Mutation Analysis (MutSig v2.0)
Kidney Renal Papillary Cell Carcinoma (Primary solid tumor)
28 January 2016  |  analyses__2016_01_28
Maintainer Information
Citation Information
doi:10.7908/C1F47NJ5
Maintained by David Heiman (Broad Institute)
Cite as Broad Institute TCGA Genome Data Analysis Center (2016): Mutation Analysis (MutSig v2.0). Broad Institute of MIT and Harvard. doi:10.7908/C1F47NJ5
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 v2.0 was used to generate the results found in this report.

  • Working with individual set: KIRP-TP

  • Number of patients in set: 282

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:KIRP-TP.final_analysis_set.maf

  • Blacklist used for this analysis: pancan_mutation_blacklist.v14.hg19.txt

  • Significantly mutated genes (q ≤ 0.1): 30

  • Mutations seen in COSMIC: 82

  • Significantly mutated genes in COSMIC territory: 11

  • Significantly mutated genesets: 1

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

Mutation Preprocessing

  • Read 282 MAFs of type "maf1"

  • Total number of mutations in input MAFs: 18668

  • After removing 123 mutations outside chr1-24: 18545

  • After removing 146 blacklisted mutations: 18399

  • After removing 388 noncoding mutations: 18011

  • After collapsing adjacent/redundant mutations: 17948

Mutation Filtering

  • Number of mutations before filtering: 17948

  • After removing 984 mutations outside gene set: 16964

  • After removing 64 mutations outside category set: 16900

  • After removing 9 "impossible" mutations in

  • gene-patient-category bins of zero coverage: 15843

Results
Breakdown of Mutations by Type

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

type count
De_novo_Start_OutOfFrame 3
Frame_Shift_Del 1334
Frame_Shift_Ins 448
In_Frame_Del 269
In_Frame_Ins 61
Missense_Mutation 9786
Nonsense_Mutation 562
Nonstop_Mutation 21
Silent 3675
Splice_Site 710
Start_Codon_Del 5
Start_Codon_SNP 20
Stop_Codon_Del 5
Stop_Codon_Ins 1
Total 16900
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
*CpG->T 871 495087687 1.8e-06 1.8 1.2 2.1
*Cp(A/C/T)->T 1659 3948225432 4.2e-07 0.42 0.28 1.7
A->G 1858 4224865722 4.4e-07 0.44 0.29 2.3
transver 5414 8668178841 6.2e-07 0.62 0.41 5
indel+null 3358 8668178841 3.9e-07 0.39 0.25 NaN
double_null 58 8668178841 6.7e-09 0.0067 0.0044 NaN
Total 13218 8668178841 1.5e-06 1.5 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). 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: KIRP-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:

  • 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: *CpG->T

  • n2 = number of nonsilent mutations of type: *Cp(A/C/T)->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_classic = p-value for the observed amount of nonsilent mutations being elevated in this gene

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

  • p_cons = p-value for enrichment of mutations at evolutionarily most-conserved sites in gene

  • p_joint = p-value for clustering + conservation

  • 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: 30. 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_classic p_ns_s p_clust p_cons p_joint p q
1 MET met proto-oncogene (hepatocyte growth factor receptor) 1189739 22 21 14 0 0 7 7 7 1 0 9.2e-15 0.001 0 0.000082 0 <1.00e-15 <3.12e-12
2 AR androgen receptor (dihydrotestosterone receptor; testicular feminization; spinal and bulbar muscular atrophy; Kennedy disease) 630521 16 13 9 1 0 2 1 13 0 0 1e-10 0.086 0 1 0 <1.00e-15 <3.12e-12
3 PCF11 PCF11, cleavage and polyadenylation factor subunit, homolog (S. cerevisiae) 1206056 12 11 9 2 0 2 7 3 0 0 0.00015 0.088 0 0.98 0 <1.00e-15 <3.12e-12
4 ZNF814 zinc finger protein 814 432631 12 9 5 0 0 6 0 4 2 0 3.2e-08 0.064 0 0.61 0 <1.00e-15 <3.12e-12
5 KRAS v-Ki-ras2 Kirsten rat sarcoma viral oncogene homolog 193814 5 5 1 0 0 3 0 2 0 0 7.4e-07 0.29 0 0.023 0 <1.00e-15 <3.12e-12
6 KCNK5 potassium channel, subfamily K, member 5 408980 3 3 3 0 0 0 0 0 3 0 0.006 0.33 0.055 0 0 <1.00e-15 <3.12e-12
7 MUC4 mucin 4, cell surface associated 944051 18 14 18 0 4 1 0 9 3 1 9.8e-11 0.016 0.18 0.5 0.42 1.03e-09 2.75e-06
8 BAP1 BRCA1 associated protein-1 (ubiquitin carboxy-terminal hydrolase) 595128 12 10 12 1 0 0 1 4 7 0 1.2e-08 0.46 0.0032 0.7 0.0079 2.25e-09 5.26e-06
9 NF2 neurofibromin 2 (merlin) 483605 10 10 10 0 0 0 0 1 9 0 5.1e-09 0.18 0.012 0.38 0.024 2.88e-09 5.98e-06
10 CUL3 cullin 3 650974 11 10 10 0 0 0 1 3 6 1 3.2e-08 0.12 0.3 0.98 0.45 2.76e-07 0.000513
11 ATP1B1 ATPase, Na+/K+ transporting, beta 1 polypeptide 259259 7 7 7 0 0 0 2 2 3 0 2.4e-08 0.37 0.48 0.3 0.65 3.01e-07 0.000513
12 SETD2 SET domain containing 2 1991508 17 16 17 1 0 1 0 4 11 1 6.8e-08 0.41 0.82 0.22 0.59 7.20e-07 0.00112
13 KRTAP4-5 keratin associated protein 4-5 140695 5 5 4 0 1 0 0 3 1 0 1.2e-06 0.61 0.014 0.87 0.048 1.03e-06 0.00148
14 SMARCA4 SWI/SNF related, matrix associated, actin dependent regulator of chromatin, subfamily a, member 4 1304135 11 10 11 1 1 0 2 7 1 0 0.000056 0.32 0.0015 0.21 0.0017 1.66e-06 0.00222
15 PARD6B par-6 partitioning defective 6 homolog beta (C. elegans) 298180 7 7 7 0 0 0 4 1 2 0 1.4e-07 0.088 0.89 0.4 0.75 1.85e-06 0.00224
16 TP53 tumor protein p53 357058 7 7 7 0 0 0 1 4 2 0 7.2e-07 0.21 0.15 0.15 0.17 2.03e-06 0.00224
17 SAV1 salvador homolog 1 (Drosophila) 323407 7 6 7 0 0 0 0 2 5 0 5.2e-07 0.59 0.12 0.99 0.23 2.04e-06 0.00224
18 PTEN phosphatase and tensin homolog (mutated in multiple advanced cancers 1) 343679 7 7 7 0 0 0 2 0 4 1 2.5e-07 0.32 0.49 0.91 0.63 2.62e-06 0.00272
19 NEFH neurofilament, heavy polypeptide 200kDa 590820 7 6 6 0 0 0 0 1 6 0 0.00014 0.84 0.00054 0.74 0.002 4.59e-06 0.00452
20 NFE2L2 nuclear factor (erythroid-derived 2)-like 2 505966 6 6 6 0 0 0 1 5 0 0 0.0001 0.29 0.014 0.03 0.0031 4.96e-06 0.00464
21 SMARCB1 SWI/SNF related, matrix associated, actin dependent regulator of chromatin, subfamily b, member 1 328224 6 6 5 0 1 1 0 0 4 0 4.1e-06 0.33 0.11 0.88 0.2 1.22e-05 0.0109
22 FAM20C family with sequence similarity 20, member C 132140 5 5 5 1 0 1 1 1 2 0 1.9e-06 0.39 0.36 0.62 0.51 1.44e-05 0.0122
23 KRTAP5-4 keratin associated protein 5-4 115571 3 3 3 0 0 0 1 0 2 0 0.000076 0.74 0.27 0.018 0.026 2.74e-05 0.0223
24 KDM6A lysine (K)-specific demethylase 6A 1088765 10 10 10 0 0 0 0 1 8 1 2.1e-06 0.32 0.9 0.6 1 2.94e-05 0.0229
25 PBRM1 polybromo 1 1394577 11 11 11 0 0 0 1 2 7 1 4.4e-06 0.19 0.82 0.73 1 5.93e-05 0.0444
26 RIMBP3B RIMS binding protein 3B 1292036 4 4 1 0 0 0 0 0 4 0 0.072 1 1e-06 0.65 0.00011 9.90e-05 0.0712
27 CNTNAP5 contactin associated protein-like 5 1022046 8 8 8 1 1 2 0 4 1 0 0.00011 0.38 0.043 0.55 0.078 0.000106 0.0735
28 NR2F2 nuclear receptor subfamily 2, group F, member 2 305604 5 5 5 0 0 0 2 2 1 0 7e-05 0.46 0.11 0.39 0.14 0.000126 0.0815
29 KRT2 keratin 2 (epidermal ichthyosis bullosa of Siemens) 525430 5 5 4 0 0 0 0 2 3 0 0.0014 0.67 0.054 0.015 0.0075 0.000128 0.0815
30 TXNIP thioredoxin interacting protein 340061 3 3 3 0 0 1 0 0 2 0 0.0026 0.63 0.0035 0.29 0.0041 0.000131 0.0815
31 IL32 interleukin 32 159460 4 4 4 0 0 1 0 2 1 0 0.000039 0.44 0.23 0.51 0.38 0.000180 0.108
32 SHANK3 SH3 and multiple ankyrin repeat domains 3 786253 6 6 6 0 1 2 1 2 0 0 0.0013 0.1 0.0097 0.54 0.017 0.000266 0.156
33 KRT10 keratin 10 (epidermolytic hyperkeratosis; keratosis palmaris et plantaris) 434029 3 2 2 0 1 2 0 0 0 0 0.041 0.28 0.00011 1 0.00096 0.000439 0.249
34 GXYLT1 glucoside xylosyltransferase 1 315252 4 4 3 0 0 2 1 0 1 0 0.00017 0.34 0.12 0.64 0.24 0.000453 0.250
35 RTKN rhotekin 501559 3 3 3 1 0 0 3 0 0 0 0.008 0.75 0.068 0.0034 0.0055 0.000486 0.260
MET

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

AR

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

PCF11

Figure S3.  This figure depicts the distribution of mutations and mutation types across the PCF11 significant gene.

ZNF814

Figure S4.  This figure depicts the distribution of mutations and mutation types across the ZNF814 significant gene.

KRAS

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

KCNK5

Figure S6.  This figure depicts the distribution of mutations and mutation types across the KCNK5 significant gene.

MUC4

Figure S7.  This figure depicts the distribution of mutations and mutation types across the MUC4 significant gene.

BAP1

Figure S8.  This figure depicts the distribution of mutations and mutation types across the BAP1 significant gene.

NF2

Figure S9.  This figure depicts the distribution of mutations and mutation types across the NF2 significant gene.

CUL3

Figure S10.  This figure depicts the distribution of mutations and mutation types across the CUL3 significant gene.

ATP1B1

Figure S11.  This figure depicts the distribution of mutations and mutation types across the ATP1B1 significant gene.

SETD2

Figure S12.  This figure depicts the distribution of mutations and mutation types across the SETD2 significant gene.

KRTAP4-5

Figure S13.  This figure depicts the distribution of mutations and mutation types across the KRTAP4-5 significant gene.

SMARCA4

Figure S14.  This figure depicts the distribution of mutations and mutation types across the SMARCA4 significant gene.

PARD6B

Figure S15.  This figure depicts the distribution of mutations and mutation types across the PARD6B significant gene.

TP53

Figure S16.  This figure depicts the distribution of mutations and mutation types across the TP53 significant gene.

SAV1

Figure S17.  This figure depicts the distribution of mutations and mutation types across the SAV1 significant gene.

PTEN

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

NEFH

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

NFE2L2

Figure S20.  This figure depicts the distribution of mutations and mutation types across the NFE2L2 significant gene.

SMARCB1

Figure S21.  This figure depicts the distribution of mutations and mutation types across the SMARCB1 significant gene.

FAM20C

Figure S22.  This figure depicts the distribution of mutations and mutation types across the FAM20C significant gene.

KRTAP5-4

Figure S23.  This figure depicts the distribution of mutations and mutation types across the KRTAP5-4 significant gene.

KDM6A

Figure S24.  This figure depicts the distribution of mutations and mutation types across the KDM6A significant gene.

PBRM1

Figure S25.  This figure depicts the distribution of mutations and mutation types across the PBRM1 significant gene.

RIMBP3B

Figure S26.  This figure depicts the distribution of mutations and mutation types across the RIMBP3B significant gene.

CNTNAP5

Figure S27.  This figure depicts the distribution of mutations and mutation types across the CNTNAP5 significant gene.

NR2F2

Figure S28.  This figure depicts the distribution of mutations and mutation types across the NR2F2 significant gene.

KRT2

Figure S29.  This figure depicts the distribution of mutations and mutation types across the KRT2 significant gene.

TXNIP

Figure S30.  This figure depicts the distribution of mutations and mutation types across the TXNIP 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: 11. Number of genes displayed: 10

rank gene description n cos n_cos N_cos cos_ev p q
1 MET met proto-oncogene (hepatocyte growth factor receptor) 22 34 10 9588 48 0 0
2 KRAS v-Ki-ras2 Kirsten rat sarcoma viral oncogene homolog 5 52 5 14664 73020 4.5e-11 1e-07
3 TP53 tumor protein p53 7 356 6 100392 483 1.6e-08 0.000023
4 FGFR3 fibroblast growth factor receptor 3 (achondroplasia, thanatophoric dwarfism) 6 62 4 17484 1811 2.1e-08 0.000023
5 PIK3CA phosphoinositide-3-kinase, catalytic, alpha polypeptide 6 220 5 62040 1661 5.8e-08 0.000048
6 PTEN phosphatase and tensin homolog (mutated in multiple advanced cancers 1) 7 767 7 216294 75 6.3e-08 0.000048
7 SMARCB1 SWI/SNF related, matrix associated, actin dependent regulator of chromatin, subfamily b, member 1 6 129 4 36378 12 3.8e-07 0.00024
8 NF2 neurofibromin 2 (merlin) 10 550 5 155100 21 5.1e-06 0.0029
9 BRAF v-raf murine sarcoma viral oncogene homolog B1 4 89 3 25098 28754 9.1e-06 0.0046
10 SMARCA4 SWI/SNF related, matrix associated, actin dependent regulator of chromatin, subfamily a, member 4 11 30 2 8460 3 0.000082 0.037

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)

Geneset Analyses

Table 5.  Get Full Table A Ranked List of Significantly Mutated Genesets. (Source: MSigDB GSEA Cannonical Pathway Set).Number of significant genesets found: 1. 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 CBLPATHWAY Activated EGF receptors undergo endocytosis into clathrin-coated vesicles, where they are recycled to the membrane or ubiquitinated by Cbl. CBL, CSF1R, EGF, EGFR, GRB2, MET, PDGFRA, PRKCA, PRKCB1, SH3GLB1, SH3GLB2, SH3KBP1, SRC 12 CSF1R(3), EGF(1), EGFR(1), GRB2(1), MET(22), PDGFRA(1), PRKCA(1), SH3KBP1(2) 8180436 32 28 24 2 2 8 8 11 3 0 0.0041 0.000047 0.029
2 ARGININECPATHWAY Related catabolic pathways process arginine, histidine, glutamine, and proline through glutamate to alpha-ketoglutamate, which feeds into the citric acid cycle. ALDH4A1, ARG1, GLS, GLUD1, OAT, PRODH 6 ALDH4A1(1), ARG1(1), GLS(5), GLUD1(1), OAT(2) 2436277 10 10 10 0 0 0 6 1 3 0 0.098 0.0025 0.5
3 HSA00627_1,4_DICHLOROBENZENE_DEGRADATION Genes involved in 1,4-dichlorobenzene degradation CMBL 1 CMBL(3) 213542 3 3 3 0 0 0 0 1 2 0 0.86 0.0031 0.5
4 ERBB4PATHWAY ErbB4 (aka HER4) is a receptor tyrosine kinase that binds neuregulins as well as members of the EGF family, which also target EGF receptors. ADAM17, ERBB4, NRG2, NRG3, PRKCA, PRKCB1, PSEN1 6 ADAM17(3), ERBB4(4), NRG2(1), NRG3(3), PRKCA(1), PSEN1(1) 3787830 13 13 13 1 1 2 1 6 3 0 0.17 0.0033 0.5
5 HSA00550_PEPTIDOGLYCAN_BIOSYNTHESIS Genes involved in peptidoglycan biosynthesis GLUL, PGLYRP2 2 GLUL(2), PGLYRP2(3) 757351 5 5 5 1 1 0 0 3 1 0 0.72 0.0044 0.54
6 PARKINPATHWAY In Parkinson's disease, dopaminergic neurons contain Lewy bodies consisting of alpha-synuclein and parkin, an E3 ubiquitin ligase that targets glycosylated alpha-synuclein. GPR37, PARK2, PNUTL1, SNCA, SNCAIP, UBE2E2, UBE2F, UBE2G1, UBE2G2, UBE2L3, UBE2L6, UBL1 10 GPR37(4), PARK2(2), SNCAIP(3), UBE2L3(1) 2673213 10 10 10 1 0 1 1 6 2 0 0.28 0.0075 0.77
7 SA_PTEN_PATHWAY PTEN is a tumor suppressor that dephosphorylates the lipid messenger phosphatidylinositol triphosphate. AKT1, AKT2, AKT3, BPNT1, GRB2, ILK, MAPK1, MAPK3, PDK1, PIK3CA, PIK3CD, PIP3-E, PTEN, PTK2B, RBL2, SHC1, SOS1 16 AKT2(1), AKT3(1), BPNT1(3), GRB2(1), MAPK1(1), PIK3CA(6), PIK3CD(1), PTEN(7), PTK2B(1), SOS1(2) 8543628 24 21 22 2 2 5 3 5 8 1 0.031 0.0088 0.78
8 ARENRF2PATHWAY Nrf1 and nrf2 are transcription factors that bind to antioxidant response elements (AREs), promoters of genes involved in oxidative damage control. CREB1, FOS, FXYD2, JUN, KEAP1, MAFF, MAFG, MAFK, MAPK1, MAPK14, MAPK8, NFE2L2, PRKCA, PRKCB1 13 CREB1(1), KEAP1(2), MAPK1(1), MAPK14(1), NFE2L2(6), PRKCA(1) 3800165 12 12 12 1 1 0 1 7 3 0 0.23 0.019 1
9 GLUTAMATE_METABOLISM ABAT, ALDH4A1, ALDH5A1, CAD, CPS1, EPRS, GAD1, GAD2, GCLC, GCLM, GFPT1, GLS, GLS2, GLUD1, GLUL, GMPS, GOT1, GOT2, GPT, GPT2, GSS, NADSYN1, PPAT, QARS 24 ABAT(1), ALDH4A1(1), CAD(4), CPS1(1), EPRS(1), GAD1(2), GAD2(2), GCLC(3), GCLM(1), GFPT1(2), GLS(5), GLUD1(1), GLUL(2), GMPS(1), GOT2(1), GPT(2), PPAT(1), QARS(3) 14031798 34 32 34 2 0 2 8 15 9 0 0.014 0.023 1
10 ACE_INHIBITOR_PATHWAY_PHARMGKB ACE, AGT, AGTR1, AGTR2, BDKRB2, KNG1, NOS3, REN 8 ACE(4), AGT(3), AGTR2(1), KNG1(3), NOS3(1) 4215483 12 12 12 0 2 0 2 7 1 0 0.053 0.025 1

Table 6.  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 ARGININECPATHWAY Related catabolic pathways process arginine, histidine, glutamine, and proline through glutamate to alpha-ketoglutamate, which feeds into the citric acid cycle. ALDH4A1, ARG1, GLS, GLUD1, OAT, PRODH 6 ALDH4A1(1), ARG1(1), GLS(5), GLUD1(1), OAT(2) 2436277 10 10 10 0 0 0 6 1 3 0 0.098 0.0025 0.67
2 HSA00627_1,4_DICHLOROBENZENE_DEGRADATION Genes involved in 1,4-dichlorobenzene degradation CMBL 1 CMBL(3) 213542 3 3 3 0 0 0 0 1 2 0 0.86 0.0031 0.67
3 ERBB4PATHWAY ErbB4 (aka HER4) is a receptor tyrosine kinase that binds neuregulins as well as members of the EGF family, which also target EGF receptors. ADAM17, ERBB4, NRG2, NRG3, PRKCA, PRKCB1, PSEN1 6 ADAM17(3), ERBB4(4), NRG2(1), NRG3(3), PRKCA(1), PSEN1(1) 3787830 13 13 13 1 1 2 1 6 3 0 0.17 0.0033 0.67
4 HSA00550_PEPTIDOGLYCAN_BIOSYNTHESIS Genes involved in peptidoglycan biosynthesis GLUL, PGLYRP2 2 GLUL(2), PGLYRP2(3) 757351 5 5 5 1 1 0 0 3 1 0 0.72 0.0044 0.67
5 PARKINPATHWAY In Parkinson's disease, dopaminergic neurons contain Lewy bodies consisting of alpha-synuclein and parkin, an E3 ubiquitin ligase that targets glycosylated alpha-synuclein. GPR37, PARK2, PNUTL1, SNCA, SNCAIP, UBE2E2, UBE2F, UBE2G1, UBE2G2, UBE2L3, UBE2L6, UBL1 10 GPR37(4), PARK2(2), SNCAIP(3), UBE2L3(1) 2673213 10 10 10 1 0 1 1 6 2 0 0.28 0.0075 0.92
6 GLUTAMATE_METABOLISM ABAT, ALDH4A1, ALDH5A1, CAD, CPS1, EPRS, GAD1, GAD2, GCLC, GCLM, GFPT1, GLS, GLS2, GLUD1, GLUL, GMPS, GOT1, GOT2, GPT, GPT2, GSS, NADSYN1, PPAT, QARS 24 ABAT(1), ALDH4A1(1), CAD(4), CPS1(1), EPRS(1), GAD1(2), GAD2(2), GCLC(3), GCLM(1), GFPT1(2), GLS(5), GLUD1(1), GLUL(2), GMPS(1), GOT2(1), GPT(2), PPAT(1), QARS(3) 14031798 34 32 34 2 0 2 8 15 9 0 0.014 0.023 1
7 ACE_INHIBITOR_PATHWAY_PHARMGKB ACE, AGT, AGTR1, AGTR2, BDKRB2, KNG1, NOS3, REN 8 ACE(4), AGT(3), AGTR2(1), KNG1(3), NOS3(1) 4215483 12 12 12 0 2 0 2 7 1 0 0.053 0.025 1
8 MTA3PATHWAY The estrogen receptor regulates proliferation in mammary epithelia via MTA3 activation; loss of either protein is implicated in breast cancer. ALDOA, CTSD, ESR1, GAPD, GREB1, HSPB1, HSPB2, MTA1, MTA3, PDZK1, TUBA1, TUBA2, TUBA3, TUBA4, TUBA6, TUBA8 10 CTSD(1), GREB1(6), HSPB2(1), MTA1(4), MTA3(2), PDZK1(1), TUBA8(1) 4765391 16 14 16 2 1 4 3 4 4 0 0.16 0.029 1
9 BETAOXIDATIONPATHWAY Beta-Oxidation of Fatty Acids ACADL, ACADM, ACADS, ACAT1, ECHS1, HADHA 6 ACADL(3), ACADM(2), HADHA(2) 2302526 7 7 7 0 0 2 2 3 0 0 0.12 0.039 1
10 CYANOAMINO_ACID_METABOLISM ATP6V0C, SHMT1, GBA3, GGT1, SHMT1, SHMT2 5 GGT1(1), SHMT1(2), SHMT2(3) 1788627 6 6 6 0 1 0 2 2 1 0 0.19 0.039 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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