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: COAD-TP
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:COAD-TP.final_analysis_set.maf
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Significantly mutated genes (q ≤ 0.1): 46
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: 46. 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 |
|---|---|---|---|---|---|---|---|
| KRAS | 15965 | 0 | 0 | 43 | 0 | 5.3e-249 | 1e-244 |
| APC | 153140 | 0 | 4 | 157 | 140 | 8.5e-126 | 8e-122 |
| TP53 | 19530 | 0 | 1 | 66 | 26 | 2.8e-83 | 1.8e-79 |
| NRAS | 11315 | 0 | 0 | 11 | 0 | 1.2e-80 | 5.5e-77 |
| SMAD4 | 28210 | 0 | 0 | 20 | 5 | 3.1e-67 | 1.2e-63 |
| FAM22F | 17205 | 0 | 1 | 9 | 1 | 2.3e-29 | 7.2e-26 |
| FAM123B | 48050 | 0 | 1 | 18 | 14 | 4.2e-21 | 1.1e-17 |
| SOX9 | 19375 | 0 | 0 | 9 | 8 | 3.4e-16 | 8.1e-13 |
| SMAD2 | 25420 | 0 | 0 | 11 | 4 | 4.5e-12 | 9.5e-09 |
| EYS | 34875 | 0 | 1 | 8 | 3 | 7.5e-12 | 1.4e-08 |
| ZNF14 | 37665 | 0 | 0 | 7 | 6 | 1.4e-10 | 2.5e-07 |
| CDC27 | 46345 | 0 | 4 | 11 | 2 | 3.3e-10 | 5.3e-07 |
| HLA-B | 14880 | 0 | 0 | 5 | 5 | 1.6e-09 | 2.3e-06 |
| ACTBL2 | 20305 | 0 | 1 | 8 | 0 | 4.5e-09 | 6e-06 |
| HCLS1 | 24335 | 0 | 0 | 6 | 3 | 1.7e-08 | 0.000021 |
| TCERG1 | 56265 | 0 | 0 | 11 | 3 | 5.4e-08 | 6e-05 |
| NID2 | 70370 | 0 | 0 | 10 | 3 | 5.4e-08 | 6e-05 |
| GOLGB1 | 192200 | 0 | 0 | 15 | 7 | 6e-08 | 0.000063 |
| TBC1D10C | 10385 | 0 | 0 | 4 | 4 | 8.4e-08 | 0.000084 |
| FBXW11 | 30845 | 0 | 0 | 6 | 0 | 6.1e-07 | 0.00058 |
| TGFBR1 | 26660 | 0 | 1 | 6 | 0 | 8.9e-07 | 0.0008 |
| ZC3H13 | 81840 | 0 | 1 | 16 | 12 | 1.1e-06 | 0.00098 |
| ACOT4 | 16430 | 0 | 0 | 6 | 6 | 1.6e-06 | 0.0013 |
| CASP8 | 36425 | 0 | 0 | 8 | 4 | 4.1e-06 | 0.0032 |
| TXNDC3 | 35495 | 0 | 0 | 12 | 5 | 5.5e-06 | 0.0042 |
| COL11A2 | 52235 | 0 | 1 | 8 | 2 | 5.8e-06 | 0.0042 |
| OR2T33 | 17360 | 0 | 1 | 5 | 0 | 6.1e-06 | 0.0042 |
| VAV3 | 50840 | 0 | 1 | 8 | 0 | 8e-06 | 0.0054 |
| FAT2 | 228780 | 0 | 4 | 26 | 1 | 9.4e-06 | 0.0061 |
| PIK3CA | 65255 | 0 | 0 | 28 | 0 | 1e-05 | 0.0064 |
| ZMYM6 | 54560 | 0 | 0 | 10 | 2 | 0.000014 | 0.0081 |
| OR2M4 | 18910 | 0 | 0 | 8 | 2 | 0.000014 | 0.0081 |
| TM9SF1 | 36425 | 0 | 1 | 7 | 0 | 0.000014 | 0.0081 |
| SCN11A | 111135 | 0 | 3 | 13 | 0 | 0.000016 | 0.009 |
| ZFP3 | 28520 | 0 | 1 | 7 | 0 | 0.000018 | 0.0099 |
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.