Mutation Analysis (MutSig v2.0)
Pan-kidney cohort (KICH+KIRC+KIRP) (Primary solid tumor)
02 April 2015  |  analyses__2015_04_02
Maintainer Information
Citation Information
doi:10.7908/C10G3J6B
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/C10G3J6B
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: KIPAN-TP

  • Number of patients in set: 678

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:KIPAN-TP.final_analysis_set.maf

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

  • Significantly mutated genes (q ≤ 0.1): 179

  • Mutations seen in COSMIC: 581

  • Significantly mutated genes in COSMIC territory: 86

  • Significantly mutated genesets: 9

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

Mutation Preprocessing

  • Read 217 MAFs of type "Broad"

  • Read 557 MAFs of type "Baylor-Illumina"

  • Read 120 MAFs of type "Baylor-SOLiD"

  • Total number of mutations in input MAFs: 84875

  • After removing 57 mutations outside chr1-24: 84818

  • After removing 9840 blacklisted mutations: 74978

  • After removing 1773 noncoding mutations: 73205

  • After collapsing adjacent/redundant mutations: 57929

Mutation Filtering

  • Number of mutations before filtering: 57929

  • After removing 2067 mutations outside gene set: 55862

  • After removing 256 mutations outside category set: 55606

  • After removing 9 "impossible" mutations in

  • gene-patient-category bins of zero coverage: 53274

Results
Breakdown of Mutations by Type

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

type count
Frame_Shift_Del 2820
Frame_Shift_Ins 3635
In_Frame_Del 587
In_Frame_Ins 129
Missense_Mutation 32021
Nonsense_Mutation 2054
Nonstop_Mutation 29
Silent 12226
Splice_Site 2068
Translation_Start_Site 37
Total 55606
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 4052 1053326702 3.8e-06 3.8 1.8 2.1
*Cp(A/C/T)->T 5845 9014095389 6.5e-07 0.65 0.3 1.7
A->G 6012 9866617587 6.1e-07 0.61 0.28 2.3
transver 16139 19934039678 8.1e-07 0.81 0.37 5.1
indel+null 11090 19934039678 5.6e-07 0.56 0.26 NaN
double_null 236 19934039678 1.2e-08 0.012 0.0054 NaN
Total 43374 19934039678 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: KIPAN-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: 179. 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 265002 245 232 142 7 8 11 25 67 133 1 2.4e-15 7.6e-14 0.000054 0.011 0.000061 0.000 0.000
2 TP53 tumor protein p53 856545 50 43 41 2 5 6 5 13 18 3 7.7e-15 0.00013 5e-05 0.00035 0.000018 0.000 0.000
3 PBRM1 polybromo 1 3380257 157 154 146 5 0 3 5 21 127 1 1.8e-15 0.000012 0.031 0.021 0.01 6.66e-16 4.60e-13
4 MUC2 mucin 2, oligomeric mucus/gel-forming 4378384 47 38 41 31 9 12 3 20 3 0 1 0.99 0 1 0 <1.00e-15 <4.60e-13
5 MUC6 mucin 6, oligomeric mucus/gel-forming 4169655 45 29 43 20 4 16 5 17 3 0 1 0.65 0 1 0 <1.00e-15 <4.60e-13
6 GCNT2 glucosaminyl (N-acetyl) transferase 2, I-branching enzyme (I blood group) 2075708 22 22 6 1 0 0 1 3 18 0 1.7e-06 0.68 0 1 0 <1.00e-15 <4.60e-13
7 KIAA0408 KIAA0408 1406651 20 20 4 0 0 1 0 0 19 0 4.7e-07 0.71 0 0.7 0 <1.00e-15 <4.60e-13
8 C6orf25 chromosome 6 open reading frame 25 406924 19 19 1 0 0 0 0 0 19 0 8.2e-12 1 0 0.96 0 <1.00e-15 <4.60e-13
9 NEFH neurofilament, heavy polypeptide 200kDa 1453374 21 17 11 2 0 7 1 2 11 0 1.9e-07 0.22 0 0.77 0 <1.00e-15 <4.60e-13
10 SMG7 Smg-7 homolog, nonsense mediated mRNA decay factor (C. elegans) 2361628 19 16 3 0 0 0 0 7 11 1 0.0016 0.036 0 0.84 0 <1.00e-15 <4.60e-13
11 ARAP3 ArfGAP with RhoGAP domain, ankyrin repeat and PH domain 3 2975027 15 15 4 1 0 0 0 2 11 2 0.014 0.72 0 0.95 0 <1.00e-15 <4.60e-13
12 CCDC136 coiled-coil domain containing 136 2001522 15 15 2 1 1 0 0 0 14 0 0.0034 0.89 0 1 0 <1.00e-15 <4.60e-13
13 CCDC91 coiled-coil domain containing 91 917928 15 15 3 0 0 0 1 1 13 0 1.8e-06 0.084 0 0.44 0 <1.00e-15 <4.60e-13
14 DPP3 dipeptidyl-peptidase 3 1459497 14 14 2 2 0 1 0 0 13 0 0.0042 0.97 0 1 0 <1.00e-15 <4.60e-13
15 NAPSA napsin A aspartic peptidase 798402 13 13 3 0 1 0 0 0 11 1 6.8e-06 0.64 0 1 0 <1.00e-15 <4.60e-13
16 TAS2R3 taste receptor, type 2, member 3 646324 14 13 5 0 0 0 1 13 0 0 3.3e-08 0.06 0 0.96 0 <1.00e-15 <4.60e-13
17 ZNF814 zinc finger protein 814 1510191 21 13 10 2 0 11 2 4 4 0 0.000079 0.07 0 0.92 0 <1.00e-15 <4.60e-13
18 ACSL3 acyl-CoA synthetase long-chain family member 3 1496283 13 12 3 0 0 1 0 10 2 0 0.0006 0.094 0 0.0096 0 <1.00e-15 <4.60e-13
19 C1S complement component 1, s subcomponent 1428871 17 12 4 2 0 1 0 8 8 0 0.002 0.35 0 0.000091 0 <1.00e-15 <4.60e-13
20 EFNB3 ephrin-B3 543578 12 12 1 0 0 0 0 0 12 0 8.8e-06 1 0 0.57 0 <1.00e-15 <4.60e-13
21 OSBPL3 oxysterol binding protein-like 3 1853774 12 12 3 2 0 0 0 0 11 1 0.014 0.66 2e-07 0.052 0 <1.00e-15 <4.60e-13
22 SPDYE3 speedy homolog E3 (Xenopus laevis) 497061 12 12 1 0 0 0 0 0 12 0 8.1e-06 1 0 0.18 0 <1.00e-15 <4.60e-13
23 TSKS testis-specific serine kinase substrate 1074725 11 11 2 0 0 1 0 0 10 0 0.0026 0.55 0 0.77 0 <1.00e-15 <4.60e-13
24 ZNF598 zinc finger protein 598 1054956 11 11 2 3 0 0 10 0 1 0 0.012 0.64 0 1 0 <1.00e-15 <4.60e-13
25 PHYH phytanoyl-CoA 2-hydroxylase 649189 10 10 2 0 0 0 0 1 9 0 0.00013 0.86 0 1 0 <1.00e-15 <4.60e-13
26 ABCC1 ATP-binding cassette, sub-family C (CFTR/MRP), member 1 3104019 10 9 7 2 1 2 1 1 5 0 0.42 0.57 0.002 6e-06 0 <1.00e-15 <4.60e-13
27 CHSY1 chondroitin sulfate synthase 1 1419323 9 9 3 1 0 0 0 2 7 0 0.046 0.94 0.00014 0.00055 0 <1.00e-15 <4.60e-13
28 OR4A47 olfactory receptor, family 4, subfamily A, member 47 618481 10 9 2 0 0 0 0 10 0 0 0.000045 0.16 0 0.92 0 <1.00e-15 <4.60e-13
29 SDHAF2 succinate dehydrogenase complex assembly factor 2 350232 9 9 1 0 0 0 0 0 9 0 0.000014 0.24 0 0.0067 0 <1.00e-15 <4.60e-13
30 RBPJL recombination signal binding protein for immunoglobulin kappa J region-like 889800 8 8 3 1 0 0 1 1 6 0 0.0058 0.85 1.8e-06 0.000047 0 <1.00e-15 <4.60e-13
31 RRAS2 related RAS viral (r-ras) oncogene homolog 2 367625 8 8 1 0 0 0 0 0 8 0 0.00012 0.3 0 0.14 0 <1.00e-15 <4.60e-13
32 TRH thyrotropin-releasing hormone 409613 8 8 1 0 0 0 0 0 8 0 0.0003 1 0 0.42 0 <1.00e-15 <4.60e-13
33 ZMAT2 zinc finger, matrin type 2 421142 7 7 1 1 0 0 0 0 7 0 0.00093 0.77 2e-07 0.29 0 <1.00e-15 <4.60e-13
34 FAM194B family with sequence similarity 194, member B 762812 10 6 6 0 1 2 6 0 1 0 0.00052 0.028 0 0.62 0 <1.00e-15 <4.60e-13
35 NSFL1C NSFL1 (p97) cofactor (p47) 706055 6 6 1 0 0 0 0 0 6 0 0.049 1 0 0.44 0 <1.00e-15 <4.60e-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.

OR4A47

Figure S4.  This figure depicts the distribution of mutations and mutation types across the OR4A47 significant gene.

TRH

Figure S5.  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: 86. 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 245 541 241 366798 5841 0 0
2 MET met proto-oncogene (hepatocyte growth factor receptor) 22 34 7 23052 27 0 0
3 TP53 tumor protein p53 50 356 43 241368 4958 0 0
4 PIK3CA phosphoinositide-3-kinase, catalytic, alpha polypeptide 14 220 11 149160 4308 0 0
5 PTEN phosphatase and tensin homolog (mutated in multiple advanced cancers 1) 34 767 34 520026 641 0 0
6 NF2 neurofibromin 2 (merlin) 16 550 12 372900 77 7.9e-11 6e-08
7 PTCH1 patched homolog 1 (Drosophila) 11 256 8 173568 13 7.3e-09 4.8e-06
8 SMARCB1 SWI/SNF related, matrix associated, actin dependent regulator of chromatin, subfamily b, member 1 8 129 6 87462 20 5.6e-08 0.000032
9 STXBP3 syntaxin binding protein 3 6 1 2 678 2 1.1e-06 0.00049
10 TMEM47 transmembrane protein 47 2 1 2 678 2 1.1e-06 0.00049

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: 9. 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 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(16), HIF1A(4), JUN(2), NOS3(4), P4HB(2), VHL(245) 16864926 279 254 173 19 9 11 30 80 146 3 5.8e-08 1.6e-15 6.8e-13
2 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), EIF2B4(1), EIF2B5(2), EIF2S2(2), EIF2S3(2), FLT1(10), FLT4(14), HIF1A(4), HRAS(1), KDR(6), NOS3(4), PIK3CA(14), PIK3R1(5), PLCG1(4), PRKCA(2), PTK2(3), PXN(3), SHC1(4), VHL(245) 34047014 334 280 225 33 20 25 37 95 155 2 3.8e-07 2.9e-15 6.8e-13
3 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), ANAPC10(1), ANAPC11(1), ANAPC2(2), ANAPC4(6), ANAPC5(3), ANAPC7(2), BTRC(2), CDC16(4), CDC20(3), CDC23(2), CDC27(14), CUL1(5), CUL2(4), CUL3(13), FBXW11(2), FBXW7(6), FZR1(4), RBX1(1), SKP2(1), SMURF2(4), TCEB1(4), TCEB2(1), UBA1(4), UBE2D1(2), UBE2D2(1), UBE2D3(2), UBE2E2(1), VHL(245), WWP1(8), WWP2(4) 40744239 356 305 248 31 18 24 45 105 162 2 1.1e-08 3.3e-15 6.8e-13
4 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(2), SP1(2), SP3(2), TP53(50), WT1(3) 6959343 66 56 57 4 5 7 5 21 25 3 0.00016 5.4e-15 8.4e-13
5 RNAPATHWAY dsRNA-activated protein kinase phosphorylates elF2a, which generally inhibits translation, and activates NF-kB to provoke inflammation. CHUK, DNAJC3, EIF2S1, EIF2S2, MAP3K14, NFKB1, NFKBIA, PRKR, RELA, TP53 9 CHUK(2), DNAJC3(2), EIF2S2(2), MAP3K14(2), NFKB1(2), NFKBIA(2), RELA(6), TP53(50) 10030074 68 57 56 6 6 11 5 17 25 4 0.0013 8e-08 9.8e-06
6 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 18 ABCB1(4), AKT1(3), ATM(20), BAX(1), CDKN1A(3), CPB2(6), CSNK1A1(2), FHL2(1), HIF1A(4), IGFBP3(1), NFKBIB(2), TP53(50) 20275174 97 81 84 6 8 10 10 29 35 5 0.000015 3.6e-07 0.000037
7 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 ARF1(1), ARF3(3), CDK2(2), CDK4(6), CDKN1A(3), CDKN1B(1), CDKN2A(5), CFL1(1), E2F1(1), E2F2(1), PRB1(10), TP53(50) 8179625 84 66 67 11 5 7 8 21 38 5 0.018 7.9e-07 0.000069
8 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(3), AKT2(5), AKT3(3), GRB2(2), ILK(4), MAPK3(3), PDK1(1), PIK3CA(14), PIK3CD(2), PTEN(34), PTK2B(3), RBL2(5), SHC1(4), SOS1(9) 20233576 92 80 85 6 7 17 10 24 31 3 0.000034 2.4e-06 0.00019
9 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(9), CDKN2A(5), E2F1(1), MYC(2), PIK3CA(14), PIK3R1(5), POLR1A(6), POLR1B(4), POLR1C(3), POLR1D(1), RAC1(1), RB1(4), TP53(50) 19807798 105 87 90 12 8 21 8 33 30 5 0.00027 0.00054 0.037
10 PTENPATHWAY PTEN suppresses AKT-induced cell proliferation and antagonizes the action of PI3K. AKT1, BCAR1, CDKN1B, FOXO3A, GRB2, ILK, ITGB1, MAPK1, MAPK3, PDK2, PDPK1, PIK3CA, PIK3R1, PTEN, PTK2, SHC1, SOS1, TNFSF6 16 AKT1(3), BCAR1(6), CDKN1B(1), GRB2(2), ILK(4), ITGB1(7), MAPK3(3), PDK2(3), PIK3CA(14), PIK3R1(5), PTEN(34), PTK2(3), SHC1(4), SOS1(9) 19180015 98 84 91 13 6 16 9 27 36 4 0.02 0.0041 0.25

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 BETAOXIDATIONPATHWAY Beta-Oxidation of Fatty Acids ACADL, ACADM, ACADS, ACAT1, ECHS1, HADHA 6 ACADL(3), ACADM(1), ACADS(3), ACAT1(1), ECHS1(3), HADHA(4) 5419468 15 15 14 0 3 2 4 5 0 1 0.0087 0.048 1
2 HSA00950_ALKALOID_BIOSYNTHESIS_I Genes involved in alkaloid biosynthesis I DDC, GOT1, GOT2, TAT, TYR 5 DDC(3), GOT1(3), GOT2(2), TAT(2), TYR(5) 4732052 15 15 15 1 2 1 3 4 5 0 0.15 0.066 1
3 CAPROLACTAM_DEGRADATION AKR1A1, ECHS1, EHHADH, HADHA, SDS 5 AKR1A1(2), ECHS1(3), EHHADH(6), HADHA(4) 4888973 15 15 14 1 1 3 4 4 3 0 0.038 0.078 1
4 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 3 CD28(1), HLA-DRA(1), HLA-DRB1(6) 1241979 8 7 8 2 1 3 1 1 2 0 0.5 0.084 1
5 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(2), ARG1(1), GLS(7), OAT(2), PRODH(4) 5565788 16 16 16 1 1 3 5 4 3 0 0.063 0.094 1
6 HSA00750_VITAMIN_B6_METABOLISM Genes involved in vitamin B6 metabolism AOX1, PDXK, PDXP, PNPO, PSAT1 5 AOX1(8), PDXK(3), PDXP(2), PSAT1(2) 4789589 15 14 15 1 3 1 1 6 4 0 0.13 0.11 1
7 CYANOAMINO_ACID_METABOLISM ATP6V0C, SHMT1, GBA3, GGT1, SHMT1, SHMT2 5 GBA3(3), GGT1(4), SHMT1(2), SHMT2(5) 4094910 14 14 14 2 1 1 4 5 3 0 0.25 0.12 1
8 HSA00300_LYSINE_BIOSYNTHESIS Genes involved in lysine biosynthesis AADAT, AASDHPPT, AASS, KARS 4 AADAT(2), AASDHPPT(3), AASS(9), KARS(1) 4802785 15 15 15 2 0 3 3 4 5 0 0.28 0.12 1
9 CTLPATHWAY Cytotoxic T lymphocytes induce apoptosis in infected cells presenting antigen-MHC-I complexes via the perforin and Fas/Fas ligand pathways. B2M, CD3D, CD3E, CD3G, CD3Z, GZMB, HLA-A, ICAM1, ITGAL, ITGB2, PRF1, TNFRSF6, TNFSF6, TRA@, TRB@ 10 B2M(3), CD3E(2), CD3G(2), HLA-A(6), ICAM1(3), ITGAL(7), ITGB2(2), PRF1(1) 8328704 26 24 26 2 2 6 3 10 4 1 0.02 0.13 1
10 LYSINE_BIOSYNTHESIS AADAT, AASDH, AASDHPPT, AASS, KARS 5 AADAT(2), AASDH(5), AASDHPPT(3), AASS(9), KARS(1) 7059407 20 20 20 2 0 4 4 6 6 0 0.13 0.13 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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