(other 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-other
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-other.final_analysis_set.maf
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Significantly mutated genes (q ≤ 0.1): 1
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)
gene | N | nflank | nsil | nnon | nnull | p | q |
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BRAF | 4959 | 0 | 0 | 4 | 0 | 3.2e-149 | 6e-145 |
DNAH2 | 30667 | 0 | 0 | 2 | 0 | 1 | 1 |
DNAH9 | 30381 | 0 | 0 | 2 | 0 | 1 | 1 |
EHBP1 | 8370 | 0 | 0 | 2 | 0 | 1 | 1 |
EIF1AX | 1064 | 0 | 0 | 2 | 1 | 1 | 1 |
FREM1 | 13571 | 0 | 0 | 2 | 0 | 1 | 1 |
HRAS | 1319 | 0 | 0 | 2 | 0 | 1 | 1 |
IRS1 | 6402 | 0 | 0 | 2 | 0 | 1 | 1 |
NRAS | 1396 | 0 | 0 | 2 | 0 | 1 | 1 |
TRIM46 | 4198 | 0 | 0 | 2 | 0 | 1 | 1 |
ABHD4 | 2119 | 0 | 0 | 1 | 0 | 1 | 1 |
ABP1 | 4540 | 0 | 0 | 1 | 1 | 1 | 1 |
ACAD10 | 6744 | 0 | 0 | 1 | 0 | 1 | 1 |
ADH4 | 2603 | 0 | 0 | 1 | 0 | 1 | 1 |
ADRB1 | 1591 | 0 | 0 | 1 | 0 | 1 | 1 |
AKAP11 | 13299 | 0 | 0 | 1 | 1 | 1 | 1 |
AKAP8L | 3371 | 0 | 0 | 1 | 1 | 1 | 1 |
ALG3 | 2982 | 0 | 0 | 1 | 0 | 1 | 1 |
ALPK1 | 8398 | 0 | 0 | 1 | 0 | 1 | 1 |
AMAC1 | 1824 | 0 | 0 | 1 | 0 | 1 | 1 |
AMY2A | 1806 | 0 | 0 | 1 | 0 | 1 | 1 |
ANK1 | 12371 | 0 | 0 | 1 | 0 | 1 | 1 |
ANTXR2 | 2198 | 0 | 0 | 1 | 0 | 1 | 1 |
AP3B1 | 7883 | 0 | 0 | 1 | 0 | 1 | 1 |
APOB | 33372 | 0 | 0 | 1 | 0 | 1 | 1 |
ARHGAP29 | 9119 | 0 | 0 | 1 | 1 | 1 | 1 |
ARID2 | 11505 | 0 | 0 | 1 | 1 | 1 | 1 |
ATM | 22860 | 0 | 0 | 1 | 0 | 1 | 1 |
ATRNL1 | 9384 | 0 | 0 | 1 | 1 | 1 | 1 |
BAT2 | 9441 | 0 | 0 | 1 | 0 | 1 | 1 |
BCAR3 | 5187 | 0 | 0 | 1 | 0 | 1 | 1 |
BCAT1 | 2566 | 0 | 0 | 1 | 1 | 1 | 1 |
BDP1 | 18135 | 0 | 0 | 1 | 0 | 1 | 1 |
BLMH | 3391 | 0 | 0 | 1 | 0 | 1 | 1 |
BMS1 | 8743 | 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.