Mutation Analysis (MutSigCV v0.9)

Colon Adenocarcinoma (Primary solid tumor)

15 July 2014 | analyses__2014_07_15

Maintainer Information

Citation Information

Maintained by David Heiman (Broad Institute)

Cite as Broad Institute TCGA Genome Data Analysis Center (2014): Mutation Analysis (MutSigCV v0.9). Broad Institute of MIT and Harvard. doi:10.7908/C1028Q7M

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: COAD-TP
Number of patients in set: 154

Input

The input for this pipeline is a set of individuals with the following files associated for each:

An annotated .maf file describing the mutations called for the respective individual, and their properties.
A .wig file that contains information about the coverage of the sample.

Summary

MAF used for this analysis:COAD-TP.final_analysis_set.maf
Blacklist used for this analysis: pancan_mutation_blacklist.v14.hg19.txt
Significantly mutated genes (q ≤ 0.1): 12

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). If the figure is unpopulated, then full coverage is assumed (e.g. MutSig CV doesn't use WIGs and assumes full coverage).

Figure 1.

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

Figure 2. Patients counts and rates file used to generate this plot: COAD-TP.patients.counts_and_rates.txt

Lego Plots

The mutation spectrum is depicted in the lego plots below in which the 96 possible mutation types are subdivided into six large blocks, color-coded to reflect the base substitution type. Each large block is further subdivided into the 16 possible pairs of 5' and 3' neighbors, as listed in the 4x4 trinucleotide context legend. The height of each block corresponds to the mutation frequency for that kind of mutation (counts of mutations normalized by the base coverage in a given bin). The shape of the spectrum is a signature for dominant mutational mechanisms in different tumor types.

Figure 3. Get High-res Image SNV Mutation rate lego plot for entire set. Each bin is normalized by base coverage for that bin. Colors represent the six SNV types on the upper right. The three-base context for each mutation is labeled in the 4x4 legend on the lower right. The fractional breakdown of SNV counts is shown in the pie chart on the upper left. If this figure is blank, not enough information was provided in the MAF to generate it.

Figure 4. Get High-res Image SNV Mutation rate lego plots for 4 slices of mutation allele fraction (0<=AF<0.1, 0.1<=AF<0.25, 0.25<=AF<0.5, & 0.5<=AF) . The color code and three-base context legends are the same as the previous figure. If this figure is blank, not enough information was provided in the MAF to generate it.

CoMut Plot

Figure 5. 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: 12. 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	nnei	fMLE	p	score	time	q
KRAS	93170	22792	106	59	59	9	0	1	0	0	130	0.09	0
APC	1027488	287980	291	163	107	108	4	4	1	1e-15	490	0.095	9.1e-12
TP53	145530	42504	206	76	74	50	1	4	1	1.8e-15	240	0.091	1.1e-11
FBXW7	299068	82082	239	33	29	21	2	20	1.5	1.9e-13	86	0.09	8.7e-10
NRAS	70994	18788	82	15	15	7	0	20	0.59	5.4e-11	47	0.087	2e-07
FAM123B	381304	113036	98	19	19	17	1	20	2	1.1e-08	79	0.089	0.000033
SMAD4	203896	56826	222	22	18	18	0	20	1.2	1.5e-08	56	0.087	0.000039
SOX9	145068	42658	52	9	9	9	0	20	1.5	5.1e-07	48	0.087	0.0012
PIK3CA	400246	102410	396	33	26	18	1	20	1.2	1.2e-06	57	0.091	0.0024
BRAF	265958	75922	339	21	20	3	0	19	1.2	0.000013	44	0.087	0.023
ACVR2A	191576	50512	222	10	9	8	1	10	1.1	0.000022	38	0.085	0.036
TXNDC3	223454	54362	294	13	10	13	2	20	1.1	0.000061	38	0.086	0.093
SMAD2	172018	48048	199	11	10	8	1	20	1.4	0.0001	36	0.086	0.14
CASP8	224224	52514	213	11	10	10	0	20	0.88	0.00013	34	0.087	0.17
TCF7L2	228690	64526	273	13	11	13	3	20	1.4	0.00033	38	0.087	0.4
MGC26647	91476	25256	24	7	7	7	0	13	1.4	0.00035	26	0.084	0.4
SAT1	64372	15400	117	4	4	2	0	20	0.91	0.00037	21	0.08	0.4
WBSCR17	212674	61292	211	17	17	16	2	18	1.5	0.00042	41	0.09	0.4
CCDC160	59906	14476	5	7	5	7	0	20	1.2	0.00045	19	0.079	0.4
ESR1	187418	53130	146	12	11	12	0	20	0.68	0.00046	30	0.084	0.4
MIER3	205128	52822	236	10	10	10	0	20	1.1	0.00046	32	0.087	0.4
ZNF593	25718	7700	43	3	3	3	0	20	0.75	0.001	15	0.077	0.85
TBC1D10C	86240	28644	92	4	4	2	0	20	1.1	0.0013	23	0.083	1
TMEM105	40964	14476	35	3	3	3	0	19	0.4	0.0017	15	0.076	1
CRTC1	199892	63140	274	5	5	3	1	20	0.45	0.0017	25	0.083	1
ELF3	136906	37576	158	5	5	5	0	20	0.82	0.0019	24	0.082	1
C6orf211	163548	41580	100	5	5	5	0	19	0.41	0.002	20	0.081	1
RNF43	256410	81158	175	11	10	10	1	8	0.64	0.0021	27	0.085	1
CELA1	83776	24948	138	6	5	6	0	20	1.1	0.0021	20	0.08	1
INSL6	76846	21098	40	5	5	5	1	20	0.91	0.0022	18	0.08	1
GGA2	216062	62370	320	8	8	8	1	20	0.91	0.0026	28	0.097	1
OR2M4	109956	33418	27	8	8	8	0	19	1.7	0.0026	24	0.084	1
HSPA1L	245784	74074	35	8	8	8	1	20	0.32	0.0039	23	0.096	1
B2M	44198	12320	64	3	3	3	0	20	1.1	0.0046	14	0.076	1
SLC16A7	171094	50050	82	10	8	9	2	20	1.8	0.0046	28	0.084	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

In addition to the links below, the full results of the analysis summarized in this report can also be downloaded programmatically using firehose_get, or interactively from either the Broad GDAC website or TCGA Data Coordination Center Portal.

References

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

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