Mutation Analysis (MutSig v2.0)
Kidney Renal Papillary Cell Carcinoma (Primary solid tumor)
02 April 2015  |  analyses__2015_04_02
Maintainer Information
Citation Information
doi:10.7908/C1MP52BR
Maintained by David Heiman (Broad Institute)
Cite as Broad Institute TCGA Genome Data Analysis Center (2015): Mutation Analysis (MutSig v2.0). Broad Institute of MIT and Harvard. doi:10.7908/C1MP52BR
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: 161

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): 21

  • Mutations seen in COSMIC: 57

  • Significantly mutated genes in COSMIC territory: 4

  • Significantly mutated genesets: 0

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

Mutation Preprocessing

  • Read 161 MAFs of type "Baylor-Illumina"

  • Total number of mutations in input MAFs: 15585

  • After removing 512 blacklisted mutations: 15073

  • After removing 137 noncoding mutations: 14936

  • After collapsing adjacent/redundant mutations: 14902

Mutation Filtering

  • Number of mutations before filtering: 14902

  • After removing 757 mutations outside gene set: 14145

  • After removing 37 mutations outside category set: 14108

  • After removing 1 "impossible" mutations in

  • gene-patient-category bins of zero coverage: 13313

Results
Breakdown of Mutations by Type

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

type count
Frame_Shift_Del 883
Frame_Shift_Ins 291
In_Frame_Del 189
In_Frame_Ins 47
Missense_Mutation 8580
Nonsense_Mutation 492
Nonstop_Mutation 1
Silent 3283
Splice_Site 342
Total 14108
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 272587938 3.2e-06 3.2 1.4 2.1
*Cp(A/C/T)->T 1495 2212498207 6.8e-07 0.68 0.3 1.7
A->G 1648 2375760574 6.9e-07 0.69 0.31 2.3
transver 4564 4860846719 9.4e-07 0.94 0.42 5
indel+null 2210 4860846719 4.5e-07 0.45 0.2 NaN
double_null 36 4860846719 7.4e-09 0.0074 0.0033 NaN
Total 10824 4860846719 2.2e-06 2.2 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: 21. 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 NEFH neurofilament, heavy polypeptide 200kDa 349554 14 10 6 1 0 7 0 2 5 0 1.9e-09 0.1 0 0.96 0 <1.00e-15 <6.13e-12
2 ZNF598 zinc finger protein 598 321927 10 10 1 1 0 0 10 0 0 0 1.6e-10 0.26 0 0.99 0 <1.00e-15 <6.13e-12
3 SKI v-ski sarcoma viral oncogene homolog (avian) 202848 6 6 1 1 0 0 0 6 0 0 1e-05 0.48 0 0.98 0 <1.00e-15 <6.13e-12
4 HNRNPM heterogeneous nuclear ribonucleoprotein M 322264 10 10 2 0 1 0 0 0 9 0 2.4e-10 0.12 1e-06 0.39 7.6e-06 6.27e-14 2.89e-10
5 MET met proto-oncogene (hepatocyte growth factor receptor) 690142 16 15 14 0 0 4 4 7 1 0 3e-11 0.012 0.00084 0.0066 0.00014 1.41e-13 5.18e-10
6 ZNF814 zinc finger protein 814 330143 14 8 8 2 0 8 1 2 3 0 2.2e-06 0.23 6e-07 0.88 0.000012 6.57e-10 2.02e-06
7 NF2 neurofibromin 2 (merlin) 274845 10 10 10 1 0 0 0 1 9 0 3.7e-10 0.47 0.22 0.9 0.33 2.89e-09 7.59e-06
8 ACTB actin, beta 180747 6 6 6 0 0 0 4 2 0 0 5.3e-07 0.39 0.32 0.72 0.44 3.81e-06 0.00875
9 SAV1 salvador homolog 1 (Drosophila) 186449 5 5 5 0 0 2 0 0 3 0 5.8e-06 0.55 0.036 0.99 0.074 6.76e-06 0.0138
10 NFE2L2 nuclear factor (erythroid-derived 2)-like 2 288984 4 4 4 0 0 0 1 3 0 0 0.0028 0.39 0.0029 0.0016 0.00055 2.20e-05 0.0406
11 UBXN11 UBX domain protein 11 244452 4 3 3 1 1 0 2 0 1 0 0.0036 0.74 8e-05 0.91 0.00051 2.63e-05 0.0439
12 LGI4 leucine-rich repeat LGI family, member 4 143767 4 4 4 0 0 1 1 2 0 0 0.000083 0.28 0.26 0.013 0.025 2.91e-05 0.0446
13 BHMT betaine-homocysteine methyltransferase 201128 5 5 5 0 0 1 3 0 1 0 0.000026 0.2 0.16 0.056 0.1 3.57e-05 0.0505
14 TDG thymine-DNA glycosylase 202647 5 5 3 0 0 1 0 0 4 0 0.000012 0.41 0.2 0.068 0.26 4.21e-05 0.0549
15 ATP1B1 ATPase, Na+/K+ transporting, beta 1 polypeptide 150057 5 5 5 0 0 0 1 1 3 0 4.4e-06 0.61 0.81 0.32 0.8 4.74e-05 0.0549
16 SF3B1 splicing factor 3b, subunit 1, 155kDa 647600 9 9 9 1 1 1 2 5 0 0 4.3e-06 0.24 0.62 0.62 0.82 4.81e-05 0.0549
17 IDUA iduronidase, alpha-L- 181170 5 5 2 0 0 0 0 5 0 0 8e-05 0.36 0.026 0.99 0.047 5.07e-05 0.0549
18 CSGALNACT2 chondroitin sulfate N-acetylgalactosaminyltransferase 2 266675 5 5 2 1 1 0 0 4 0 0 0.00024 0.71 0.0085 0.62 0.018 5.61e-05 0.0573
19 CUL3 cullin 3 376822 7 5 7 0 0 1 1 2 3 0 0.00071 0.21 0.0035 1 0.0072 6.72e-05 0.0650
20 MUC2 mucin 2, oligomeric mucus/gel-forming 1079801 25 19 23 18 3 7 3 12 0 0 1 0.98 2e-07 0.97 6.6e-06 8.53e-05 0.0760
21 CDC27 cell division cycle 27 homolog (S. cerevisiae) 396405 5 5 5 0 1 0 2 1 1 0 0.00034 0.17 0.013 0.4 0.02 8.67e-05 0.0760
22 OR2L8 olfactory receptor, family 2, subfamily L, member 8 151700 4 4 2 1 0 1 0 0 3 0 0.000069 0.83 0.084 0.94 0.22 0.000185 0.154
23 HOXD8 homeobox D8 99500 4 4 3 0 0 0 0 2 2 0 0.000035 0.71 0.27 0.93 0.53 0.000219 0.175
24 PTEN phosphatase and tensin homolog (mutated in multiple advanced cancers 1) 197053 5 5 5 0 0 0 2 0 3 0 0.000039 0.3 0.33 0.75 0.56 0.000256 0.187
25 NACA2 nascent polypeptide-associated complex alpha subunit 2 104972 3 3 1 2 0 3 0 0 0 0 0.059 0.8 0.00023 0.99 0.00037 0.000259 0.187
26 B3GNT6 UDP-GlcNAc:betaGal beta-1,3-N-acetylglucosaminyltransferase 6 (core 3 synthase) 97140 3 3 2 0 0 0 1 0 2 0 0.00016 0.6 0.032 0.96 0.15 0.000267 0.187
27 CHCHD3 coiled-coil-helix-coiled-coil-helix domain containing 3 105858 4 4 4 0 0 1 0 2 1 0 0.000034 0.45 0.53 0.46 0.71 0.000284 0.187
28 KDM6A lysine (K)-specific demethylase 6A 652356 7 7 7 0 0 0 0 0 6 1 0.000072 0.43 0.24 0.56 0.34 0.000285 0.187
29 FAT1 FAT tumor suppressor homolog 1 (Drosophila) 2217821 14 13 14 1 1 2 2 4 4 1 0.00055 0.22 0.054 0.18 0.052 0.000326 0.207
30 COMMD8 COMM domain containing 8 83206 3 1 3 0 0 1 0 0 2 0 0.028 0.71 0.00025 0.39 0.0012 0.000367 0.225
31 MAST4 microtubule associated serine/threonine kinase family member 4 1097366 6 6 6 1 0 1 1 3 1 0 0.032 0.57 0.00089 0.04 0.0012 0.000417 0.248
32 KRTAP1-3 keratin associated protein 1-3 81787 4 3 3 1 0 0 0 4 0 0 0.0002 0.84 0.12 0.91 0.21 0.000461 0.265
33 MKL1 megakaryoblastic leukemia (translocation) 1 410567 6 6 6 1 3 1 0 1 1 0 0.00017 0.3 0.17 0.97 0.26 0.000487 0.272
34 SETD2 SET domain containing 2 1091040 11 11 11 2 0 0 0 1 10 0 0.000049 0.93 0.82 0.64 1 0.000532 0.288
35 FLYWCH2 FLYWCH family member 2 67592 3 1 3 0 0 0 0 2 1 0 0.033 0.64 0.0015 0.048 0.0016 0.000567 0.292
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: 4. 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) 16 34 7 5474 27 2e-15 9.1e-12
2 NF2 neurofibromin 2 (merlin) 10 550 7 88550 39 1.9e-09 4.4e-06
3 FGFR3 fibroblast growth factor receptor 3 (achondroplasia, thanatophoric dwarfism) 6 62 3 9982 1469 1.8e-06 0.0027
4 PTEN phosphatase and tensin homolog (mutated in multiple advanced cancers 1) 5 767 5 123487 42 1e-05 0.012
5 KRAS v-Ki-ras2 Kirsten rat sarcoma viral oncogene homolog 2 52 2 8372 29208 0.00017 0.15
6 TP53 tumor protein p53 4 356 3 57316 418 0.00031 0.15
7 CDCA8 cell division cycle associated 8 1 1 1 161 1 0.00036 0.15
8 FLCN folliculin 1 1 1 161 1 0.00036 0.15
9 NKX2-1 NK2 homeobox 1 1 1 1 161 1 0.00036 0.15
10 PHF10 PHD finger protein 10 1 1 1 161 1 0.00036 0.15

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: 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 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 CBL(1), CSF1R(1), EGF(1), MET(16), PDGFRA(1), SH3KBP1(2), SRC(1) 4697422 23 20 21 1 1 5 4 11 2 0 0.016 0.0017 1
2 NUCLEOTIDE_GPCRS ADORA1, ADORA2A, ADORA2B, ADORA3, GPR23, LTB4R, P2RY1, P2RY2, P2RY5, P2RY6 8 ADORA2A(2), ADORA3(1), P2RY1(2), P2RY2(1), P2RY6(2) 1424191 8 8 8 0 1 1 2 4 0 0 0.094 0.012 1
3 MTORPATHWAY Mammalian target of rapamycin (mTOR) senses mitogenic factors and nutrients, including ATP, and induces cell proliferation. AKT1, EIF3S10, EIF4A1, EIF4A2, EIF4B, EIF4E, EIF4EBP1, EIF4G1, EIF4G2, EIF4G3, FKBP1A, FRAP1, MKNK1, PDK2, PDPK1, PIK3CA, PIK3R1, PPP2CA, PTEN, RPS6, RPS6KB1, TSC1, TSC2 21 AKT1(1), EIF4A1(1), EIF4A2(1), EIF4B(2), EIF4EBP1(1), EIF4G1(1), EIF4G2(1), EIF4G3(4), PIK3CA(2), PIK3R1(2), PTEN(5), TSC1(2), TSC2(4) 6716562 27 24 27 2 2 6 4 6 9 0 0.023 0.012 1
4 HSA00480_GLUTATHIONE_METABOLISM Genes involved in glutathione metabolism ANPEP, G6PD, GCLC, GCLM, GGT1, GGTL3, GGTL4, GPX1, GPX2, GPX3, GPX4, GPX5, GPX6, GPX7, GSR, GSS, GSTA1, GSTA2, GSTA3, GSTA4, GSTA5, GSTK1, GSTM1, GSTM2, GSTM3, GSTM4, GSTM5, GSTO2, GSTP1, GSTT1, GSTT2, GSTZ1, IDH1, IDH2, MGST1, MGST2, MGST3, OPLAH, TXNDC12 37 ANPEP(2), GCLC(3), GGT1(1), GPX1(1), GPX4(1), GSTA1(1), GSTA2(1), GSTK1(1), GSTM1(1), GSTM4(1), GSTP1(2), GSTT1(2), IDH2(1), OPLAH(3) 5431281 21 18 21 0 2 4 5 7 3 0 0.0023 0.019 1
5 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 ARF3(1), CDKN2A(2), E2F2(1), PRB1(2), TP53(4) 2036926 10 9 10 1 0 0 0 6 3 1 0.36 0.021 1
6 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(2), ERBB4(3), NRG2(1), NRG3(3) 2177146 9 9 9 0 2 1 1 4 1 0 0.085 0.024 1
7 HSA00550_PEPTIDOGLYCAN_BIOSYNTHESIS Genes involved in peptidoglycan biosynthesis GLUL, PGLYRP2 2 GLUL(2), PGLYRP2(1) 433960 3 3 3 1 1 0 1 1 0 0 0.77 0.025 1
8 KREBPATHWAY The Krebs (citric acid) cycle takes place in mitochondria, where it extracts energy in the form of electron carriers NADH and FADH2, which drive the electron transport chain. ACO2, CS, FH, IDH2, MDH1, OGDH, SDHA, SUCLA2 8 FH(2), IDH2(1), MDH1(1), OGDH(5), SDHA(2), SUCLA2(1) 2277788 12 11 12 2 0 3 0 4 5 0 0.29 0.034 1
9 UBIQUINONE_BIOSYNTHESIS NDUFA1, NDUFA10, NDUFA11, NDUFA4, NDUFA5, NDUFA8, NDUFB2, NDUFB4, NDUFB5, NDUFB6, NDUFB7, NDUFS1, NDUFS2, NDUFV1, NDUFV2 15 NDUFA11(2), NDUFB2(1), NDUFB4(1), NDUFB5(2), NDUFB7(1), NDUFS1(1), NDUFV1(1) 1698697 9 9 8 2 0 0 1 3 5 0 0.75 0.042 1
10 GLUTATHIONE_METABOLISM ANPEP, G6PD, GCLC, GCLM, GGT1, GPX1, GPX2, GPX3, GPX4, GPX5, GSS, GSTA1, GSTA2, GSTA3, GSTA4, GSTM1, GSTM2, GSTM3, GSTM4, GSTM5, GSTO2, GSTP1, GSTT1, GSTT2, GSTZ1, IDH1, IDH2, MGST1, MGST2, MGST3, PGD 31 ANPEP(2), GCLC(3), GGT1(1), GPX1(1), GPX4(1), GSTA1(1), GSTA2(1), GSTM1(1), GSTM4(1), GSTP1(2), GSTT1(2), IDH2(1) 4460585 17 15 17 0 1 3 4 7 2 0 0.0082 0.044 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 NUCLEOTIDE_GPCRS ADORA1, ADORA2A, ADORA2B, ADORA3, GPR23, LTB4R, P2RY1, P2RY2, P2RY5, P2RY6 8 ADORA2A(2), ADORA3(1), P2RY1(2), P2RY2(1), P2RY6(2) 1424191 8 8 8 0 1 1 2 4 0 0 0.094 0.012 1
2 MTORPATHWAY Mammalian target of rapamycin (mTOR) senses mitogenic factors and nutrients, including ATP, and induces cell proliferation. AKT1, EIF3S10, EIF4A1, EIF4A2, EIF4B, EIF4E, EIF4EBP1, EIF4G1, EIF4G2, EIF4G3, FKBP1A, FRAP1, MKNK1, PDK2, PDPK1, PIK3CA, PIK3R1, PPP2CA, PTEN, RPS6, RPS6KB1, TSC1, TSC2 21 AKT1(1), EIF4A1(1), EIF4A2(1), EIF4B(2), EIF4EBP1(1), EIF4G1(1), EIF4G2(1), EIF4G3(4), PIK3CA(2), PIK3R1(2), PTEN(5), TSC1(2), TSC2(4) 6716562 27 24 27 2 2 6 4 6 9 0 0.023 0.012 1
3 HSA00480_GLUTATHIONE_METABOLISM Genes involved in glutathione metabolism ANPEP, G6PD, GCLC, GCLM, GGT1, GGTL3, GGTL4, GPX1, GPX2, GPX3, GPX4, GPX5, GPX6, GPX7, GSR, GSS, GSTA1, GSTA2, GSTA3, GSTA4, GSTA5, GSTK1, GSTM1, GSTM2, GSTM3, GSTM4, GSTM5, GSTO2, GSTP1, GSTT1, GSTT2, GSTZ1, IDH1, IDH2, MGST1, MGST2, MGST3, OPLAH, TXNDC12 37 ANPEP(2), GCLC(3), GGT1(1), GPX1(1), GPX4(1), GSTA1(1), GSTA2(1), GSTK1(1), GSTM1(1), GSTM4(1), GSTP1(2), GSTT1(2), IDH2(1), OPLAH(3) 5431281 21 18 21 0 2 4 5 7 3 0 0.0023 0.019 1
4 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 ARF3(1), CDKN2A(2), E2F2(1), PRB1(2), TP53(4) 2036926 10 9 10 1 0 0 0 6 3 1 0.36 0.021 1
5 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(2), ERBB4(3), NRG2(1), NRG3(3) 2177146 9 9 9 0 2 1 1 4 1 0 0.085 0.024 1
6 HSA00550_PEPTIDOGLYCAN_BIOSYNTHESIS Genes involved in peptidoglycan biosynthesis GLUL, PGLYRP2 2 GLUL(2), PGLYRP2(1) 433960 3 3 3 1 1 0 1 1 0 0 0.77 0.025 1
7 KREBPATHWAY The Krebs (citric acid) cycle takes place in mitochondria, where it extracts energy in the form of electron carriers NADH and FADH2, which drive the electron transport chain. ACO2, CS, FH, IDH2, MDH1, OGDH, SDHA, SUCLA2 8 FH(2), IDH2(1), MDH1(1), OGDH(5), SDHA(2), SUCLA2(1) 2277788 12 11 12 2 0 3 0 4 5 0 0.29 0.034 1
8 UBIQUINONE_BIOSYNTHESIS NDUFA1, NDUFA10, NDUFA11, NDUFA4, NDUFA5, NDUFA8, NDUFB2, NDUFB4, NDUFB5, NDUFB6, NDUFB7, NDUFS1, NDUFS2, NDUFV1, NDUFV2 15 NDUFA11(2), NDUFB2(1), NDUFB4(1), NDUFB5(2), NDUFB7(1), NDUFS1(1), NDUFV1(1) 1698697 9 9 8 2 0 0 1 3 5 0 0.75 0.042 1
9 GLUTATHIONE_METABOLISM ANPEP, G6PD, GCLC, GCLM, GGT1, GPX1, GPX2, GPX3, GPX4, GPX5, GSS, GSTA1, GSTA2, GSTA3, GSTA4, GSTM1, GSTM2, GSTM3, GSTM4, GSTM5, GSTO2, GSTP1, GSTT1, GSTT2, GSTZ1, IDH1, IDH2, MGST1, MGST2, MGST3, PGD 31 ANPEP(2), GCLC(3), GGT1(1), GPX1(1), GPX4(1), GSTA1(1), GSTA2(1), GSTM1(1), GSTM4(1), GSTP1(2), GSTT1(2), IDH2(1) 4460585 17 15 17 0 1 3 4 7 2 0 0.0082 0.044 1
10 RABPATHWAY Rab family GTPases regulate vesicle transport, endocytosis and exocytosis, and vesicle docking via interactions with the rabphilins. ACTA1, MEL, RAB11A, RAB1A, RAB2, RAB27A, RAB3A, RAB4A, RAB5A, RAB6A, RAB7, RAB9A 9 ACTA1(1), RAB11A(1), RAB1A(1), RAB3A(1), RAB6A(1) 1030751 5 5 5 1 0 1 1 2 1 0 0.68 0.044 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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