Mutation Analysis (MutSigCV v0.9)
Colon/Rectal Adenocarcinoma (Primary solid tumor)
23 May 2013  |  analyses__2013_05_23
Maintainer Information
Citation Information
Maintained by Dan DiCara (Broad Institute)
Cite as Broad Institute TCGA Genome Data Analysis Center (2013): Mutation Analysis (MutSigCV v0.9). Broad Institute of MIT and Harvard. doi:10.7908/C1ZS2TH3
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: COADREAD-TP

  • Number of patients in set: 228

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: COADREAD-TP.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: 15. 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
TP53 215460 62928 206 124 122 69 2 0 4 0.98 2.7e-15 400 0.22 2.5e-11
APC 1521216 426360 291 257 167 158 4 0 4 0.73 3.2e-15 780 0.24 2.5e-11
FBXW7 442776 121524 239 48 40 28 2 1 20 1.4 4.1e-15 120 0.23 2.5e-11
KRAS 137940 33744 106 98 98 12 0 0 1 0 5.6e-15 230 0.22 2.5e-11
NRAS 105108 27816 82 21 21 8 0 0 20 0.65 1.5e-14 67 0.22 5.4e-11
SMAD4 301872 84132 222 31 27 23 0 0 20 1 5.9e-14 84 0.22 1.8e-10
FAM123B 564528 167352 98 27 25 24 3 0 20 1.8 1.6e-12 110 0.22 4.1e-09
PIK3CA 592572 151620 396 40 33 21 2 0 20 1.3 3.5e-08 76 0.22 0.000079
SMAD2 254676 71136 199 17 16 12 1 0 20 1.2 1.2e-07 54 0.22 0.00023
TCF7L2 338580 95532 273 20 18 18 5 0 20 1.5 2e-07 63 0.21 0.00036
SOX9 214776 63156 52 11 10 11 0 0 20 1.3 2.2e-07 55 0.21 0.00036
ACVR2A 283632 74784 222 14 11 10 1 0 10 0.84 5.5e-07 49 0.21 0.00084
ELF3 202692 55632 158 8 8 7 0 0 20 0.75 2e-06 42 0.21 0.0028
BRAF 393756 112404 339 23 22 4 0 0 19 1 5.5e-06 51 0.23 0.0072
CCDC160 88692 21432 5 10 7 10 0 0 20 1.3 0.000048 27 0.21 0.058
B2M 65436 18240 64 7 5 6 0 0 20 0.96 0.00011 23 0.2 0.13
KIAA1804 412680 121980 180 20 16 16 0 0 20 0.65 0.0002 42 0.22 0.21
ZNF593 38076 11400 43 4 4 4 0 0 20 0.66 0.00022 19 0.2 0.22
MYO1B 631560 163020 576 20 14 16 2 0 20 0.84 0.00025 49 0.21 0.24
CRTC1 295944 93480 274 6 6 3 1 0 20 0.45 0.0004 32 0.21 0.37
CDC27 444144 120156 351 18 15 10 6 0 20 1.1 0.00052 42 0.21 0.44
CASP14 124032 34656 102 11 9 8 0 0 20 1.2 0.00055 28 0.22 0.44
CASP8 331968 77748 213 11 10 10 0 0 20 0.88 0.00056 35 0.23 0.44
AKT1S1 54948 16644 54 3 3 3 0 0 20 0.41 0.00066 16 0.2 0.49
PTEN 222072 53352 174 13 8 9 1 0 20 0.78 0.00067 29 0.21 0.49
ESR1 277476 78660 146 12 11 12 0 0 20 0.58 0.00074 31 0.21 0.52
ARL2BP 89376 22344 111 7 6 6 1 0 20 0.99 0.00085 22 0.22 0.57
MAPK10 262428 66120 358 9 9 8 1 0 16 0.8 0.00088 30 0.21 0.57
TXNDC3 330828 80484 294 14 11 14 2 0 20 1.3 0.00094 37 0.23 0.59
MAP7 368448 110580 334 11 11 10 0 0 20 0.84 0.001 37 0.21 0.62
MAPK9 252852 65664 230 7 7 6 1 0 20 0.5 0.0011 28 0.22 0.64
SAT1 95304 22800 117 4 4 2 0 0 20 1 0.0011 21 0.2 0.64
CCBP2 202236 60648 24 11 11 10 0 0 20 0.94 0.0012 27 0.21 0.67
MGC26647 135432 37392 24 7 7 7 0 0 13 1.5 0.0013 27 0.21 0.71
CPXM2 358644 99636 258 13 11 12 1 0 19 0.72 0.0015 34 0.21 0.79
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)