Mutation Analysis (MutSig v2.0)
Kidney Renal Clear Cell Carcinoma (Primary solid tumor)
02 April 2015  |  analyses__2015_04_02
Maintainer Information
Citation Information
doi:10.7908/C19K498J
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/C19K498J
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: KIRC-TP

  • Number of patients in set: 451

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:KIRC-TP.final_analysis_set.maf

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

  • Significantly mutated genes (q ≤ 0.1): 203

  • Mutations seen in COSMIC: 482

  • Significantly mutated genes in COSMIC territory: 97

  • Significantly mutated genesets: 12

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

Mutation Preprocessing

  • Read 217 MAFs of type "Broad"

  • Read 330 MAFs of type "Baylor-Illumina"

  • Read 120 MAFs of type "Baylor-SOLiD"

  • Total number of mutations in input MAFs: 61731

  • After removing 23 mutations outside chr1-24: 61708

  • After removing 8808 blacklisted mutations: 52900

  • After removing 1411 noncoding mutations: 51489

  • After collapsing adjacent/redundant mutations: 36260

Mutation Filtering

  • Number of mutations before filtering: 36260

  • After removing 1031 mutations outside gene set: 35229

  • After removing 127 mutations outside category set: 35102

  • After removing 8 "impossible" mutations in

  • gene-patient-category bins of zero coverage: 33936

Results
Breakdown of Mutations by Type

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

type count
Frame_Shift_Del 1756
Frame_Shift_Ins 3123
In_Frame_Del 344
In_Frame_Ins 64
Missense_Mutation 19552
Nonsense_Mutation 1388
Nonstop_Mutation 28
Silent 7189
Splice_Site 1621
Translation_Start_Site 37
Total 35102
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 2027 666857343 3e-06 3 1.4 2.2
*Cp(A/C/T)->T 3761 5856172488 6.4e-07 0.64 0.3 1.7
A->G 3198 6472983367 4.9e-07 0.49 0.23 2.3
transver 10597 12996013198 8.2e-07 0.82 0.38 5.1
indel+null 8209 12996013198 6.3e-07 0.63 0.29 NaN
double_null 117 12996013198 9e-09 0.009 0.0042 NaN
Total 27909 12996013198 2.1e-06 2.1 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: KIRC-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: 203. 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 VHL von Hippel-Lindau tumor suppressor 164008 242 229 140 7 8 11 24 66 132 1 <1.00e-15 1.4e-13 0.0043 0.024 0.0061 <2.22e-16 <3.45e-13
2 PBRM1 polybromo 1 2247536 150 147 139 4 0 3 5 18 123 1 <1.00e-15 8.6e-06 0.036 0.016 0.0081 <3.33e-16 <3.45e-13
3 DNMT1 DNA (cytosine-5-)-methyltransferase 1 2083111 22 22 7 0 0 1 4 1 16 0 1.70e-06 0.17 0 1 0 <1.00e-15 <3.45e-13
4 GCNT2 glucosaminyl (N-acetyl) transferase 2, I-branching enzyme (I blood group) 1378585 21 21 5 1 0 0 1 2 18 0 2.73e-08 0.74 0 1 0 <1.00e-15 <3.45e-13
5 C6orf25 chromosome 6 open reading frame 25 236229 19 19 1 0 0 0 0 0 19 0 1.78e-14 1 0 0.96 0 <1.00e-15 <3.45e-13
6 KIAA0408 KIAA0408 931597 19 19 3 0 0 1 0 0 18 0 1.85e-08 0.71 0 0.65 0 <1.00e-15 <3.45e-13
7 SMG7 Smg-7 homolog, nonsense mediated mRNA decay factor (C. elegans) 1558778 19 16 3 0 0 0 0 7 11 1 2.70e-05 0.036 0 0.84 0 <1.00e-15 <3.45e-13
8 CCDC136 coiled-coil domain containing 136 1318310 15 15 2 1 1 0 0 0 14 0 9.85e-05 0.89 0 1 0 <1.00e-15 <3.45e-13
9 CCDC91 coiled-coil domain containing 91 614810 15 15 3 0 0 0 1 1 13 0 2.66e-08 0.085 0 0.44 0 <1.00e-15 <3.45e-13
10 ARAP3 ArfGAP with RhoGAP domain, ankyrin repeat and PH domain 3 1928794 14 14 3 0 0 0 0 1 11 2 0.000987 0.53 0 0.97 0 <1.00e-15 <3.45e-13
11 DPP3 dipeptidyl-peptidase 3 945518 14 14 2 1 0 1 0 0 13 0 5.18e-05 0.92 0 1 0 <1.00e-15 <3.45e-13
12 TAS2R3 taste receptor, type 2, member 3 429539 14 13 5 0 0 0 1 13 0 0 3.42e-10 0.06 0 0.96 0 <1.00e-15 <3.45e-13
13 ACSL3 acyl-CoA synthetase long-chain family member 3 997929 13 12 3 0 0 1 0 10 2 0 1.62e-05 0.094 0 0.0096 0 <1.00e-15 <3.45e-13
14 EFNB3 ephrin-B3 348243 12 12 1 0 0 0 0 0 12 0 2.60e-07 1 0 0.56 0 <1.00e-15 <3.45e-13
15 NAPSA napsin A aspartic peptidase 515598 12 12 2 0 1 0 0 0 10 1 1.04e-06 0.64 0 0.99 0 <1.00e-15 <3.45e-13
16 OSBPL3 oxysterol binding protein-like 3 1231143 12 12 3 1 0 0 0 0 11 1 0.000785 0.45 2e-07 0.052 0 <1.00e-15 <3.45e-13
17 SPDYE3 speedy homolog E3 (Xenopus laevis) 358182 12 12 1 0 0 0 0 0 12 0 5.08e-07 1 0 0.17 0 <1.00e-15 <3.45e-13
18 C1S complement component 1, s subcomponent 949879 16 11 3 2 0 1 0 7 8 0 0.000255 0.39 0 0.00029 0 <1.00e-15 <3.45e-13
19 PKD2 polycystic kidney disease 2 (autosomal dominant) 1063183 12 11 3 0 0 1 0 11 0 0 0.000142 0.1 8e-07 0.00021 0 <1.00e-15 <3.45e-13
20 SLC26A4 solute carrier family 26, member 4 1015348 11 11 3 3 1 0 0 1 9 0 0.00682 0.55 2e-06 0.041 0 <1.00e-15 <3.45e-13
21 TSKS testis-specific serine kinase substrate 691209 11 11 2 0 0 1 0 0 10 0 0.000133 0.55 0 0.78 0 <1.00e-15 <3.45e-13
22 PHYH phytanoyl-CoA 2-hydroxylase 429107 10 10 2 0 0 0 0 1 9 0 6.75e-06 0.86 0 1 0 <1.00e-15 <3.45e-13
23 CHSY1 chondroitin sulfate synthase 1 938583 9 9 3 0 0 0 0 2 7 0 0.00603 0.72 0.00015 0.00055 0 <1.00e-15 <3.45e-13
24 OR4A47 olfactory receptor, family 4, subfamily A, member 47 408792 10 9 2 0 0 0 0 10 0 0 2.19e-06 0.16 0 0.92 0 <1.00e-15 <3.45e-13
25 SDHAF2 succinate dehydrogenase complex assembly factor 2 232996 9 9 1 0 0 0 0 0 9 0 9.76e-07 0.24 0 0.0067 0 <1.00e-15 <3.45e-13
26 SLC4A5 solute carrier family 4, sodium bicarbonate cotransporter, member 5 1541933 9 9 2 0 0 0 0 1 8 0 0.0922 0.83 4e-07 0.00098 0 <1.00e-15 <3.45e-13
27 ARPC2 actin related protein 2/3 complex, subunit 2, 34kDa 412986 8 8 2 0 0 0 0 1 7 0 0.000124 0.28 0 0.44 0 <1.00e-15 <3.45e-13
28 PDE9A phosphodiesterase 9A 831641 8 8 1 0 0 0 0 0 8 0 0.0178 1 0 0.5 0 <1.00e-15 <3.45e-13
29 RRAS2 related RAS viral (r-ras) oncogene homolog 2 238375 8 8 1 0 0 0 0 0 8 0 1.03e-05 0.31 0 0.15 0 <1.00e-15 <3.45e-13
30 TRH thyrotropin-releasing hormone 243937 8 8 1 0 0 0 0 0 8 0 1.67e-05 1 0 0.44 0 <1.00e-15 <3.45e-13
31 NETO2 neuropilin (NRP) and tolloid (TLL)-like 2 707598 7 7 2 0 0 0 1 0 6 0 0.00620 0.24 0 0.34 0 <1.00e-15 <3.45e-13
32 PCGF1 polycomb group ring finger 1 340537 7 7 1 1 0 0 0 0 7 0 0.000471 1 0 0.96 0 <1.00e-15 <3.45e-13
33 RBPJL recombination signal binding protein for immunoglobulin kappa J region-like 565554 7 7 2 0 0 0 1 0 6 0 0.00233 0.8 2e-07 0.00016 0 <1.00e-15 <3.45e-13
34 SHANK1 SH3 and multiple ankyrin repeat domains 1 1347926 7 7 1 2 0 0 0 0 5 2 0.0865 1 0 0.0012 0 <1.00e-15 <3.45e-13
35 ZMAT2 zinc finger, matrin type 2 279511 7 7 1 1 0 0 0 0 7 0 0.000116 0.77 2e-07 0.29 0 <1.00e-15 <3.45e-13
C6orf25

Figure S1.  This figure depicts the distribution of mutations and mutation types across the C6orf25 significant gene.

EFNB3

Figure S2.  This figure depicts the distribution of mutations and mutation types across the EFNB3 significant gene.

SPDYE3

Figure S3.  This figure depicts the distribution of mutations and mutation types across the SPDYE3 significant gene.

PKD2

Figure S4.  This figure depicts the distribution of mutations and mutation types across the PKD2 significant gene.

OR4A47

Figure S5.  This figure depicts the distribution of mutations and mutation types across the OR4A47 significant gene.

PDE9A

Figure S6.  This figure depicts the distribution of mutations and mutation types across the PDE9A significant gene.

TRH

Figure S7.  This figure depicts the distribution of mutations and mutation types across the TRH 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: 97. Number of genes displayed: 10

rank gene description n cos n_cos N_cos cos_ev p q
1 VHL von Hippel-Lindau tumor suppressor 242 541 238 243991 5783 0 0
2 TP53 tumor protein p53 18 356 16 160556 1973 0 0
3 PIK3CA phosphoinositide-3-kinase, catalytic, alpha polypeptide 12 220 9 99220 3320 5.4e-12 7.7e-09
4 PTEN phosphatase and tensin homolog (mutated in multiple advanced cancers 1) 22 767 22 345917 563 6.8e-12 7.7e-09
5 PTCH1 patched homolog 1 (Drosophila) 10 256 8 115456 13 2.9e-10 2.6e-07
6 CSF1R colony stimulating factor 1 receptor, formerly McDonough feline sarcoma viral (v-fms) oncogene homolog 6 14 3 6314 9 4.1e-07 0.00026
7 STXBP3 syntaxin binding protein 3 4 1 2 451 2 4.7e-07 0.00026
8 TMEM47 transmembrane protein 47 2 1 2 451 2 4.7e-07 0.00026
9 EGFR epidermal growth factor receptor (erythroblastic leukemia viral (v-erb-b) oncogene homolog, avian) 10 293 6 132143 30 5.7e-07 0.00029
10 KLK10 kallikrein-related peptidase 10 3 2 2 902 2 1.9e-06 0.00071

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: 12. 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 HSA04120_UBIQUITIN_MEDIATED_PROTEOLYSIS Genes involved in ubiquitin mediated proteolysis ANAPC1, ANAPC10, ANAPC11, ANAPC2, ANAPC4, ANAPC5, ANAPC7, BTRC, CDC16, CDC20, CDC23, CDC26, CDC27, CUL1, CUL2, CUL3, FBXW11, FBXW7, FZR1, ITCH, LOC728919, RBX1, SKP1, SKP2, SMURF1, SMURF2, TCEB1, TCEB2, UBA1, UBE2C, UBE2D1, UBE2D2, UBE2D3, UBE2D4, UBE2E1, UBE2E2, UBE2E3, VHL, WWP1, WWP2 39 ANAPC1(4), ANAPC11(1), ANAPC2(1), ANAPC4(5), ANAPC5(1), ANAPC7(2), BTRC(2), CDC16(3), CDC20(1), CDC23(2), CDC27(2), CUL1(3), CUL2(1), CUL3(6), FBXW11(1), FBXW7(2), FZR1(4), SKP2(1), SMURF2(3), TCEB1(4), TCEB2(1), UBA1(1), UBE2D1(2), UBE2D2(1), UBE2D3(2), UBE2E2(1), VHL(242), WWP2(3) 26842932 302 260 195 21 11 18 29 91 151 2 3e-08 <1.00e-15 <6.16e-13
2 HIFPATHWAY Under normal conditions, hypoxia inducible factor HIF-1 is degraded; under hypoxic conditions, it activates transcription of genes controlled by hpoxic response elements (HREs). ARNT, ASPH, COPS5, CREB1, EDN1, EP300, EPO, HIF1A, HSPCA, JUN, LDHA, NOS3, P4HB, VEGF, VHL 13 ARNT(2), ASPH(3), COPS5(1), EP300(11), HIF1A(3), JUN(2), NOS3(3), VHL(242) 11058426 267 242 162 16 8 11 29 76 142 1 1e-08 2.44e-15 7.52e-13
3 VEGFPATHWAY Vascular endothelial growth factor (VEGF) is upregulated by hypoxic conditions and promotes normal blood vessel formation and angiogenesis related to tumor growth or cardiac disease. ARNT, EIF1, EIF1A, EIF2B1, EIF2B2, EIF2B3, EIF2B4, EIF2B5, EIF2S1, EIF2S2, EIF2S3, ELAVL1, FLT1, FLT4, HIF1A, HRAS, KDR, NOS3, PIK3CA, PIK3R1, PLCG1, PRKCA, PRKCB1, PTK2, PXN, SHC1, VEGF, VHL 25 ARNT(2), EIF1(2), EIF2B1(2), EIF2B2(1), EIF2B3(1), EIF2B5(2), EIF2S2(2), FLT1(9), FLT4(7), HIF1A(3), HRAS(1), KDR(5), NOS3(3), PIK3CA(12), PIK3R1(2), PLCG1(2), PRKCA(2), PTK2(1), PXN(1), SHC1(3), VHL(242) 22290046 305 256 199 23 13 22 31 89 149 1 1.3e-08 6.11e-15 1.25e-12
4 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 AKT1(2), AKT2(3), AKT3(2), GRB2(2), ILK(4), MAPK3(1), PDK1(1), PIK3CA(12), PIK3CD(1), PTEN(22), PTK2B(3), RBL2(2), SHC1(3), SOS1(6) 13295530 64 56 59 4 4 14 5 18 22 1 0.00047 6.54e-07 0.000101
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(2), MAX(5), MYC(1), SP1(2), SP3(2), TP53(18), WT1(3) 4549903 33 29 31 3 2 3 2 11 13 2 0.067 2.28e-05 0.00280
6 CDC42RACPATHWAY PI3 kinase stimulates cell migration by activating cdc42, which activates ARP2/3, which in turn promotes formation of new actin fibers. ACTR2, ACTR3, ARHA, ARPC1A, ARPC1B, ARPC2, ARPC3, ARPC4, CDC42, PAK1, PDGFRA, PIK3CA, PIK3R1, RAC1, WASL 14 ACTR2(1), ARPC1B(1), ARPC2(8), CDC42(1), PAK1(2), PDGFRA(7), PIK3CA(12), PIK3R1(2), RAC1(1), WASL(6) 8954221 41 40 32 2 0 9 3 17 12 0 0.0031 3.44e-05 0.00353
7 SA_TRKA_RECEPTOR The TrkA receptor binds nerve growth factor to activate MAP kinase pathways and promote cell growth. AKT1, AKT2, AKT3, ARHA, CDKN1A, ELK1, GRB2, HRAS, MAP2K1, MAP2K2, NGFB, NGFR, NTRK1, PIK3CA, PIK3CD, SHC1, SOS1 15 AKT1(2), AKT2(3), AKT3(2), CDKN1A(1), ELK1(1), GRB2(2), HRAS(1), NGFR(1), NTRK1(6), PIK3CA(12), PIK3CD(1), SHC1(3), SOS1(6) 10262631 41 39 37 1 2 11 5 19 4 0 0.00015 4.03e-05 0.00355
8 P53HYPOXIAPATHWAY Hypoxia induces p53 accumulation and consequent apoptosis with p53-mediated cell cycle arrest, which is present under conditions of DNA damage. ABCB1, AKT1, ATM, BAX, CDKN1A, CPB2, CSNK1A1, CSNK1D, FHL2, GADD45A, HIC1, HIF1A, HSPA1A, HSPCA, IGFBP3, MAPK8, MDM2, NFKBIB, NQO1, TP53 17 ABCB1(4), AKT1(2), ATM(16), BAX(1), CDKN1A(1), CPB2(5), CSNK1A1(2), FHL2(1), HIF1A(3), IGFBP3(1), NFKBIB(1), TP53(18) 13158403 55 49 50 3 2 6 7 16 22 2 0.002 8.50e-05 0.00654
9 BBCELLPATHWAY Fas ligand expression by T cells induces apoptosis in Fas-expressing, inactive B cells. CD28, CD4, HLA-DRA, HLA-DRB1, TNFRSF5, TNFRSF6, TNFSF5, TNFSF6 4 CD28(1), CD4(10), HLA-DRA(1), HLA-DRB1(1) 1356343 13 13 7 1 1 1 0 1 9 1 0.7 0.000295 0.0202
10 BLOOD_GROUP_GLYCOLIPID_BIOSYNTHESIS_NEOLACTOSERIES ABO, B3GNT1, FUT1, FUT2, FUT9, GCNT2, ST8SIA1 7 ABO(1), B3GNT1(1), FUT1(1), GCNT2(21), ST8SIA1(2) 3802567 26 25 10 2 2 1 1 3 19 0 0.48 0.000577 0.0356

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 SA_TRKA_RECEPTOR The TrkA receptor binds nerve growth factor to activate MAP kinase pathways and promote cell growth. AKT1, AKT2, AKT3, ARHA, CDKN1A, ELK1, GRB2, HRAS, MAP2K1, MAP2K2, NGFB, NGFR, NTRK1, PIK3CA, PIK3CD, SHC1, SOS1 14 AKT1(2), AKT2(3), AKT3(2), CDKN1A(1), ELK1(1), GRB2(2), HRAS(1), NGFR(1), NTRK1(6), PIK3CD(1), SHC1(3), SOS1(6) 8805146 29 28 28 1 2 6 3 15 3 0 0.0048 0.01 1
2 HSA00950_ALKALOID_BIOSYNTHESIS_I Genes involved in alkaloid biosynthesis I DDC, GOT1, GOT2, TAT, TYR 5 DDC(2), GOT1(3), GOT2(2), TAT(1), TYR(5) 3135385 13 13 13 1 1 0 3 4 5 0 0.27 0.01 1
3 CHREBPPATHWAY Carbohydrate responsive element binding protein (chREBP) is a transcription factor inhibited by cAMP and activated by high carbohydrate levels. ADCY1, BG1, BUCS1, GNAS, GNB1, GNGT1, PPP2CA, PRKAA1, PRKAA2, PRKAB1, PRKAB2, PRKACB, PRKACG, PRKAG1, PRKAG2, PRKAR1A, PRKAR1B, PRKAR2A, PRKAR2B, WBSCR14 16 ADCY1(2), GNAS(4), GNB1(2), PPP2CA(1), PRKAB1(1), PRKACB(5), PRKACG(2), PRKAG1(4), PRKAG2(4), PRKAR1A(2), PRKAR2B(2) 9130690 29 29 29 2 3 3 2 15 6 0 0.043 0.036 1
4 HSA00750_VITAMIN_B6_METABOLISM Genes involved in vitamin B6 metabolism AOX1, PDXK, PDXP, PNPO, PSAT1 5 AOX1(7), PDXK(3), PDXP(1), PSAT1(1) 3151763 12 11 12 0 2 1 0 6 3 0 0.079 0.038 1
5 AKAPCENTROSOMEPATHWAY Protein Kinase A at the Centrosome AKAP9, ARHA, CDC2, MAP2, PCNT1, PCNT2, PPP1CA, PPP2CA, PRKACB, PRKACG, PRKAG1, PRKAR2A, PRKAR2B, PRKCE, PRKCL1 10 AKAP9(19), MAP2(4), PPP2CA(1), PRKACB(5), PRKACG(2), PRKAG1(4), PRKAR2B(2), PRKCE(2) 12102647 39 37 36 3 5 2 2 17 12 1 0.026 0.04 1
6 UREACYCLEPATHWAY Ammonia released from amino acid deamination is used to produce carbamoyl phosphate, which is used to convert ornithine to citrulline, from which urea is eventually formed. ARG1, ASL, ASS, CPS1, GLS, GLUD1, GOT1 6 ARG1(1), ASL(4), CPS1(5), GLS(4), GOT1(3) 5133932 17 17 17 1 0 3 1 8 5 0 0.13 0.04 1
7 CYSTEINE_METABOLISM CARS, CTH, GOT1, GOT2, LDHA, LDHB, LDHC, MPST 8 CARS(6), CTH(1), GOT1(3), GOT2(2), LDHB(1), LDHC(3), MPST(2) 4479216 18 18 16 2 1 0 2 6 9 0 0.39 0.045 1
8 STILBENE_COUMARINE_AND_LIGNIN_BIOSYNTHESIS EPX, GBA3, LPO, MPO, PRDX1, PRDX2, PRDX5, PRDX6, TPO, TYR 10 EPX(2), GBA3(2), MPO(4), PRDX1(1), PRDX5(1), TPO(4), TYR(5) 6283322 19 18 19 1 1 2 5 7 4 0 0.056 0.058 1
9 HSA00401_NOVOBIOCIN_BIOSYNTHESIS Genes involved in novobiocin biosynthesis GOT1, GOT2, TAT 3 GOT1(3), GOT2(2), TAT(1) 1757669 6 6 6 1 1 0 2 0 3 0 0.57 0.1 1
10 HSA00300_LYSINE_BIOSYNTHESIS Genes involved in lysine biosynthesis AADAT, AASDHPPT, AASS, KARS 4 AADAT(1), AASDHPPT(2), AASS(5), KARS(1) 3196928 9 9 9 1 0 1 1 2 5 0 0.45 0.12 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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