Mutation Analysis (MutSig v1.5)
Skin Cutaneous Melanoma (Metastatic)
23 September 2013  |  analyses__2013_09_23
Maintainer Information
Citation Information
Maintained by Dan DiCara (Broad Institute)
Cite as Broad Institute TCGA Genome Data Analysis Center (2013): Mutation Analysis (MutSig v1.5). Broad Institute of MIT and Harvard. doi:10.7908/C1WH2NBD
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. MutSig v1.5 was used to generate the results found in this report.

  • Working with individual set: SKCM-TM

  • 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
  • MAF used for this analysis:SKCM-TM.final_analysis_set.maf

  • Significantly mutated genes (q ≤ 0.1): 86

  • Mutations seen in COSMIC: 641

  • Significantly mutated genes in COSMIC territory: 42

  • Genes with clustered mutations (≤ 3 aa apart): 1624

  • Significantly mutated genesets: 2

  • Significantly mutated genesets: (excluding sig. mutated genes):0

Mutation Preprocessing
  • Read 228 MAFs of type "Broad"

  • Total number of mutations in input MAFs: 199529

  • After removing 4 mutations outside chr1-24: 199525

  • After removing 3914 noncoding mutations: 195611

Mutation Filtering
  • Number of mutations before filtering: 195611

  • After removing 2649 mutations outside gene set: 192962

  • After removing 179 mutations outside category set: 192783

  • After removing 7 "impossible" mutations in

  • gene-patient-category bins of zero coverage: 189948

Results
Breakdown of Mutations by Type

Table 1.  Get Full Table Table representing breakdown of mutations by type.

type count
Frame_Shift_Del 961
Frame_Shift_Ins 282
In_Frame_Del 413
In_Frame_Ins 57
Missense_Mutation 117592
Nonsense_Mutation 7173
Nonstop_Mutation 49
Silent 64333
Splice_Site 1861
Translation_Start_Site 62
Total 192783
Breakdown of Mutation Rates by Category Type

Table 2.  Get Full Table A breakdown of mutation rates per category discovered for this individual set.

category n N rate rate_per_mb relative_rate exp_ns_s_ratio
(C/T)p*C->T 88967 1812910184 0.000049 49 2.5 1.6
(A/G)p*C->T 9833 1521271502 6.5e-06 6.5 0.33 1.9
A->G 5085 3220290978 1.6e-06 1.6 0.081 2.3
transver 13754 6554472664 2.1e-06 2.1 0.11 5
indel+null 10648 6554472664 1.6e-06 1.6 0.083 NaN
double_null 159 6554472664 2.4e-08 0.024 0.0012 NaN
Total 128446 6554472664 2e-05 20 1 3.5
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: SKCM-TM.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:

  • N = number of sequenced bases in this gene across the individual set

  • n = 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

  • nsil = number of silent mutations in this gene across the individual set

  • n1 = number of nonsilent mutations of type: (C/T)p*C->T

  • n2 = number of nonsilent mutations of type: (A/G)p*C->T

  • n3 = number of nonsilent mutations of type: A->G

  • n4 = number of nonsilent mutations of type: transver

  • n5 = number of nonsilent mutations of type: indel+null

  • n6 = number of nonsilent mutations of type: double_null

  • p_ns_s = p-value for the observed nonsilent/silent ratio being elevated in this gene

  • p = p-value (overall)

  • q = q-value, False Discovery Rate (Benjamini-Hochberg procedure)

Table 3.  Get Full Table A Ranked List of Significantly Mutated Genes. Number of significant genes found: 86. 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).

rank gene description N n npat nsite nsil n1 n2 n3 n4 n5 n6 p_ns_s p q
1 NRAS neuroblastoma RAS viral (v-ras) oncogene homolog 133556 67 67 9 1 2 1 23 41 0 0 8.2e-07 1.7e-15 2.1e-11
2 CDKN2A cyclin-dependent kinase inhibitor 2A (melanoma, p16, inhibits CDK4) 209713 34 34 16 1 10 0 0 2 22 0 0.00036 2.3e-15 2.1e-11
3 BRAF v-raf murine sarcoma viral oncogene homolog B1 505506 123 117 17 3 13 1 5 103 1 0 9.2e-09 4e-15 2.4e-11
4 TP53 tumor protein p53 276551 39 35 33 1 17 0 4 4 14 0 0.000012 7.4e-15 3.4e-11
5 PTEN phosphatase and tensin homolog (mutated in multiple advanced cancers 1) 257977 18 18 16 0 1 0 3 3 11 0 0.046 2.1e-13 7.5e-10
6 ACSM2B acyl-CoA synthetase medium-chain family member 2B 396058 49 38 36 8 39 4 0 2 4 0 0.00012 4.1e-09 0.000012
7 RAC1 ras-related C3 botulinum toxin substrate 1 (rho family, small GTP binding protein Rac1) 140096 17 17 8 1 15 0 0 2 0 0 0.0025 1.4e-08 0.000035
8 LCE1B late cornified envelope 1B 82168 12 12 12 0 8 0 0 2 2 0 0.051 3.4e-08 0.000076
9 NAP1L2 nucleosome assembly protein 1-like 2 311075 27 23 26 2 19 1 3 2 2 0 0.0035 1.2e-07 0.00024
10 MUC7 mucin 7, secreted 259079 22 19 17 1 14 1 6 0 1 0 0.0013 2e-07 0.00037
11 NUDT11 nudix (nucleoside diphosphate linked moiety X)-type motif 11 79804 8 8 1 0 0 0 0 0 8 0 1 2.3e-07 0.00038
12 PPP6C protein phosphatase 6, catalytic subunit 228898 19 18 14 2 13 0 0 2 4 0 0.061 2.7e-07 0.00041
13 HIST1H2AA histone cluster 1, H2aa 91198 10 10 8 0 5 1 0 3 1 0 0.037 1.2e-06 0.0017
14 GRXCR1 glutaredoxin, cysteine rich 1 198611 20 18 18 3 11 2 2 1 4 0 0.04 1.3e-06 0.0017
15 RBM11 RNA binding motif protein 11 148849 13 13 11 0 8 0 0 2 3 0 0.066 1.5e-06 0.0018
16 CDH9 cadherin 9, type 2 (T1-cadherin) 532588 42 33 39 5 33 2 0 4 3 0 0.0056 1.7e-06 0.0019
17 PRB2 proline-rich protein BstNI subfamily 2 283874 41 31 39 2 37 1 1 1 1 0 0.048 1.9e-06 0.0019
18 FUT9 fucosyltransferase 9 (alpha (1,3) fucosyltransferase) 227839 22 22 21 4 16 2 1 3 0 0 0.05 1.9e-06 0.0019
19 GFRAL GDNF family receptor alpha like 272487 38 31 36 9 30 2 0 2 4 0 0.047 3.5e-06 0.0034
20 OR51S1 olfactory receptor, family 51, subfamily S, member 1 221261 30 27 21 8 23 3 0 2 2 0 0.0041 3.8e-06 0.0034
21 TAF1A TATA box binding protein (TBP)-associated factor, RNA polymerase I, A, 48kDa 317552 13 13 7 1 1 0 0 12 0 0 0.35 5.7e-06 0.0049
22 DDX3X DEAD (Asp-Glu-Ala-Asp) box polypeptide 3, X-linked 448287 18 18 17 0 6 1 2 2 7 0 0.019 7e-06 0.0058
23 PARM1 prostate androgen-regulated mucin-like protein 1 202481 18 18 15 2 14 2 0 1 1 0 0.018 0.000016 0.012
24 KRTAP4-8 keratin associated protein 4-8 84189 7 7 6 1 1 0 0 5 1 0 0.46 2e-05 0.015
25 PRR23B proline rich 23B 138502 17 15 17 3 10 5 0 2 0 0 0.026 0.000021 0.015
26 USP17L2 ubiquitin specific peptidase 17-like 2 305433 22 19 19 1 17 0 1 2 2 0 0.0003 0.000022 0.015
27 DEFB118 defensin, beta 118 85857 9 9 8 1 7 0 0 1 1 0 0.23 0.000022 0.015
28 TFEC transcription factor EC 234240 16 15 16 1 13 1 0 1 1 0 0.051 0.000028 0.018
29 NBPF1 neuroblastoma breakpoint family, member 1 733217 55 46 37 10 24 5 1 15 10 0 0.0018 0.000031 0.019
30 HBD hemoglobin, delta 102715 10 10 9 1 8 1 0 1 0 0 0.013 0.000032 0.019
31 OR4N2 olfactory receptor, family 4, subfamily N, member 2 210736 24 22 16 7 22 1 1 0 0 0 0.0024 0.000036 0.02
32 MARCH11 membrane-associated ring finger (C3HC4) 11 143290 11 11 9 1 9 1 0 0 1 0 0.053 0.000036 0.02
33 FRG2B FSHD region gene 2 family, member B 119852 16 16 10 4 12 1 1 2 0 0 0.12 0.000037 0.02
34 VEGFC vascular endothelial growth factor C 269516 19 17 17 2 13 1 0 0 5 0 0.012 0.000042 0.023
35 HHLA2 HERV-H LTR-associating 2 255986 22 17 17 2 18 1 0 0 3 0 0.014 0.000048 0.025
NRAS

Figure S1.  This figure depicts the distribution of mutations and mutation types across the NRAS significant gene.

CDKN2A

Figure S2.  This figure depicts the distribution of mutations and mutation types across the CDKN2A significant gene.

BRAF

Figure S3.  This figure depicts the distribution of mutations and mutation types across the BRAF significant gene.

TP53

Figure S4.  This figure depicts the distribution of mutations and mutation types across the TP53 significant gene.

PTEN

Figure S5.  This figure depicts the distribution of mutations and mutation types across the PTEN significant gene.

ACSM2B

Figure S6.  This figure depicts the distribution of mutations and mutation types across the ACSM2B significant gene.

RAC1

Figure S7.  This figure depicts the distribution of mutations and mutation types across the RAC1 significant gene.

LCE1B

Figure S8.  This figure depicts the distribution of mutations and mutation types across the LCE1B significant gene.

NAP1L2

Figure S9.  This figure depicts the distribution of mutations and mutation types across the NAP1L2 significant gene.

MUC7

Figure S10.  This figure depicts the distribution of mutations and mutation types across the MUC7 significant gene.

PPP6C

Figure S11.  This figure depicts the distribution of mutations and mutation types across the PPP6C significant gene.

HIST1H2AA

Figure S12.  This figure depicts the distribution of mutations and mutation types across the HIST1H2AA significant gene.

GRXCR1

Figure S13.  This figure depicts the distribution of mutations and mutation types across the GRXCR1 significant gene.

RBM11

Figure S14.  This figure depicts the distribution of mutations and mutation types across the RBM11 significant gene.

CDH9

Figure S15.  This figure depicts the distribution of mutations and mutation types across the CDH9 significant gene.

FUT9

Figure S16.  This figure depicts the distribution of mutations and mutation types across the FUT9 significant gene.

GFRAL

Figure S17.  This figure depicts the distribution of mutations and mutation types across the GFRAL significant gene.

OR51S1

Figure S18.  This figure depicts the distribution of mutations and mutation types across the OR51S1 significant gene.

TAF1A

Figure S19.  This figure depicts the distribution of mutations and mutation types across the TAF1A significant gene.

DDX3X

Figure S20.  This figure depicts the distribution of mutations and mutation types across the DDX3X significant gene.

PARM1

Figure S21.  This figure depicts the distribution of mutations and mutation types across the PARM1 significant gene.

KRTAP4-8

Figure S22.  This figure depicts the distribution of mutations and mutation types across the KRTAP4-8 significant gene.

PRR23B

Figure S23.  This figure depicts the distribution of mutations and mutation types across the PRR23B significant gene.

USP17L2

Figure S24.  This figure depicts the distribution of mutations and mutation types across the USP17L2 significant gene.

TFEC

Figure S25.  This figure depicts the distribution of mutations and mutation types across the TFEC significant gene.

NBPF1

Figure S26.  This figure depicts the distribution of mutations and mutation types across the NBPF1 significant gene.

HBD

Figure S27.  This figure depicts the distribution of mutations and mutation types across the HBD significant gene.

OR4N2

Figure S28.  This figure depicts the distribution of mutations and mutation types across the OR4N2 significant gene.

MARCH11

Figure S29.  This figure depicts the distribution of mutations and mutation types across the MARCH11 significant gene.

FRG2B

Figure S30.  This figure depicts the distribution of mutations and mutation types across the FRG2B significant gene.

COSMIC analyses

In this analysis, COSMIC is used as a filter to increase power by restricting the territory of each gene. Cosmic version: v48.

Table 4.  Get Full Table Significantly mutated genes (COSMIC territory only). To access the database please go to: COSMIC. Number of significant genes found: 42. Number of genes displayed: 10

rank gene description n cos n_cos N_cos cos_ev p q
1 STK19 serine/threonine kinase 19 13 2 6 456 12 1.9e-14 8.7e-11
2 IDH1 isocitrate dehydrogenase 1 (NADP+), soluble 12 5 10 1140 14920 4.5e-14 1e-10
3 NRAS neuroblastoma RAS viral (v-ras) oncogene homolog 67 33 65 7524 80983 2.6e-13 4e-10
4 BRAF v-raf murine sarcoma viral oncogene homolog B1 123 89 116 20292 1494071 5.5e-13 5.3e-10
5 TP53 tumor protein p53 39 356 37 81168 3489 6.7e-13 5.3e-10
6 CDKN2A cyclin-dependent kinase inhibitor 2A (melanoma, p16, inhibits CDK4) 34 332 34 75696 1296 7e-13 5.3e-10
7 EPHA6 EPH receptor A6 60 8 5 1824 5 4.7e-10 3e-07
8 EPHA7 EPH receptor A7 42 13 5 2964 5 5.2e-09 3e-06
9 PTEN phosphatase and tensin homolog (mutated in multiple advanced cancers 1) 18 767 18 174876 374 2.6e-08 0.000013
10 NF1 neurofibromin 1 (neurofibromatosis, von Recklinghausen disease, Watson disease) 40 285 11 64980 25 1.1e-07 0.000048

Note:

n - number of (nonsilent) mutations in this gene across the individual set.

cos = number of unique mutated sites in this gene in COSMIC

n_cos = overlap between n and cos.

N_cos = number of individuals times cos.

cos_ev = total evidence: number of reports in COSMIC for mutations seen in this gene.

p = p-value for seeing the observed amount of overlap in this gene)

q = q-value, False Discovery Rate (Benjamini-Hochberg procedure)

Clustered Mutations

Table 5.  Get Full Table Genes with Clustered Mutations

num gene desc n mindist nmuts0 nmuts3 nmuts12 npairs0 npairs3 npairs12
1349 BRAF v-raf murine sarcoma viral oncogene homolog B1 123 0 3584 4031 4125 3584 4031 4125
9285 NRAS neuroblastoma RAS viral (v-ras) oncogene homolog 67 0 1602 1606 1612 1602 1606 1612
8700 MUC16 mucin 16, cell surface associated 757 0 109 232 599 109 232 599
14649 TTN titin 1051 0 91 147 374 91 147 374
3989 DNAH5 dynein, axonemal, heavy chain 5 307 0 86 128 338 86 128 338
10148 PCLO piccolo (presynaptic cytomatrix protein) 264 0 58 104 237 58 104 237
11358 RAC1 ras-related C3 botulinum toxin substrate 1 (rho family, small GTP binding protein Rac1) 17 0 55 55 67 55 55 67
6487 IDH1 isocitrate dehydrogenase 1 (NADP+), soluble 12 0 45 45 45 45 45 45
13921 THSD7B thrombospondin, type I, domain containing 7B 121 0 35 75 157 35 75 157
11224 PTPRT protein tyrosine phosphatase, receptor type, T 101 0 34 52 130 34 52 130

Note:

n - number of mutations in this gene in the individual set.

mindist - distance (in aa) between closest pair of mutations in this gene

npairs3 - how many pairs of mutations are within 3 aa of each other.

npairs12 - how many pairs of mutations are within 12 aa of each other.

Geneset Analyses

Table 6.  Get Full Table A Ranked List of Significantly Mutated Genesets. (Source: MSigDB GSEA Cannonical Pathway Set).Number of significant genesets found: 2. Number of genesets displayed: 10

rank geneset description genes N_genes mut_tally N n npat nsite nsil n1 n2 n3 n4 n5 n6 p_ns_s p q
1 SA_G1_AND_S_PHASES Cdk2, 4, and 6 bind cyclin D in G1, while cdk2/cyclin E promotes the G1/S transition. ARF1, ARF3, CCND1, CDK2, CDK4, CDKN1A, CDKN1B, CDKN2A, CFL1, E2F1, E2F2, MDM2, NXT1, PRB1, TP53 15 CCND1(1), CDK4(5), CDKN1A(4), CDKN1B(1), CDKN2A(34), CFL1(1), E2F1(5), E2F2(4), MDM2(3), NXT1(2), PRB1(29), TP53(39) 2837450 128 80 100 16 62 3 6 17 40 0 2.2e-09 2.7e-06 0.0017
2 ST_G_ALPHA_S_PATHWAY The G-alpha-s protein activates adenylyl cyclases, which catalyze cAMP formation. ASAH1, BF, BFAR, BRAF, CAMP, CREB1, CREB3, CREB5, EPAC, GAS, GRF2, MAPK1, RAF1, SNX13, SRC, TERF2IP 12 BRAF(123), CAMP(1), CREB3(1), CREB5(9), MAPK1(4), RAF1(8), SNX13(1), SRC(1), TERF2IP(1) 3751054 149 130 43 30 28 4 6 107 4 0 0.02 0.00016 0.048
3 SA_REG_CASCADE_OF_CYCLIN_EXPR Expression of cyclins regulates progression through the cell cycle by activating cyclin-dependent kinases. CCNA1, CCNA2, CCND1, CCNE1, CCNE2, CDK2, CDK4, CDKN1B, CDKN2A, E2F1, E2F2, E2F4, PRB1 13 CCNA1(13), CCND1(1), CCNE1(4), CCNE2(12), CDK4(5), CDKN1B(1), CDKN2A(34), E2F1(5), E2F2(4), E2F4(1), PRB1(29) 3023744 109 77 83 17 61 0 4 19 25 0 2.4e-06 0.024 1
4 HSA00472_D_ARGININE_AND_D_ORNITHINE_METABOLISM Genes involved in D-arginine and D-ornithine metabolism DAO 1 DAO(10) 240807 10 10 10 2 7 1 1 1 0 0 0.12 0.11 1
5 TERTPATHWAY hTERC, the RNA subunit of telomerase, and hTERT, the catalytic protein subunit, are required for telomerase activity and are overexpressed in many cancers. HDAC1, MAX, MYC, SP1, SP3, TP53, WT1, ZNF42 7 HDAC1(1), MYC(5), SP1(5), SP3(1), TP53(39), WT1(5) 2379389 56 44 50 8 26 2 7 6 15 0 0.00078 0.24 1
6 ARFPATHWAY Cyclin-dependent kinase inhibitor 2A is a tumor suppressor that induces G1 arrest and can activate the p53 pathway, leading to G2/M arrest. ABL1, CDKN2A, E2F1, MDM2, MYC, PIK3CA, PIK3R1, POLR1A, POLR1B, POLR1C, POLR1D, RAC1, RB1, TBX2, TP53, TWIST1 16 ABL1(12), CDKN2A(34), E2F1(5), MDM2(3), MYC(5), PIK3CA(8), PIK3R1(3), POLR1A(11), POLR1B(8), POLR1C(1), RAC1(17), RB1(8), TBX2(6), TP53(39), TWIST1(1) 6784714 161 96 127 24 84 8 6 17 43 3 8.2e-10 0.46 1
7 HSA00627_1,4_DICHLOROBENZENE_DEGRADATION Genes involved in 1,4-dichlorobenzene degradation CMBL 1 CMBL(4) 172740 4 4 4 1 4 0 0 0 0 0 0.48 0.47 1
8 FOSBPATHWAY FOSB gene expression and drug abuse CDK5, FOSB, GRIA2, JUND, PPP1R1B 5 CDK5(4), FOSB(5), GRIA2(34), JUND(1), PPP1R1B(2) 1226014 46 39 43 15 28 3 2 6 7 0 0.069 0.83 1
9 HSA00401_NOVOBIOCIN_BIOSYNTHESIS Genes involved in novobiocin biosynthesis GOT1, GOT2, TAT 3 GOT1(6), GOT2(5), TAT(17) 883649 28 18 27 7 21 2 2 1 2 0 0.015 0.88 1
10 SLRPPATHWAY Small leucine-rich proteoglycans (SLRPs) interact with and reorganize collagen fibers in the extracellular matrix. BGN, DCN, DSPG3, FMOD, KERA, LUM 5 BGN(6), DCN(17), FMOD(4), KERA(14), LUM(11) 1178331 52 38 48 16 41 4 3 1 3 0 0.0018 0.89 1

Table 7.  Get Full Table A Ranked List of Significantly Mutated Genesets (Excluding Significantly Mutated Genes). Number of significant genesets found: 0. Number of genesets displayed: 10

rank geneset description genes N_genes mut_tally N n npat nsite nsil n1 n2 n3 n4 n5 n6 p_ns_s p q
1 HSA00472_D_ARGININE_AND_D_ORNITHINE_METABOLISM Genes involved in D-arginine and D-ornithine metabolism DAO 1 DAO(10) 240807 10 10 10 2 7 1 1 1 0 0 0.12 0.11 1
2 HSA00627_1,4_DICHLOROBENZENE_DEGRADATION Genes involved in 1,4-dichlorobenzene degradation CMBL 1 CMBL(4) 172740 4 4 4 1 4 0 0 0 0 0 0.48 0.47 1
3 FOSBPATHWAY FOSB gene expression and drug abuse CDK5, FOSB, GRIA2, JUND, PPP1R1B 5 CDK5(4), FOSB(5), GRIA2(34), JUND(1), PPP1R1B(2) 1226014 46 39 43 15 28 3 2 6 7 0 0.069 0.83 1
4 HSA00401_NOVOBIOCIN_BIOSYNTHESIS Genes involved in novobiocin biosynthesis GOT1, GOT2, TAT 3 GOT1(6), GOT2(5), TAT(17) 883649 28 18 27 7 21 2 2 1 2 0 0.015 0.88 1
5 SLRPPATHWAY Small leucine-rich proteoglycans (SLRPs) interact with and reorganize collagen fibers in the extracellular matrix. BGN, DCN, DSPG3, FMOD, KERA, LUM 5 BGN(6), DCN(17), FMOD(4), KERA(14), LUM(11) 1178331 52 38 48 16 41 4 3 1 3 0 0.0018 0.89 1
6 PEPIPATHWAY Proepithelin (PEPI) induces epithelial cells to secrete IL-8, which promotes elastase secretion by neutrophils. ELA1, ELA2, ELA2A, ELA2B, ELA3B, GRN, IL8, SLPI 3 GRN(4), IL8(1), SLPI(6) 576974 11 11 11 4 5 1 0 4 1 0 0.44 0.92 1
7 BOTULINPATHWAY Blockade of Neurotransmitter Relase by Botulinum Toxin CHRM1, CHRNA1, SNAP25, STX1A, VAMP2 5 CHRM1(5), CHRNA1(5), SNAP25(6), STX1A(2) 1097766 18 15 15 3 12 1 0 1 4 0 0.01 0.95 1
8 HSA00785_LIPOIC_ACID_METABOLISM Genes involved in lipoic acid metabolism LIAS, LIPT1, LOC387787 2 LIAS(2), LIPT1(2) 519728 4 3 4 0 0 2 0 1 1 0 0.33 0.95 1
9 1_AND_2_METHYLNAPHTHALENE_DEGRADATION ADH1A, ADH1A, ADH1B, ADH1C, ADH1B, ADH1C, ADH4, ADH6, ADH7, ADHFE1 6 ADH1A(14), ADH1B(27), ADH4(11), ADH6(11), ADH7(13), ADHFE1(5) 1631130 81 59 69 24 65 4 5 5 2 0 0.004 0.96 1
10 INOSITOL_METABOLISM ALDH6A1, ALDOA, ALDOB, ALDOC, TPI1 5 ALDH6A1(3), ALDOA(2), ALDOB(12), ALDOC(3) 1324868 20 15 17 4 15 2 0 1 2 0 0.014 0.97 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)