Mutation Analysis (MutSig v1.5)
Bladder Urothelial Carcinoma (Primary solid tumor)
15 January 2014  |  analyses__2014_01_15
Maintainer Information
Citation Information
doi:10.7908/C1NZ8621
Maintained by Dan DiCara (Broad Institute)
Cite as Broad Institute TCGA Genome Data Analysis Center (2014): Mutation Analysis (MutSig v1.5). Broad Institute of MIT and Harvard. doi:10.7908/C1NZ8621
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 v1.5 was used to generate the results found in this report.

  • Working with individual set: BLCA-TP

  • Number of patients in set: 28

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:BLCA-TP.final_analysis_set.maf

  • Significantly mutated genes (q ≤ 0.1): 6

  • Mutations seen in COSMIC: 35

  • Significantly mutated genes in COSMIC territory: 3

  • Significantly mutated genesets: 20

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

Mutation Preprocessing

  • Read 28 MAFs of type "Broad"

  • Total number of mutations in input MAFs: 7557

  • After removing 3 mutations outside chr1-24: 7554

  • After removing 166 blacklisted mutations: 7388

  • After removing 126 noncoding mutations: 7262

Mutation Filtering

  • Number of mutations before filtering: 7262

  • After removing 79 mutations outside gene set: 7183

  • After removing 11 mutations outside category set: 7172

Results
Breakdown of Mutations by Type

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

type count
Frame_Shift_Del 85
Frame_Shift_Ins 37
In_Frame_Del 20
In_Frame_Ins 4
Missense_Mutation 4662
Nonsense_Mutation 418
Nonstop_Mutation 9
Silent 1814
Splice_Site 115
Translation_Start_Site 8
Total 7172
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
Tp*C->(T/G) 2634 108904258 0.000024 24 3.7 3
Tp*C->A 202 108904258 1.9e-06 1.9 0.28 4
(A/C/G)p*C->mut 1219 308289400 4e-06 4 0.61 3.2
A->mut 615 402887181 1.5e-06 1.5 0.23 3.9
indel+null 677 820080839 8.3e-07 0.83 0.13 NaN
double_null 11 820080839 1.3e-08 0.013 0.0021 NaN
Total 5358 820080839 6.5e-06 6.5 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: BLCA-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: Tp*C->(T/G)

  • n2 = number of nonsilent mutations of type: Tp*C->A

  • n3 = number of nonsilent mutations of type: (A/C/G)p*C->mut

  • n4 = number of nonsilent mutations of type: A->mut

  • n5 = number of nonsilent mutations of type: indel+null

  • n6 = number of nonsilent mutations of type: double_null

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

  • 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: 6. 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_ns_s p q
1 TP53 tumor protein p53 34506 14 11 13 1 2 0 8 1 3 0 0.1 9.2e-15 1.7e-10
2 KDM6A lysine (K)-specific demethylase 6A 109258 6 6 6 2 0 0 0 0 6 0 0.98 3.4e-06 0.031
3 FBXW7 F-box and WD repeat domain containing 7 68665 6 5 5 0 2 0 2 0 2 0 0.34 8.3e-06 0.05
4 GPS2 G protein pathway suppressor 2 26706 3 3 3 0 0 1 0 0 1 1 0.58 0.000012 0.056
5 NFE2L2 nuclear factor (erythroid-derived 2)-like 2 50092 4 4 4 0 1 0 1 2 0 0 0.4 0.000017 0.062
6 HCN1 hyperpolarization activated cyclic nucleotide-gated potassium channel 1 68545 4 4 4 1 1 0 1 0 1 1 0.61 0.000022 0.067
7 ARID1A AT rich interactive domain 1A (SWI-like) 162255 8 6 8 1 3 0 0 0 5 0 0.66 0.000054 0.14
8 HLA-A major histocompatibility complex, class I, A 29882 3 3 3 0 0 0 1 0 2 0 0.54 0.0001 0.22
9 PPBP pro-platelet basic protein (chemokine (C-X-C motif) ligand 7) 11172 2 2 2 0 0 1 1 0 0 0 0.56 0.00011 0.22
10 ERCC2 excision repair cross-complementing rodent repair deficiency, complementation group 2 (xeroderma pigmentosum D) 60112 4 4 4 0 1 0 1 2 0 0 0.35 0.00013 0.22
11 PCDHAC1 protocadherin alpha subfamily C, 1 82079 4 4 4 0 1 0 1 2 0 0 0.33 0.00014 0.22
12 OTUD7A OTU domain containing 7A 48592 4 4 4 0 3 0 1 0 0 0 0.28 0.00014 0.22
13 ELF3 E74-like factor 3 (ets domain transcription factor, epithelial-specific ) 32054 3 3 3 0 0 0 1 0 2 0 0.72 0.00019 0.24
14 HRNR hornerin 181633 6 6 6 0 2 1 2 1 0 0 0.34 0.0002 0.24
15 BCLAF1 BCL2-associated transcription factor 1 78524 5 4 5 0 2 0 0 2 1 0 0.4 0.0002 0.24
16 PYGO1 pygopus homolog 1 (Drosophila) 35616 3 3 3 0 0 0 1 1 1 0 0.52 0.00021 0.24
17 OPCML opioid binding protein/cell adhesion molecule-like 31380 3 3 3 1 1 0 1 1 0 0 0.73 0.00022 0.24
18 XPR1 xenotropic and polytropic retrovirus receptor 59450 5 4 5 1 3 0 0 0 2 0 0.64 0.00029 0.3
19 NAA25 N(alpha)-acetyltransferase 25, NatB auxiliary subunit 82616 4 4 4 0 1 1 1 0 1 0 0.44 0.00033 0.32
20 CUL1 cullin 1 67427 4 4 3 0 3 0 1 0 0 0 0.37 0.00043 0.39
21 C11orf85 chromosome 11 open reading frame 85 19112 2 2 2 0 0 0 0 1 1 0 0.58 0.00049 0.42
22 RFTN2 raftlin family member 2 40281 3 3 3 0 1 0 0 0 2 0 0.6 0.00054 0.45
23 KRTAP4-9 keratin associated protein 4-9 13465 2 2 2 1 0 0 1 1 0 0 0.9 0.00057 0.45
24 LETMD1 LETM1 domain containing 1 31332 3 3 3 0 1 0 0 2 0 0 0.42 0.0006 0.46
25 HEG1 HEG homolog 1 (zebrafish) 97799 4 4 4 0 1 0 0 2 1 0 0.36 0.00072 0.5
26 MTERFD2 MTERF domain containing 2 31783 3 3 3 0 1 0 1 1 0 0 0.48 0.00073 0.5
27 IL34 interleukin 34 19899 2 2 2 0 1 0 1 0 0 0 0.46 0.00074 0.5
28 ZNF99 zinc finger protein 99 87538 3 3 3 0 0 1 0 2 0 0 0.6 0.0009 0.58
29 C7orf36 chromosome 7 open reading frame 36 19403 2 2 2 0 2 0 0 0 0 0 0.65 0.00096 0.59
30 SLMAP sarcolemma associated protein 69823 3 3 3 0 0 0 0 0 3 0 0.67 0.00099 0.59
31 CDH22 cadherin-like 22 52386 3 3 3 0 1 0 1 1 0 0 0.43 0.0011 0.66
32 ACN9 ACN9 homolog (S. cerevisiae) 10808 2 2 2 1 1 0 0 1 0 0 0.89 0.0013 0.73
33 CREBBP CREB binding protein (Rubinstein-Taybi syndrome) 195325 5 5 5 1 0 0 2 0 3 0 0.54 0.0014 0.74
34 OR5K2 olfactory receptor, family 5, subfamily K, member 2 26703 2 2 2 0 0 1 1 0 0 0 0.61 0.0014 0.74
35 ZBTB37 zinc finger and BTB domain containing 37 30228 3 3 3 1 2 0 0 0 1 0 0.83 0.0014 0.74
TP53

Figure S1.  This figure depicts the distribution of mutations and mutation types across the TP53 significant gene.

KDM6A

Figure S2.  This figure depicts the distribution of mutations and mutation types across the KDM6A significant gene.

FBXW7

Figure S3.  This figure depicts the distribution of mutations and mutation types across the FBXW7 significant gene.

GPS2

Figure S4.  This figure depicts the distribution of mutations and mutation types across the GPS2 significant gene.

NFE2L2

Figure S5.  This figure depicts the distribution of mutations and mutation types across the NFE2L2 significant gene.

HCN1

Figure S6.  This figure depicts the distribution of mutations and mutation types across the HCN1 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 TP53 tumor protein p53 14 356 14 9968 2964 0 0
2 FBXW7 F-box and WD repeat domain containing 7 6 91 4 2548 102 3.2e-09 7.1e-06
3 FGFR3 fibroblast growth factor receptor 3 (achondroplasia, thanatophoric dwarfism) 2 62 2 1736 216 0.000064 0.096
4 DPYSL4 dihydropyrimidinase-like 4 1 1 1 28 2 0.00018 0.17
5 TBC1D8B TBC1 domain family, member 8B (with GRAM domain) 2 1 1 28 1 0.00018 0.17
6 BMX BMX non-receptor tyrosine kinase 2 2 1 56 2 0.00037 0.24
7 GABRA6 gamma-aminobutyric acid (GABA) A receptor, alpha 6 2 2 1 56 1 0.00037 0.24
8 BAZ1A bromodomain adjacent to zinc finger domain, 1A 1 4 1 112 1 0.00073 0.36
9 PHIP pleckstrin homology domain interacting protein 3 4 1 112 1 0.00073 0.36
10 PIK3CA phosphoinositide-3-kinase, catalytic, alpha polypeptide 3 220 2 6160 375 0.00079 0.36

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: 20. 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 TIDPATHWAY On ligand binding, interferon gamma receptors stimulate JAK2 kinase to phosphorylate STAT transcription factors, which promote expression of interferon responsive genes. DNAJA3, HSPA1A, IFNG, IFNGR1, IFNGR2, IKBKB, JAK2, LIN7A, NFKB1, NFKBIA, RB1, RELA, TIP-1, TNF, TNFRSF1A, TNFRSF1B, TP53, USH1C, WT1 18 IFNGR2(1), JAK2(1), RB1(2), RELA(1), TNFRSF1B(1), TP53(14), USH1C(1) 754587 21 15 19 1 5 1 9 1 4 1 0.023 1.8e-08 0.000011
2 PMLPATHWAY Ring-shaped PML nuclear bodies regulate transcription and are required co-activators in p53- and DAXX-mediated apoptosis. CREBBP, DAXX, HRAS, PAX3, PML, PRAM-1, RARA, RB1, SIRT1, SP100, TNF, TNFRSF1A, TNFRSF1B, TNFRSF6, TNFSF6, TP53, UBL1 13 CREBBP(5), DAXX(1), PML(3), RARA(2), RB1(2), SP100(1), TNFRSF1B(1), TP53(14) 792662 29 17 27 2 7 0 13 1 7 1 0.012 5.3e-08 0.000016
3 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 DNAJC3(1), RELA(1), TP53(14) 408205 16 12 15 1 4 0 8 1 3 0 0.085 2.9e-07 0.000059
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 SP3(2), TP53(14) 292760 16 12 15 2 4 0 8 1 3 0 0.19 8.3e-07 0.00013
5 FBW7PATHWAY Cyclin E interacts with cell cycle checkpoint kinase cdk2 to allow transcription of genes required for S phase, including transcription of additional cyclin E. CCNE1, CDC34, CDK2, CUL1, E2F1, FBXW7, RB1, SKP1A, TFDP1 8 CUL1(4), FBXW7(6), RB1(2) 343289 12 9 9 0 5 0 3 0 3 1 0.06 5.7e-06 0.0007
6 RBPATHWAY The ATM protein kinase recognizes DNA damage and blocks cell cycle progression by phosphorylating chk1 and p53, which normally inhibits Rb to allow G1/S transitions. ATM, CDC2, CDC25A, CDC25B, CDC25C, CDK2, CDK4, CHEK1, MYT1, RB1, TP53, WEE1, YWHAH 12 ATM(3), RB1(2), TP53(14), WEE1(1) 734757 20 16 18 3 3 0 9 2 5 1 0.3 0.000022 0.0022
7 PLK3PATHWAY Active Plk3 phosphorylates CDC25c, blocking the G2/M transition, and phosphorylates p53 to induce apoptosis. ATM, ATR, CDC25C, CHEK1, CHEK2, CNK, TP53, YWHAH 7 ATM(3), ATR(3), TP53(14) 670310 20 13 19 2 6 0 9 2 3 0 0.18 0.000065 0.0058
8 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 CCND1(1), CDKN1A(2), E2F2(1), TP53(14) 345627 18 12 17 3 4 0 9 2 3 0 0.22 0.00015 0.012
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(1), PIK3CA(3), PIK3R1(1), RB1(2), TP53(14) 838723 21 13 19 3 5 1 9 1 4 1 0.16 0.00025 0.017
10 G1PATHWAY CDK4/6-cyclin D and CDK2-cyclin E phosphorylate Rb, which allows the transcription of genes needed for the G1/S cell cycle transition. ABL1, ATM, ATR, CCNA1, CCND1, CCNE1, CDC2, CDC25A, CDK2, CDK4, CDK6, CDKN1A, CDKN1B, CDKN2A, CDKN2B, DHFR, E2F1, GSK3B, HDAC1, MADH3, MADH4, RB1, SKP2, TFDP1, TGFB1, TGFB2, TGFB3, TP53 25 ABL1(1), ATM(3), ATR(3), CCND1(1), CDK6(1), CDKN1A(2), RB1(2), TP53(14) 1250337 27 17 25 3 10 0 10 2 4 1 0.079 0.00028 0.017

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 PMLPATHWAY Ring-shaped PML nuclear bodies regulate transcription and are required co-activators in p53- and DAXX-mediated apoptosis. CREBBP, DAXX, HRAS, PAX3, PML, PRAM-1, RARA, RB1, SIRT1, SP100, TNF, TNFRSF1A, TNFRSF1B, TNFRSF6, TNFSF6, TP53, UBL1 12 CREBBP(5), DAXX(1), PML(3), RARA(2), RB1(2), SP100(1), TNFRSF1B(1) 758156 15 11 14 1 5 0 5 0 4 1 0.074 0.00051 0.18
2 FBW7PATHWAY Cyclin E interacts with cell cycle checkpoint kinase cdk2 to allow transcription of genes required for S phase, including transcription of additional cyclin E. CCNE1, CDC34, CDK2, CUL1, E2F1, FBXW7, RB1, SKP1A, TFDP1 7 CUL1(4), RB1(2) 274624 6 6 4 0 3 0 1 0 1 1 0.2 0.00059 0.18
3 IL7PATHWAY IL-7 is required for B and T cell development and proliferation and may contribute to activation of VDJ recombination. BCL2, CREBBP, EP300, FYN, IL2RG, IL7, IL7R, JAK1, JAK3, LCK, NMI, PIK3CA, PIK3R1, PTK2B, STAT5A, STAT5B 16 CREBBP(5), EP300(3), IL2RG(1), JAK1(1), LCK(1), PIK3CA(3), PIK3R1(1), STAT5B(1) 1162044 16 14 16 2 5 1 5 2 3 0 0.17 0.0016 0.18
4 PDGFPATHWAY Platelet-derived growth factor (PDGF) receptor is phosphorylated on ligand binding and promotes cell proliferation. CSNK2A1, ELK1, FOS, GRB2, HRAS, JAK1, JUN, MAP2K1, MAP2K4, MAP3K1, MAPK3, MAPK8, PDGFA, PDGFRA, PIK3CA, PIK3R1, PLCG1, PRKCA, PRKCB1, RAF1, RASA1, SHC1, SOS1, SRF, STAT1, STAT3, STAT5A 26 CSNK2A1(1), FOS(1), JAK1(1), MAP2K1(1), MAP3K1(2), MAPK8(2), PDGFRA(1), PIK3CA(3), PIK3R1(1), PLCG1(2), RASA1(1), SOS1(2), STAT1(1) 1449993 19 14 19 1 11 1 4 2 1 0 0.036 0.0022 0.18
5 SKP2E2FPATHWAY E2F-1, a transcription factor that promotes the G1/S transition, is repressed by Rb and activated by cdk2/cyclin E. CCNA1, CCNE1, CDC34, CDK2, CUL1, E2F1, RB1, SKP1A, SKP2, TFDP1 9 CUL1(4), RB1(2) 356034 6 6 4 1 3 0 1 0 1 1 0.48 0.0022 0.18
6 P27PATHWAY p27 blocks the G1/S transition by inhibiting the checkpoint kinase cdk2/cyclin E and is inhibited by cdk2-mediated ubiquitination. CCNE1, CDK2, CDKN1B, CKS1B, CUL1, E2F1, NEDD8, RB1, RBX1, SKP1A, SKP2, TFDP1, UBE2M 12 CUL1(4), RB1(2) 357550 6 6 4 0 3 0 1 0 1 1 0.2 0.0022 0.18
7 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(1), GZMB(1), HLA-A(3), ICAM1(1), PRF1(2) 363702 8 7 8 1 2 0 4 0 2 0 0.28 0.0024 0.18
8 D4GDIPATHWAY D4-GDI inhibits the pro-apoptotic Rho GTPases and is cleaved by caspase-3. ADPRT, APAF1, ARHGAP5, ARHGDIB, CASP1, CASP10, CASP3, CASP8, CASP9, CYCS, GZMB, JUN, PRF1 12 ARHGAP5(4), CASP8(2), GZMB(1), PRF1(2) 537688 9 8 9 1 1 0 5 3 0 0 0.33 0.0028 0.18
9 TPOPATHWAY Thrombopoietin binds to its receptor and activates cell growth through the Erk and JNK MAP kinase pathways, protein kinase C, and JAK/STAT activation. CSNK2A1, FOS, GRB2, HRAS, JAK2, JUN, MAP2K1, MAPK3, MPL, PIK3CA, PIK3R1, PLCG1, PRKCA, PRKCB1, RAF1, RASA1, SHC1, SOS1, STAT1, STAT3, STAT5A, STAT5B, THPO 22 CSNK2A1(1), FOS(1), JAK2(1), MAP2K1(1), MPL(1), PIK3CA(3), PIK3R1(1), PLCG1(2), RASA1(1), SOS1(2), STAT1(1), STAT5B(1) 1245136 16 14 16 0 10 1 4 1 0 0 0.016 0.003 0.18
10 HCMVPATHWAY Cytomegalovirus activates MAP kinase pathways in the host cell, inducing transcription of viral genes. AKT1, CREB1, MAP2K1, MAP2K2, MAP2K3, MAP2K6, MAP3K1, MAPK1, MAPK14, MAPK3, NFKB1, PIK3CA, PIK3R1, RB1, RELA, SP1 16 MAP2K1(1), MAP3K1(2), PIK3CA(3), PIK3R1(1), RB1(2), RELA(1) 805679 10 9 9 1 4 1 1 1 2 1 0.28 0.003 0.18
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)
Copyright © 2014 Broad Institute TCGA GDAC as part of the TCGA Research Network. All rights reserved.
Made with Nozzle