Mutation Analysis (MutSig v2.0)
Uveal Melanoma (Primary solid tumor)
21 August 2015  |  analyses__2015_08_21
Maintainer Information
Citation Information
doi:10.7908/C1R49Q28
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/C1R49Q28
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: UVM-TP

  • Number of patients in set: 80

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:UVM-TP.final_analysis_set.maf

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

  • Significantly mutated genes (q ≤ 0.1): 7

  • Mutations seen in COSMIC: 43

  • Significantly mutated genes in COSMIC territory: 3

  • Significantly mutated genesets: 39

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

Mutation Preprocessing

  • Read 80 MAFs of type "maf1"

  • Total number of mutations in input MAFs: 2528

  • After removing 271 blacklisted mutations: 2257

  • After removing 190 noncoding mutations: 2067

Mutation Filtering

  • Number of mutations before filtering: 2067

  • After removing 142 mutations outside gene set: 1925

Results
Breakdown of Mutations by Type

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

type count
De_novo_Start_OutOfFrame 1
Frame_Shift_Del 75
Frame_Shift_Ins 17
In_Frame_Del 21
In_Frame_Ins 2
Missense_Mutation 1226
Nonsense_Mutation 68
Silent 464
Splice_Site 49
Start_Codon_SNP 2
Total 1925
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 560 121008619 4.6e-06 4.6 7.1 2.1
*Cp(A/C/T)->T 186 1019738599 1.8e-07 0.18 0.28 1.7
A->G 137 1112999983 1.2e-07 0.12 0.19 2.3
transver 345 2253747201 1.5e-07 0.15 0.24 5.1
indel+null 233 2253747201 1e-07 0.1 0.16 NaN
double_null 0 2253747201 0 0 0 NaN
Total 1461 2253747201 6.5e-07 0.65 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: UVM-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: 7. 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 GNAQ guanine nucleotide binding protein (G protein), q polypeptide 80906 41 40 4 0 2 0 0 38 1 0 <1.00e-15 0.0012 0 0.00017 0 <1.00e-15 <4.49e-12
2 GNA11 guanine nucleotide binding protein (G protein), alpha 11 (Gq class) 77747 36 36 3 0 2 0 0 34 0 0 <1.00e-15 0.0013 0 0.00021 0 <1.00e-15 <4.49e-12
3 SF3B1 splicing factor 3b, subunit 1, 155kDa 313797 18 18 5 0 14 0 1 3 0 0 8.22e-15 0.012 0 0.88 0 <1.00e-15 <4.49e-12
4 EIF1AX eukaryotic translation initiation factor 1A, X-linked 34466 10 10 6 0 0 4 0 3 3 0 1.89e-14 0.11 4e-06 0.0013 0 <1.00e-15 <4.49e-12
5 PRMT8 protein arginine methyltransferase 8 92574 5 5 1 0 0 0 5 0 0 0 6.84e-11 0.33 0 1 3e-06 7.66e-15 2.75e-11
6 BAP1 BRCA1 associated protein-1 (ubiquitin carboxy-terminal hydrolase) 135417 10 10 10 0 0 0 0 2 8 0 1.70e-14 0.32 0.2 0.089 0.11 6.68e-14 2.00e-10
7 CYSLTR2 cysteinyl leukotriene receptor 2 83578 3 3 1 0 0 0 0 3 0 0 6.70e-06 0.58 0.000083 0.0039 0.000011 1.86e-09 4.76e-06
8 PLCB4 phospholipase C, beta 4 294902 3 2 2 0 1 0 0 2 0 0 0.0113 0.54 0.000083 0.025 0.00034 5.08e-05 0.114
9 TMEM216 transmembrane protein 216 25145 2 2 1 0 0 0 0 0 2 0 2.41e-05 0.65 0.066 1 0.31 9.47e-05 0.189
10 MAPKAPK5 mitogen-activated protein kinase-activated protein kinase 5 80593 2 2 2 0 0 0 0 0 2 0 0.000191 1 0.99 0.014 0.086 0.000198 0.335
11 PLCB2 phospholipase C, beta 2 246300 3 3 3 0 1 0 0 0 2 0 0.000103 0.55 0.094 0.5 0.18 0.000224 0.335
12 GMEB2 glucocorticoid modulatory element binding protein 2 98241 2 2 2 0 0 0 1 0 1 0 0.000123 0.67 0.026 0.63 0.16 0.000239 0.335
13 KRTAP5-2 keratin associated protein 5-2 43040 1 1 1 0 1 0 0 0 0 0 0.000242 0.6 NaN NaN NaN 0.000242 0.335
14 UBE2N ubiquitin-conjugating enzyme E2N (UBC13 homolog, yeast) 37996 1 1 1 0 1 0 0 0 0 0 0.000322 0.73 NaN NaN NaN 0.000322 0.413
15 COL14A1 collagen, type XIV, alpha 1 445955 3 3 3 0 1 1 1 0 0 0 0.000611 0.3 0.074 0.096 0.052 0.000359 0.429
16 PLEKHF2 pleckstrin homology domain containing, family F (with FYVE domain) member 2 60320 1 1 1 0 1 0 0 0 0 0 0.000520 0.9 NaN NaN NaN 0.000520 0.583
17 EIF1B eukaryotic translation initiation factor 1B 28613 2 2 2 0 0 0 0 1 1 0 5.79e-05 0.86 0.79 0.81 1 0.000622 0.657
18 HSD17B7 hydroxysteroid (17-beta) dehydrogenase 7 82585 2 2 2 0 0 1 0 1 0 0 0.000217 0.52 0.28 0.26 0.52 0.00113 1.000
19 OR1L1 olfactory receptor, family 1, subfamily L, member 1 74800 1 1 1 0 1 0 0 0 0 0 0.00124 0.75 NaN NaN NaN 0.00124 1.000
20 TMOD2 tropomodulin 2 (neuronal) 87077 1 1 1 0 1 0 0 0 0 0 0.00125 0.77 NaN NaN NaN 0.00125 1.000
21 RPTN repetin 189040 2 2 2 0 1 0 1 0 0 0 0.000205 0.46 0.27 0.74 0.64 0.00129 1.000
22 OR52M1 olfactory receptor, family 52, subfamily M, member 1 76532 1 1 1 0 0 0 1 0 0 0 0.00152 0.72 NaN NaN NaN 0.00152 1.000
23 SELE selectin E (endothelial adhesion molecule 1) 149603 2 2 2 0 0 0 0 2 0 0 0.00201 0.72 0.14 0.025 0.082 0.00159 1.000
24 XRCC3 X-ray repair complementing defective repair in Chinese hamster cells 3 34076 1 1 1 0 0 0 1 0 0 0 0.00164 0.73 NaN NaN NaN 0.00164 1.000
25 CCDC126 coiled-coil domain containing 126 34118 1 1 1 1 0 0 1 0 0 0 0.00165 0.87 NaN NaN NaN 0.00165 1.000
26 PCGF6 polycomb group ring finger 6 63580 1 1 1 0 0 0 0 0 1 0 0.00165 1 NaN NaN NaN 0.00165 1.000
27 ZNF680 zinc finger protein 680 120715 1 1 1 0 1 0 0 0 0 0 0.00173 0.85 NaN NaN NaN 0.00173 1.000
28 OR10G4 olfactory receptor, family 10, subfamily G, member 4 73881 1 1 1 0 0 0 1 0 0 0 0.00192 0.79 NaN NaN NaN 0.00192 1.000
29 MUC4 mucin 4, cell surface associated 217349 3 3 3 0 1 1 1 0 0 0 0.000254 0.28 0.5 0.66 0.81 0.00195 1.000
30 CNPY2 canopy 2 homolog (zebrafish) 45514 1 1 1 0 1 0 0 0 0 0 0.00206 0.79 NaN NaN NaN 0.00206 1.000
31 RAB2B RAB2B, member RAS oncogene family 54538 1 1 1 0 0 0 1 0 0 0 0.00229 0.72 NaN NaN NaN 0.00229 1.000
32 USP49 ubiquitin specific peptidase 49 148283 2 2 2 0 1 0 0 0 1 0 0.000789 0.58 0.39 0.066 0.32 0.00236 1.000
33 OR2D3 olfactory receptor, family 2, subfamily D, member 3 79663 1 1 1 0 0 1 0 0 0 0 0.00239 0.59 NaN NaN NaN 0.00239 1.000
34 ZSWIM1 zinc finger, SWIM-type containing 1 116960 1 1 1 0 0 0 1 0 0 0 0.00254 0.76 NaN NaN NaN 0.00254 1.000
35 GPR78 G protein-coupled receptor 78 56805 1 1 1 0 0 0 1 0 0 0 0.00261 0.83 NaN NaN NaN 0.00261 1.000
GNAQ

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

GNA11

Figure S2.  This figure depicts the distribution of mutations and mutation types across the GNA11 significant gene.

SF3B1

Figure S3.  This figure depicts the distribution of mutations and mutation types across the SF3B1 significant gene.

EIF1AX

Figure S4.  This figure depicts the distribution of mutations and mutation types across the EIF1AX significant gene.

PRMT8

Figure S5.  This figure depicts the distribution of mutations and mutation types across the PRMT8 significant gene.

BAP1

Figure S6.  This figure depicts the distribution of mutations and mutation types across the BAP1 significant gene.

CYSLTR2

Figure S7.  This figure depicts the distribution of mutations and mutation types across the CYSLTR2 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: 3. Number of genes displayed: 10

rank gene description n cos n_cos N_cos cos_ev p q
1 GNAQ guanine nucleotide binding protein (G protein), q polypeptide 41 4 37 320 3811 9.3e-15 4.2e-11
2 RAB38 RAB38, member RAS oncogene family 1 1 1 80 1 0.000052 0.078
3 RGAG4 retrotransposon gag domain containing 4 2 1 1 80 1 0.000052 0.078
4 GNA11 guanine nucleotide binding protein (G protein), alpha 11 (Gq class) 36 2 1 160 1 0.0001 0.12
5 RET ret proto-oncogene 1 49 1 3920 1 0.0025 1
6 BRCA2 breast cancer 2, early onset 2 59 1 4720 0 0.0031 1
7 FBXW7 F-box and WD repeat domain containing 7 1 91 1 7280 31 0.0047 1
8 CDKN2A cyclin-dependent kinase inhibitor 2A (melanoma, p16, inhibits CDK4) 1 332 1 26560 6 0.017 1
9 A4GNT alpha-1,4-N-acetylglucosaminyltransferase 0 0 0 0 0 1 1
10 AACS acetoacetyl-CoA synthetase 0 0 0 0 0 1 1

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: 39. 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 G_PROTEIN_SIGNALING ADCY1, ADCY2, ADCY3, ADCY4, ADCY5, ADCY6, ADCY7, ADCY8, ADCY9, AKAP1, AKAP10, AKAP11, AKAP12, AKAP2, PALM2_AKAP2, AKAP3, AKAP4, AKAP5, AKAP6, AKAP7, AKAP8, AKAP9, ARHGEF1, CALM1, CALM2, CALM3, CHMP1B, GNA11, GNA12, GNA13, GNA14, GNA15, GNAI2, GNAI3, GNAL, GNAO1, GNAQ, GNAZ, GNB1, GNB2, GNB3, GNB5, GNG10, GNG10, LOC552891, GNG12, GNG13, GNG3, GNG4, GNG5, GNG7, GNGT1, GNGT2, HRAS, IL18BP, ITPR1, KCNJ3, KRAS, MGC11266, NRAS, PALM2, PALM2_AKAP2, PALM2_AKAP2, PDE1A, PDE1B, PDE1C, PDE4A, PDE4B, PDE4C, PDE4D, PDE7A, PDE7B, PDE8A, PDE8B, PLCB3, PPP3CA, PPP3CC, PRKACA, PRKACB, PRKACG, PRKAR1A, PRKAR1B, PRKAR2A, PRKAR2B, PRKCA, PRKCB1, PRKCD, PRKCE, PRKCG, PRKCH, PRKCI, PRKCQ, PRKCZ, PRKD1, PRKD3, RHOA, RRAS, SARA1, SLC9A1, USP5 92 ADCY4(1), AKAP9(1), GNA11(36), GNAQ(41), GNB1(2), GNB3(1), ITPR1(1), PDE4D(1), PDE8B(1), PRKD1(1) 13427629 86 74 16 4 6 1 2 73 4 0 0.000086 <1.00e-15 <1.44e-13
2 PAR1PATHWAY Activated extracellular thrombin cleaves and activates the G-protein coupled receptors PAR1 and PAR4, which activate platelets. ADCY1, ARHA, ARHGEF1, F2, F2R, F2RL3, GNA12, GNA13, GNAI1, GNAQ, GNB1, GNGT1, MAP3K7, PIK3CA, PIK3R1, PLCB1, PPP1R12B, PRKCA, PRKCB1, PTK2B, ROCK1 19 GNAQ(41), GNB1(2) 2979174 43 41 6 0 3 0 0 39 1 0 0.00042 <1.00e-15 <1.44e-13
3 PYK2PATHWAY Pyk2 and Rac1 stimulate the JNK cascade and activate MKK3, which activates p38. BCAR1, CALM1, CALM2, CALM3, CRKL, GNAQ, GRB2, HRAS, JUN, MAP2K1, MAP2K2, MAP2K3, MAP2K4, MAP3K1, MAPK1, MAPK14, MAPK3, MAPK8, PAK1, PLCG1, PRKCA, PRKCB1, PTK2B, RAC1, RAF1, SHC1, SOS1, SRC, SYT1 28 GNAQ(41), MAP2K3(1) 3298743 42 40 5 0 2 0 0 38 2 0 0.00037 <1.00e-15 <1.44e-13
4 CALCIUM_REGULATION_IN_CARDIAC_CELLS ADCY1, ADCY2, ADCY3, ADCY4, ADCY5, ADCY6, ADCY7, ADCY8, ADCY9, ADRA1A, ADRA1B, ADRA1D, ADRB1, ADRB2, ADRB3, ANXA6, ARRB1, ARRB2, ATP1A4, ATP1B1, ATP1B2, ATP1B3, ATP2A2, ATP2A3, ATP2B1, ATP2B2, ATP2B3, CACNA1A, CACNA1B, CACNA1C, CACNA1D, CACNA1E, CACNA1S, CACNB1, CACNB3, CALM1, CALM2, CALM3, CALR, CAMK1, CAMK2A, CAMK2B, CAMK2D, CAMK2G, CAMK4, CASQ1, CASQ2, CHRM1, CHRM2, CHRM3, CHRM4, CHRM5, FXYD2, GJA1, GJA12, GJA4, GJA5, GJB1, GJB2, GJB3, GJB4, GJB5, GJB6, GNA11, GNAI2, GNAI3, GNAO1, GNAQ, GNAZ, GNB1, GNB2, GNB3, GNB4, GNB5, GNG12, GNG13, GNG2, GNG3, GNG4, GNG5, GNG7, GNGT1, GRK4, GRK5, GRK6, ITPR1, ITPR2, ITPR3, KCNB1, KCNJ3, KCNJ5, MGC11266, MYCBP, NME7, PEA15, PKIA, PKIB, PKIG, PLCB3, PLN, PRKACA, PRKACB, PRKAR1A, PRKAR1B, PRKAR2A, PRKAR2B, PRKCA, PRKCB1, PRKCD, PRKCE, PRKCG, PRKCH, PRKCQ, PRKCZ, PRKD1, RGS1, RGS10, RGS11, RGS14, RGS16, RGS17, RGS18, RGS19, RGS2, RGS20, RGS3, RGS4, RGS5, RGS6, RGS7, RGS9, RYR1, RYR2, RYR3, SARA1, SFN, SLC8A1, SLC8A3, USP5, YWHAB, YWHAH, YWHAQ, YWHAQ, MIB1 137 ADCY4(1), ATP2A3(1), CACNA1A(1), CACNA1B(2), CACNA1C(1), CACNA1D(2), CHRM1(1), GJA1(1), GNA11(36), GNAQ(41), GNB1(2), GNB3(1), ITPR1(1), NME7(1), PRKD1(1), RYR1(1), RYR2(2), RYR3(1) 21185595 97 75 27 10 11 2 2 76 6 0 0.0012 1.22e-15 1.44e-13
5 HSA04020_CALCIUM_SIGNALING_PATHWAY Genes involved in calcium signaling pathway ADCY1, ADCY2, ADCY3, ADCY4, ADCY7, ADCY8, ADCY9, ADORA2A, ADORA2B, ADRA1A, ADRA1B, ADRA1D, ADRB1, ADRB2, ADRB3, AGTR1, ATP2A1, ATP2A2, ATP2A3, ATP2B1, ATP2B2, ATP2B3, ATP2B4, AVPR1A, AVPR1B, BDKRB1, BDKRB2, BST1, CACNA1A, CACNA1B, CACNA1C, CACNA1D, CACNA1E, CACNA1F, CACNA1G, CACNA1H, CACNA1I, CACNA1S, CALM1, CALM2, CALM3, CALML3, CALML6, CAMK2A, CAMK2B, CAMK2D, CAMK2G, CAMK4, CCKAR, CCKBR, CD38, CHP, CHRM1, CHRM2, CHRM3, CHRM5, CHRNA7, CYSLTR1, CYSLTR2, DRD1, EDNRA, EDNRB, EGFR, ERBB2, ERBB3, ERBB4, F2R, GNA11, GNA14, GNA15, GNAL, GNAQ, GNAS, GRIN1, GRIN2A, GRIN2C, GRIN2D, GRM1, GRM5, GRPR, HRH1, HRH2, HTR2A, HTR2B, HTR2C, HTR4, HTR5A, HTR6, HTR7, ITPKA, ITPKB, ITPR1, ITPR2, ITPR3, LHCGR, LTB4R2, MLCK, MYLK, MYLK2, NOS1, NOS2A, NOS3, NTSR1, OXTR, P2RX1, P2RX2, P2RX3, P2RX4, P2RX5, P2RX7, P2RXL1, PDE1A, PDE1B, PDE1C, PDGFRA, PDGFRB, PHKA1, PHKA2, PHKB, PHKG1, PHKG2, PLCB1, PLCB2, PLCB3, PLCB4, PLCD1, PLCD3, PLCD4, PLCE1, PLCG1, PLCG2, PLCZ1, PLN, PPID, PPP3CA, PPP3CB, PPP3CC, PPP3R1, PPP3R2, PRKACA, PRKACB, PRKACG, PRKCA, PRKCB1, PRKCG, PRKX, PRKY, PTAFR, PTGER1, PTGER3, PTGFR, PTK2B, RYR1, RYR2, RYR3, SLC25A4, SLC25A5, SLC25A6, SLC8A1, SLC8A2, SLC8A3, SPHK1, SPHK2, TACR1, TACR2, TACR3, TBXA2R, TNNC1, TNNC2, TRHR, TRPC1, VDAC1, VDAC2, VDAC3 167 ADCY4(1), ATP2A3(1), CACNA1A(1), CACNA1B(2), CACNA1C(1), CACNA1D(2), CHRM1(1), CYSLTR2(3), ERBB4(1), GNA11(36), GNAQ(41), GRIN2A(1), HTR2B(1), ITPKB(1), ITPR1(1), P2RX3(1), PDGFRA(1), PHKA2(1), PLCB2(3), PLCB4(3), PLCD4(1), PLCE1(1), RYR1(1), RYR2(2), RYR3(1), SLC25A6(1) 30452509 110 79 37 9 15 2 0 83 10 0 0.000055 1.33e-15 1.44e-13
6 VIPPATHWAY Apoptosis of activated T cells is inhibited by vasoactive intestinal peptide (VIP) and its relative PACAP. CALM1, CALM2, CALM3, CHUK, EGR2, EGR3, GNAQ, MAP3K1, MYC, NFATC1, NFATC2, NFKB1, NFKBIA, PLCG1, PPP3CA, PPP3CB, PPP3CC, PRKACB, PRKACG, PRKAR1A, PRKAR1B, PRKAR2A, PRKAR2B, RELA, SYT1, VIP, VIPR2 27 GNAQ(41), NFATC2(1) 3243383 42 41 5 1 3 0 0 38 1 0 0.0023 1.67e-15 1.44e-13
7 HSA04540_GAP_JUNCTION Genes involved in gap junction ADCY1, ADCY2, ADCY3, ADCY4, ADCY5, ADCY6, ADCY7, ADCY8, ADCY9, ADRB1, CDC2, CSNK1D, DRD1, DRD2, EDG2, EGF, EGFR, GJA1, GJD2, GNA11, GNAI1, GNAI2, GNAI3, GNAQ, GNAS, GRB2, GRM1, GRM5, GUCY1A2, GUCY1A3, GUCY1B3, GUCY2C, GUCY2D, GUCY2F, HRAS, HTR2A, HTR2B, HTR2C, ITPR1, ITPR2, ITPR3, KRAS, LOC643224, LOC654264, MAP2K1, MAP2K2, MAP2K5, MAP3K2, MAPK1, MAPK3, MAPK7, NPR1, NPR2, NRAS, PDGFA, PDGFB, PDGFC, PDGFD, PDGFRA, PDGFRB, PLCB1, PLCB2, PLCB3, PLCB4, PRKACA, PRKACB, PRKACG, PRKCA, PRKCB1, PRKCG, PRKG1, PRKG2, PRKX, PRKY, RAF1, SOS1, SOS2, SRC, TJP1, TUBA1A, TUBA1B, TUBA1C, TUBA3C, TUBA3D, TUBA3E, TUBA4A, TUBA8, TUBAL3, TUBB, TUBB1, TUBB2A, TUBB2B, TUBB2C, TUBB3, TUBB4, TUBB4Q, TUBB6, TUBB8 92 ADCY4(1), EGF(1), GJA1(1), GNA11(36), GNAQ(41), HTR2B(1), ITPR1(1), PDGFRA(1), PLCB2(3), PLCB4(3), PRKG1(1) 15229164 90 75 19 6 10 0 0 75 5 0 0.00017 1.89e-15 1.44e-13
8 CALCINEURINPATHWAY Increased intracellular calcium activates the phosphatase calcineurin in differentiating keratinocytes. CALM1, CALM2, CALM3, CDKN1A, GNAQ, MARCKS, NFATC1, NFATC2, NFATC3, NFATC4, PLCG1, PPP3CA, PPP3CB, PPP3CC, PRKCA, PRKCB1, SP1, SP3, SYT1 18 GNAQ(41), NFATC2(1) 2445629 42 41 5 1 3 0 0 38 1 0 0.0016 2.11e-15 1.44e-13
9 MYOSINPATHWAY Myosin light chain kinase phosphorylates myosin and promotes muscle contraction and platelet formation; myosin phosphatase antagonizes these processes. ARHGAP5, ARHGEF1, GNA12, GNA13, GNAQ, GNB1, GNGT1, MYL2, MYLK, PLCB1, PPP1R12B, PRKCA, PRKCB1, PRKCL1, ROCK1 13 GNAQ(41), GNB1(2) 2393153 43 41 6 0 3 0 0 39 1 0 0.00046 2.11e-15 1.44e-13
10 TUBBYPATHWAY Tubby is activated by phospholipase C activity and hydrolysis of PIP2, after which it enters the nucleus and regulates transcription. CHRM1, GNAQ, GNB1, GNGT1, HTR2C, PLCB1, TUB 7 CHRM1(1), GNAQ(41), GNB1(2) 840313 44 41 7 0 4 0 0 39 1 0 0.00018 2.55e-15 1.47e-13

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 HSA04742_TASTE_TRANSDUCTION Genes involved in taste transduction ACCN1, ADCY4, ADCY6, ADCY8, CACNA1A, CACNA1B, GNAS, GNAT3, GNB1, GNB3, GNG13, GNG3, GRM4, ITPR3, KCNB1, PDE1A, PLCB2, PRKACA, PRKACB, PRKACG, PRKX, PRKY, SCNN1A, SCNN1B, SCNN1G, TAS1R1, TAS1R2, TAS1R3, TAS2R1, TAS2R10, TAS2R13, TAS2R14, TAS2R16, TAS2R3, TAS2R38, TAS2R39, TAS2R4, TAS2R40, TAS2R41, TAS2R42, TAS2R43, TAS2R44, TAS2R45, TAS2R46, TAS2R48, TAS2R49, TAS2R5, TAS2R50, TAS2R60, TAS2R7, TAS2R8, TAS2R9, TRPM5 48 ADCY4(1), CACNA1A(1), CACNA1B(2), GNB1(2), GNB3(1), PLCB2(3), TAS1R2(1), TRPM5(1) 6427695 12 11 12 2 4 1 1 2 4 0 0.32 0.00055 0.34
2 SA_DIACYLGLYCEROL_SIGNALING DAG (diacylglycerol) signaling activity ESR1, ESR2, ITPKA, PDE1A, PDE1B, PLCB1, PLCB2, PRL, TRH, VIP 10 ESR1(1), PLCB2(3) 1275965 4 4 4 0 1 1 0 0 2 0 0.31 0.0025 0.78
3 STEROID_BIOSYNTHESIS CYP17A1, F13B, HSD17B1, HSD17B2, HSD17B3, HSD17B4, HSD17B7, HSD3B1, HSD3B2 9 CYP17A1(1), HSD17B1(1), HSD17B7(2) 949947 4 3 4 0 1 1 1 1 0 0 0.24 0.0053 1
4 TUBBYPATHWAY Tubby is activated by phospholipase C activity and hydrolysis of PIP2, after which it enters the nucleus and regulates transcription. CHRM1, GNAQ, GNB1, GNGT1, HTR2C, PLCB1, TUB 6 CHRM1(1), GNB1(2) 759407 3 3 3 0 2 0 0 1 0 0 0.4 0.0093 1
5 HSA00533_KERATAN_SULFATE_BIOSYNTHESIS Genes involved in keratan sulfate biosynthesis B3GNT1, B3GNT2, B3GNT7, B4GALT1, B4GALT2, B4GALT3, B4GALT4, CHST1, CHST2, CHST4, CHST6, FUT8, ST3GAL1, ST3GAL2, ST3GAL3, ST3GAL4 16 B4GALT4(1), CHST2(1), CHST4(1), ST3GAL3(1) 1414921 4 4 4 0 3 1 0 0 0 0 0.19 0.012 1
6 1_2_DICHLOROETHANE_DEGRADATION ALDH1A1, ALDH1A2, ALDH1A3, ALDH1B1, ALDH2, ALDH3A1, ALDH3A2, ALDH9A1 8 ALDH1A3(1), ALDH2(1), ALDH9A1(1) 922476 3 3 3 0 1 1 0 1 0 0 0.33 0.013 1
7 ASCORBATE_AND_ALDARATE_METABOLISM ALDH1A1, ALDH1A2, ALDH1A3, ALDH1B1, ALDH2, ALDH3A1, ALDH3A2, ALDH9A1 8 ALDH1A3(1), ALDH2(1), ALDH9A1(1) 922476 3 3 3 0 1 1 0 1 0 0 0.33 0.013 1
8 HSA00053_ASCORBATE_AND_ALDARATE_METABOLISM Genes involved in ascorbate and aldarate metabolism ALDH1A3, ALDH1B1, ALDH2, ALDH3A1, ALDH3A2, ALDH7A1, ALDH9A1, MIOX, UGDH 9 ALDH1A3(1), ALDH2(1), ALDH9A1(1) 984315 3 3 3 0 1 1 0 1 0 0 0.34 0.016 1
9 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 ARPC1B(1), ARPC2(1), PDGFRA(1) 1582336 3 3 3 1 1 1 1 0 0 0 0.64 0.018 1
10 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 CD4(1) 278162 1 1 1 0 0 0 1 0 0 0 0.75 0.026 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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