Cervical Squamous Cell Carcinoma: Mutation Analysis (MutSig)
Maintained by Dan DiCara (Broad Institute)
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: CESC

  • Number of patients in set: 36

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:CESC.final_analysis_set.maf

  • Significantly mutated genes (q ≤ 0.1): 3

  • Mutations seen in COSMIC: 31

  • Significantly mutated genes in COSMIC territory: 1

  • Genes with clustered mutations (≤ 3 aa apart): 0

  • Significantly mutated genesets: 7

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

Mutation Preprocessing

  • Read 36 MAFs of type "Broad"

  • Total number of mutations in input MAFs: 9967

  • After removing 2681 noncoding mutations: 7286

  • After collapsing adjacent/redundant mutations: 7271

Mutation Filtering

  • Number of mutations before filtering: 7271

  • After removing 41 mutations outside gene set: 7230

  • After removing 9 mutations outside category set: 7221

Results
Breakdown of Mutations by Type

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

type count
Frame_Shift_Del 19
Frame_Shift_Ins 17
In_Frame_Del 9
In_Frame_Ins 1
Missense_Mutation 4748
Nonsense_Mutation 449
Nonstop_Mutation 11
Silent 1883
Splice_Site 84
Total 7221
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) 3265 138808933 0.000024 24 4.6 3
Tp*C->A 172 138808933 1.2e-06 1.2 0.24 4
(A/C/G)p*C->mut 1022 391812501 2.6e-06 2.6 0.51 3.2
A->mut 287 513858559 5.6e-07 0.56 0.11 3.9
indel+null 583 1044479993 5.6e-07 0.56 0.11 NaN
double_null 9 1044479993 8.6e-09 0.0086 0.0017 NaN
Total 5338 1044479993 5.1e-06 5.1 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).

Figure 1. 

Distribution of Mutation Counts, Coverage, and Mutation Rates Across Samples

Figure 2.  Patients counts and rates file used to generate this plot: CESC.patients.counts_and_rates.txt

CoMut Plot

Figure 3.  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

  • 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_ks = p-value for clustering of mutations (Kolmogorov-Smirnoff test)

  • 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: 3. 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_ks p_cons p_joint p q
1 PIK3CA phosphoinositide-3-kinase, catalytic, alpha polypeptide 118073 11 9 4 0 10 0 0 1 0 0 1.1e-08 0.12 5.2e-06 0.0087 0 <1.00e-15 <1.79e-11
2 MAPK1 mitogen-activated protein kinase 1 35708 3 3 1 0 3 0 0 0 0 0 0.00069 0.41 8e-05 0.15 8e-05 9.76e-07 0.0088
3 NFYB nuclear transcription factor Y, beta 23472 2 2 1 0 0 0 0 0 2 0 0.00052 0.55 0.032 0.0016 0.0048 0.000034 0.16
4 FAM49A family with sequence similarity 49, member A 36191 2 2 2 0 0 0 1 1 0 0 0.0015 0.64 0.0018 0.51 0.0018 0.000036 0.16
5 NFE2L2 nuclear factor (erythroid-derived 2)-like 2 64404 6 5 5 0 4 0 0 1 1 0 0.000017 0.34 0.78 0.052 0.27 0.000060 0.21
6 CPNE3 copine III 59970 3 2 3 0 2 0 0 0 1 0 0.03 0.51 0.00033 0.97 0.00033 0.00012 0.36
7 TADA2A 50258 2 2 2 1 1 0 0 1 0 0 0.0072 0.88 0.0019 0.086 0.0019 0.00017 0.36
8 FCRL1 Fc receptor-like 1 47973 3 3 3 0 1 0 0 2 0 0 0.0002 0.45 0.029 0.65 0.069 0.00017 0.36
9 PTEN phosphatase and tensin homolog (mutated in multiple advanced cancers 1) 43485 3 3 3 0 0 0 0 0 3 0 0.000041 0.62 0.27 0.8 0.37 0.00018 0.36
10 ALS2 amyotrophic lateral sclerosis 2 (juvenile) 181332 2 1 2 0 0 0 0 1 1 0 0.23 0.64 0.00057 0.071 0.000082 0.00022 0.36
11 POU4F1 POU class 4 homeobox 1 20132 3 3 2 0 1 0 0 0 2 0 4e-05 0.66 0.36 0.54 0.47 0.00022 0.36
12 GPR153 G protein-coupled receptor 153 37643 2 2 2 0 0 0 1 1 0 0 0.0015 0.61 0.13 0.03 0.015 0.00026 0.39
13 TIE1 tyrosine kinase with immunoglobulin-like and EGF-like domains 1 115718 4 3 4 0 0 1 2 0 1 0 0.0018 0.27 0.051 0.022 0.018 0.00036 0.44
14 AQP2 aquaporin 2 (collecting duct) 27218 3 3 3 0 1 0 1 1 0 0 0.000063 0.34 0.44 0.11 0.5 0.00036 0.44
15 C2CD3 C2 calcium-dependent domain containing 3 215830 2 2 2 0 1 0 1 0 0 0 0.24 0.61 0.00014 0.33 0.00014 0.00037 0.44
16 LRP1 low density lipoprotein-related protein 1 (alpha-2-macroglobulin receptor) 489294 2 2 2 2 1 0 1 0 0 0 1 0.96 0.01 0.00016 0.000054 0.00058 0.63
17 DNAJB1 DnaJ (Hsp40) homolog, subfamily B, member 1 36199 5 3 5 0 3 1 0 0 1 0 0.00018 0.22 0.45 0.14 0.33 0.00064 0.63
18 ZNF645 zinc finger protein 645 46152 2 2 1 0 0 0 2 0 0 0 0.0031 0.69 0.003 0.061 0.019 0.00064 0.63
19 GGH gamma-glutamyl hydrolase (conjugase, folylpolygammaglutamyl hydrolase) 32271 2 2 2 0 1 0 1 0 0 0 0.0042 0.67 0.2 0.042 0.016 0.00073 0.63
20 SVIP 7089 1 1 1 0 0 0 0 0 1 0 0.00079 0.96 NaN NaN NaN 0.00079 0.63
21 TMEM51 transmembrane protein 51 27562 3 3 3 0 1 0 1 1 0 0 0.0002 0.42 0.27 0.83 0.39 0.00082 0.63
22 HOXA4 homeobox A4 15624 2 2 2 1 2 0 0 0 0 0 0.0011 0.8 0.071 0.083 0.071 0.00084 0.63
23 DALRD3 DALR anticodon binding domain containing 3 43562 4 2 4 1 2 1 1 0 0 0 0.00078 0.51 0.038 0.6 0.1 0.00085 0.63
24 FETUB fetuin B 42308 2 2 2 0 1 0 0 1 0 0 0.0073 0.6 0.083 0.024 0.012 0.00088 0.63
25 USP26 ubiquitin specific peptidase 26 98820 2 2 2 0 1 0 0 0 1 0 0.02 0.69 0.034 0.0052 0.0042 0.00089 0.63
26 BAI1 brain-specific angiogenesis inhibitor 1 80396 3 3 3 0 1 0 2 0 0 0 0.0008 0.32 0.038 0.63 0.11 0.00092 0.63
27 RYR2 ryanodine receptor 2 (cardiac) 480994 8 7 8 1 4 0 2 1 1 0 0.0016 0.35 0.038 0.47 0.06 0.00100 0.65
28 KPNA2 karyopherin alpha 2 (RAG cohort 1, importin alpha 1) 58680 3 3 3 1 2 1 0 0 0 0 0.00061 0.81 0.17 0.28 0.16 0.0010 0.65
29 OR5H6 olfactory receptor, family 5, subfamily H, member 6 35322 3 3 3 0 1 0 0 1 1 0 0.00011 0.39 0.78 0.64 0.98 0.0010 0.65
30 SNTG2 syntrophin, gamma 2 41640 2 2 2 0 2 0 0 0 0 0 0.0026 0.51 0.013 0.65 0.05 0.0013 0.79
31 HRCT1 10323 1 1 1 0 0 0 0 1 0 0 0.0014 0.76 NaN NaN NaN 0.0014 0.82
32 NTNG2 netrin G2 46701 3 3 3 0 2 0 1 0 0 0 0.0011 0.34 0.16 0.15 0.14 0.0015 0.82
33 VWA3A von Willebrand factor A domain containing 3A 91313 3 3 3 1 1 0 0 1 1 0 0.0016 0.75 0.058 0.79 0.099 0.0015 0.82
34 NCKAP1 NCK-associated protein 1 123812 4 4 4 0 1 0 1 0 2 0 0.00071 0.48 0.24 0.71 0.24 0.0017 0.87
35 ARID1A AT rich interactive domain 1A (SWI-like) 208460 5 4 5 0 1 0 1 0 2 1 0.00077 0.3 0.6 0.13 0.26 0.0019 0.99
PIK3CA

Figure S1.  This figure depicts the distribution of mutations and mutation types across the PIK3CA 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: 1. Number of genes displayed: 10

rank gene description n cos n_cos N_cos cos_ev p q
1 PIK3CA phosphoinositide-3-kinase, catalytic, alpha polypeptide 11 184 8 6624 3939 1.9e-13 8.7e-10
2 ATL2 1 1 1 36 1 0.00018 0.14
3 KIAA1024 KIAA1024 2 1 1 36 1 0.00018 0.14
4 LRRC8E leucine rich repeat containing 8 family, member E 1 1 1 36 1 0.00018 0.14
5 MAPK11 mitogen-activated protein kinase 11 1 1 1 36 1 0.00018 0.14
6 SUV39H2 suppressor of variegation 3-9 homolog 2 (Drosophila) 1 1 1 36 2 0.00018 0.14
7 PTEN phosphatase and tensin homolog (mutated in multiple advanced cancers 1) 3 728 3 26208 23 0.00036 0.19
8 CHEK2 CHK2 checkpoint homolog (S. pombe) 1 2 1 72 1 0.00037 0.19
9 ALS2 amyotrophic lateral sclerosis 2 (juvenile) 2 3 1 108 1 0.00055 0.19
10 EPHA10 EPH receptor A10 1 3 1 108 1 0.00055 0.19

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)

Clustered Mutations

There were no clustered mutations discovered.

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: 7. 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 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 ADCY1(1), ARHGEF1(1), F2R(1), F2RL3(2), GNA13(1), PIK3CA(11), PIK3R1(1), PPP1R12B(1), PRKCA(1), ROCK1(3) 1369418 23 13 16 1 16 0 4 2 0 1 0.012 0.00017 0.043
2 GCRPATHWAY Corticosteroids activate the glucocorticoid receptor (GR), which inhibits NF-kB and activates Annexin-1, thus inhibiting the inflammatory response. ADRB2, AKT1, ANXA1, CALM1, CALM2, CALM3, CRN, GNAS, GNB1, GNGT1, HSPCA, NFKB1, NOS3, NPPA, NR3C1, PIK3CA, PIK3R1, RELA, SYT1 17 CALM1(1), CALM3(1), NPPA(1), PIK3CA(11), PIK3R1(1), SYT1(1) 943298 16 11 9 0 12 1 1 2 0 0 0.019 0.00021 0.043
3 ACHPATHWAY Nicotinic acetylcholine receptors are ligand-gated ion channels that primarily mediate neuromuscular signaling and may inhibit neuronal apoptosis via the AKT pathway. AKT1, BAD, CHRNB1, CHRNG, FOXO3A, MUSK, PIK3CA, PIK3R1, PTK2, PTK2B, RAPSN, SRC, TERT, TNFSF6, YWHAH 13 CHRNG(1), MUSK(1), PIK3CA(11), PIK3R1(1), PTK2(1) 864474 15 11 8 1 11 0 1 2 1 0 0.051 0.00021 0.043
4 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 MAPK1(3), PIK3CA(11), PIK3R1(1), PTEN(3), PTK2(1), SOS1(1) 1023962 20 11 11 0 15 0 0 2 3 0 0.0084 0.00036 0.056
5 CTLA4PATHWAY T cell activation requires interaction with an antigen-MHC-I complex on an antigen-presenting cell (APC), as well as CD28 interaction with the APC's CD80 or 86. CD28, CD3D, CD3E, CD3G, CD3Z, CD80, CD86, CTLA4, GRB2, HLA-DRA, HLA-DRB1, ICOS, ICOSL, IL2, ITK, LCK, PIK3CA, PIK3R1, PTPN11, TRA@, TRB@ 17 CD86(1), ITK(1), PIK3CA(11), PIK3R1(1) 686462 14 9 7 0 12 0 0 2 0 0 0.025 0.00093 0.097
6 ERK5PATHWAY Signaling between a tissue and its innervating axon stimulates retrograde transport via Trk receptors, which activate Erk5, which induces transcription of anti-apoptotic factors. AKT1, CREB1, GRB2, HRAS, MAPK1, MAPK3, MAPK7, MEF2A, MEF2B, MEF2C, MEF2D, NTRK1, PIK3CA, PIK3R1, PLCG1, RPS6KA1, SHC1 17 MAPK1(3), MAPK7(1), MEF2C(1), PIK3CA(11), PIK3R1(1), RPS6KA1(1) 1008219 18 10 9 1 14 0 1 3 0 0 0.031 0.00097 0.097
7 PLCPATHWAY Phospholipase C hydrolyzes the membrane lipid PIP2 to DAG, which activates protein kinase C, and IP3, which causes calcium influx. AKT1, PIK3CA, PIK3R1, PLCB1, PLCG1, PRKCA, PRKCB1, VAV1 7 PIK3CA(11), PIK3R1(1), PRKCA(1) 686172 13 9 6 1 11 0 0 2 0 0 0.13 0.0011 0.097
8 ARENRF2PATHWAY Nrf1 and nrf2 are transcription factors that bind to antioxidant response elements (AREs), promoters of genes involved in oxidative damage control. CREB1, FOS, FXYD2, JUN, KEAP1, MAFF, MAFG, MAFK, MAPK1, MAPK14, MAPK8, NFE2L2, PRKCA, PRKCB1 12 MAPK1(3), NFE2L2(6), PRKCA(1) 460362 10 8 7 0 8 0 0 1 1 0 0.07 0.0028 0.2
9 GSK3PATHWAY Bacterial lipopolysaccharide activates AKT to promote the survival and activation of macrophages and inhibits Gsk3-beta to promote beta-catenin accumulation in the nucleus. AKT1, APC, AXIN1, CCND1, CD14, CTNNB1, DVL1, FZD1, GJA1, GNAI1, GSK3B, IRAK1, LBP, LEF1, LY96, MYD88, NFKB1, PDPK1, PIK3CA, PIK3R1, PPP2CA, PRKR, RELA, TIRAP, TLR4, TOLLIP, WNT1 26 APC(3), CTNNB1(1), FZD1(1), GJA1(1), IRAK1(1), LY96(1), PIK3CA(11), PIK3R1(1) 1634345 20 13 13 1 16 1 0 2 1 0 0.039 0.0029 0.2
10 TRKAPATHWAY Nerve growth factor (NGF) promotes neuronal survival and proliferation by binding its receptor TrkA, which activates PI3K/AKT, Ras, and the MAP kinase pathway. AKT1, DPM2, GRB2, HRAS, KLK2, NGFB, NTRK1, PIK3CA, PIK3R1, PLCG1, PRKCA, PRKCB1, SHC1, SOS1 12 PIK3CA(11), PIK3R1(1), PRKCA(1), SOS1(1) 833454 14 9 7 1 12 0 0 2 0 0 0.099 0.0032 0.2

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 FIBRINOLYSISPATHWAY Thrombin cleavage of fibrinogen results in rapid formation of fibrin threads that form a mesh to capture platelets and other blood cells into a clot. CPB2, F13A1, F2, F2R, FGA, FGB, FGG, PLAT, PLAU, PLG, SERPINB2, SERPINE1 12 CPB2(2), F2R(1), FGA(1), PLAT(1), PLAU(1), PLG(1) 716620 7 7 7 1 2 1 2 2 0 0 0.44 0.0038 1
2 ST_TYPE_I_INTERFERON_PATHWAY Type I interferon is an antiviral cytokine that induces a JAK-STAT type pathway leading to ISGF3 activation and a cellular antiviral response. IFNAR1, IFNB1, ISGF3G, JAK1, PTPRU, REG1A, STAT1, STAT2, TYK2 8 IFNAR1(2), REG1A(1), STAT1(2), TYK2(3) 668217 8 8 8 1 6 0 2 0 0 0 0.22 0.0056 1
3 IFNGPATHWAY IFN gamma signaling pathway IFNG, IFNGR1, IFNGR2, JAK1, JAK2, STAT1 6 IFNGR1(2), IFNGR2(1), JAK2(1), STAT1(2) 441063 6 6 6 1 3 0 1 0 2 0 0.58 0.0077 1
4 IFNAPATHWAY Interferon alpha, active in the immune response, binds to the IFN receptor and activates Jak1 and Tyk2, which phosphorylate Stat1 and Stat2. IFNA1, IFNAR1, IFNAR2, IFNB1, ISGF3G, JAK1, STAT1, STAT2, TYK2 8 IFNA1(1), IFNAR1(2), IFNAR2(1), STAT1(2), TYK2(3) 580812 9 8 9 1 8 0 1 0 0 0 0.19 0.0087 1
5 PEPIPATHWAY Proepithelin (PEPI) induces epithelial cells to secrete IL-8, which promotes elastase secretion by neutrophils. ELA1, ELA2, ELA2A, ELA2B, ELA3B, GRN, IL8, SLPI 3 GRN(1), IL8(1) 91703 2 2 2 0 0 1 1 0 0 0 0.63 0.015 1
6 MSPPATHWAY Macrophage stimulating protein is synthesized as pro-MSP by the liver and, on proteolysis, binds to monocyte receptor kinase RON to induce macrophage development. CCL2, CSF1, IL1B, MST1, MST1R, TNF 6 MST1(1), MST1R(3) 347109 4 4 4 0 2 0 2 0 0 0 0.27 0.018 1
7 NOTCHPATHWAY Proteolysis and Signaling Pathway of Notch ADAM17, DLL1, FURIN, NOTCH1, PSEN1, RBPSUH 5 ADAM17(1), DLL1(1), NOTCH1(7), PSEN1(2) 483236 11 8 11 3 5 1 2 1 2 0 0.64 0.02 1
8 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 18 ADCY1(1), ARHGEF1(1), F2R(1), F2RL3(2), GNA13(1), PIK3R1(1), PPP1R12B(1), PRKCA(1), ROCK1(3) 1251345 12 9 12 1 6 0 4 1 0 1 0.13 0.021 1
9 TGFBPATHWAY The TGF-beta receptor responds to ligand binding by activating the SMAD family of transcriptional regulations, commonly blocking cell growth. APC, CDH1, CREBBP, EP300, MADH2, MADH3, MADH4, MADH7, MADHIP, MAP2K1, MAP3K7, MAP3K7IP1, MAPK3, SKIL, TGFB1, TGFB2, TGFB3, TGFBR1, TGFBR2 13 APC(3), CREBBP(4), EP300(2), SKIL(1), TGFB3(2) 1372116 12 10 12 1 8 0 2 0 2 0 0.22 0.021 1
10 HSA00130_UBIQUINONE_BIOSYNTHESIS Genes involved in ubiquinone biosynthesis COQ2, COQ3, COQ5, COQ6, COQ7, ND1, ND2, ND3, ND4, ND4L, ND5, ND6, NDUFA12, NDUFA13, NDUFB11 8 COQ3(1), COQ5(1), COQ6(1) 215602 3 3 3 0 2 0 1 0 0 0 0.46 0.022 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

This is an experimental feature. The full results of the analysis summarized in this report can be downloaded from the TCGA Data Coordination Center.

References
[1] TCGA, Integrated genomic analyses of ovarian carcinoma, Nature 474:609 - 615 (2011)
Copyright © 2012 Broad Institute TCGA GDAC as part of the TCGA Research Network. All rights reserved.
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