M | 11211 | 0 | 0 | 1 | 0 | 1 | 1 |
| ABCA3 | 12117 | 0 | 0 | 1 | 0 | 1 | 1 |
| ABCB11 | 10470 | 0 | 0 | 1 | 0 | 1 | 1 |
| ABCB7 | 5856 | 0 | 0 | 1 | 1 | 1 | 1 |
| ABCD1 | 3387 | 0 | 0 | 1 | 0 | 1 | 1 |
| ACAD10 | 8148 | 0 | 0 | 1 | 1 | 1 | 1 |
| ACOT12 | 4442 | 0 | 0 | 1 | 0 | 1 | 1 |
| ACVR2A | 4353 | 0 | 0 | 1 | 0 | 1 | 1 |
| ADAM33 | 3304 | 0 | 0 | 1 | 1 | 1 | 1 |
| ADAMTS18 | 9266 | 0 | 0 | 1 | 0 | 1 | 1 |
| ADAMTSL3 | 13041 | 0 | 0 | 1 | 0 | 1 | 1 |
| ADAMTSL4 | 6038 | 0 | 0 | 1 | 0 | 1 | 1 |
| ADC | 3631 | 0 | 0 | 1 | 0 | 1 | 1 |
| ADH7 | 3200 | 0 | 0 | 1 | 0 | 1 | 1 |
| AIM1 | 12839 | 0 | 0 | 1 | 0 | 1 | 1 |
| AMOTL2 | 4571 | 0 | 0 | 1 | 0 | 1 | 1 |
| ANAPC5 | 6348 | 0 | 0 | 1 | 0 | 1 | 1 |
| ANK2 | 30498 | 0 | 0 | 1 | 0 | 1 | 1 |
| AP2B1 | 8122 | 0 | 0 | 1 | 0 | 1 | 1 |
| AP3B1 | 9511 | 0 | 0 | 1 | 0 | 1 | 1 |
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]
This is an experimental feature. The full results of the analysis summarized in this report can be downloaded from the TCGA Data Coordination Center.