Mutation Analysis (MutSig v2.0)
Colon Adenocarcinoma (Primary solid tumor)
16 April 2014  |  analyses__2014_04_16
Maintainer Information
Citation Information
doi:10.7908/C1CF9NQN
Maintained by Dan DiCara (Broad Institute)
Cite as Broad Institute TCGA Genome Data Analysis Center (2014): Mutation Analysis (MutSig v2.0). Broad Institute of MIT and Harvard. doi:10.7908/C1CF9NQN
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: COAD-TP

  • Number of patients in set: 154

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:COAD-TP.final_analysis_set.maf

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

  • Significantly mutated genes (q ≤ 0.1): 32

  • Mutations seen in COSMIC: 516

  • Significantly mutated genes in COSMIC territory: 23

  • Significantly mutated genesets: 32

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

Mutation Preprocessing

  • Read 102 MAFs of type "Broad"

  • Read 52 MAFs of type "Baylor-SOLiD"

  • Total number of mutations in input MAFs: 62530

  • After removing 1112 invalidated mutations: 61418

  • After removing 976 noncoding mutations: 60442

  • After collapsing adjacent/redundant mutations: 60440

Mutation Filtering

  • Number of mutations before filtering: 60440

  • After removing 659 mutations outside gene set: 59781

  • After removing 171 mutations outside category set: 59610

  • After removing 10 "impossible" mutations in

  • gene-patient-category bins of zero coverage: 58770

Results
Breakdown of Mutations by Type

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

type count
De_novo_Start_InFrame 16
De_novo_Start_OutOfFrame 126
Frame_Shift_Del 1137
Frame_Shift_Ins 655
In_Frame_Del 139
In_Frame_Ins 19
Missense_Mutation 39581
Nonsense_Mutation 3275
Nonstop_Mutation 30
Silent 14482
Splice_Site 148
Translation_Start_Site 2
Total 59610
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 15449 234808561 0.000066 66 6.2 2.1
*Np(A/C/T)->transit 10138 3376820560 3e-06 3 0.28 2
*ApG->G 966 654324208 1.5e-06 1.5 0.14 2.1
transver 13023 4265953329 3.1e-06 3.1 0.29 5
indel+null 5397 4265953329 1.3e-06 1.3 0.12 NaN
double_null 147 4265953329 3.4e-08 0.034 0.0033 NaN
Total 45120 4265953329 0.000011 11 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: COAD-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: *Np(A/C/T)->transit

  • n3 = number of nonsilent mutations of type: *ApG->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: 32. 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 FBXW7 F-box and WD repeat domain containing 7 397592 33 29 21 2 17 1 0 8 7 0 5.66e-15 0.017 0.00026 0.087 0.00034 1.11e-16 2.00e-12
2 NRAS neuroblastoma RAS viral (v-ras) oncogene homolog 90244 15 15 7 0 2 2 0 11 0 0 9.21e-15 0.033 0.0014 0.024 0.00069 2.22e-16 2.00e-12
3 APC adenomatous polyposis coli 1306595 121 103 85 4 5 6 1 11 64 34 <1.00e-15 7.1e-07 0 0.68 0 <1.00e-15 <2.57e-12
4 TP53 tumor protein p53 187068 76 74 50 1 28 11 0 11 26 0 <1.00e-15 2.2e-07 0 2e-07 0 <1.00e-15 <2.57e-12
5 KRAS v-Ki-ras2 Kirsten rat sarcoma viral oncogene homolog 108699 58 58 8 0 0 31 0 27 0 0 <1.00e-15 1.9e-07 0 4.6e-06 0 <1.00e-15 <2.57e-12
6 PIK3CA phosphoinositide-3-kinase, catalytic, alpha polypeptide 423914 33 26 18 1 5 19 1 8 0 0 4.33e-15 0.00064 0.00059 2e-06 0 <1.00e-15 <2.57e-12
7 BRAF v-raf murine sarcoma viral oncogene homolog B1 340063 21 20 3 0 0 0 0 21 0 0 3.74e-12 0.02 0 0.000088 0 <1.00e-15 <2.57e-12
8 SMAD4 SMAD family member 4 260543 21 18 17 0 8 7 0 2 3 1 1.18e-14 0.0021 0.078 0.0061 0.0059 2.66e-15 5.99e-12
9 FAM123B family with sequence similarity 123B 449294 19 19 17 1 1 2 0 2 14 0 1.11e-12 0.14 0.035 0.63 0.1 3.46e-12 6.91e-09
10 ACVR1B activin A receptor, type IB 234306 13 13 13 0 4 6 0 2 1 0 3.98e-08 0.014 0.1 0.00095 0.0056 5.21e-09 9.38e-06
11 TNFRSF10C tumor necrosis factor receptor superfamily, member 10c, decoy without an intracellular domain 116139 6 6 2 0 0 0 0 6 0 0 8.29e-06 0.3 7e-06 1 0.000035 6.69e-09 1.10e-05
12 SMAD2 SMAD family member 2 222029 11 10 8 1 3 0 0 4 4 0 1.88e-07 0.23 0.031 0.07 0.025 9.49e-08 0.000142
13 MAP2K4 mitogen-activated protein kinase kinase 4 170049 9 9 8 0 2 3 1 2 1 0 2.33e-06 0.063 0.093 0.0013 0.0047 2.10e-07 0.000290
14 WBSCR17 Williams-Beuren syndrome chromosome region 17 276560 17 17 16 2 10 2 1 1 3 0 1.39e-07 0.033 0.047 0.56 0.088 2.35e-07 0.000302
15 PCBP1 poly(rC) binding protein 1 127377 4 4 2 0 0 0 2 2 0 0 0.00111 0.34 1e-05 0.035 0.000015 3.19e-07 0.000383
16 SOX9 SRY (sex determining region Y)-box 9 (campomelic dysplasia, autosomal sex-reversal) 180368 9 9 9 0 0 1 0 0 8 0 1.46e-06 0.26 0.11 0.58 0.21 5.00e-06 0.00562
17 GABRA5 gamma-aminobutyric acid (GABA) A receptor, alpha 5 125970 8 8 7 0 3 2 0 2 1 0 1.18e-05 0.044 0.032 0.48 0.05 9.09e-06 0.00962
18 OR2M4 olfactory receptor, family 2, subfamily M, member 4 144562 8 8 8 0 3 2 1 0 2 0 4.70e-06 0.095 0.5 0.034 0.14 9.86e-06 0.00986
19 ACVR2A activin A receptor, type IIA 243930 9 8 8 1 0 1 0 3 5 0 0.000220 0.58 0.014 0.031 0.0054 1.74e-05 0.0165
20 GGT1 gamma-glutamyltransferase 1 178862 3 3 1 1 0 3 0 0 0 0 0.194 0.54 0.000086 6.2e-06 7.4e-06 2.08e-05 0.0180
21 MGC26647 chromosome 7 open reading frame 62 117149 7 7 7 0 1 1 0 2 3 0 6.92e-06 0.21 0.12 0.8 0.21 2.10e-05 0.0180
22 FAM22F family with sequence similarity 22, member F 194820 8 8 4 1 1 0 0 6 1 0 2.73e-05 0.37 0.032 0.34 0.07 2.70e-05 0.0221
23 MGC42105 203184 10 10 10 1 5 1 0 2 2 0 5.24e-06 0.15 0.5 0.9 0.61 4.36e-05 0.0341
24 OTOL1 otolin 1 129846 7 7 6 0 3 1 0 2 1 0 4.01e-06 0.14 0.82 0.52 0.88 4.79e-05 0.0359
25 ACOT4 acyl-CoA thioesterase 4 151249 3 3 2 1 0 0 0 0 2 1 0.0146 1 0.00023 0.021 0.00026 5.22e-05 0.0375
26 ATM ataxia telangiectasia mutated 1439817 27 21 27 1 4 6 0 9 7 1 3.14e-05 0.019 0.31 0.079 0.13 5.65e-05 0.0391
27 TPTE transmembrane phosphatase with tensin homology 259074 14 11 13 1 5 2 2 4 1 0 9.71e-06 0.065 0.5 0.81 0.71 8.91e-05 0.0594
28 BTNL8 butyrophilin-like 8 90899 3 3 1 1 0 0 0 3 0 0 0.00878 0.82 0.00042 0.038 0.0013 0.000145 0.0888
29 TCF7L2 transcription factor 7-like 2 (T-cell specific, HMG-box) 280265 13 11 13 3 3 2 0 3 5 0 0.000116 0.29 0.054 0.46 0.1 0.000146 0.0888
30 TXNDC3 thioredoxin domain containing 3 (spermatozoa) 281221 13 10 13 2 3 1 1 3 5 0 1.72e-05 0.22 0.53 0.8 0.7 0.000148 0.0888
31 OR51V1 olfactory receptor, family 51, subfamily V, member 1 148296 11 9 11 1 2 2 0 5 2 0 1.29e-05 0.15 0.79 0.96 1 0.000158 0.0917
32 CNTN6 contactin 6 487581 19 15 19 2 5 3 0 10 1 0 1.80e-05 0.14 0.64 0.69 0.76 0.000168 0.0943
33 C8B complement component 8, beta polypeptide 280558 9 9 9 0 3 2 0 4 0 0 2.20e-05 0.079 0.92 0.68 0.86 0.000224 0.120
34 PSG8 pregnancy specific beta-1-glycoprotein 8 182562 8 8 6 0 5 2 0 0 1 0 2.23e-05 0.083 0.61 0.63 0.86 0.000227 0.120
35 ISL1 ISL LIM homeobox 1 146048 9 8 9 2 2 2 0 4 1 0 7.78e-05 0.38 0.16 0.77 0.26 0.000243 0.125
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: 23. Number of genes displayed: 10

rank gene description n cos n_cos N_cos cos_ev p q
1 KRAS v-Ki-ras2 Kirsten rat sarcoma viral oncogene homolog 58 52 58 8008 650714 0 0
2 NRAS neuroblastoma RAS viral (v-ras) oncogene homolog 15 33 13 5082 12243 0 0
3 FBXW7 F-box and WD repeat domain containing 7 33 91 25 14014 899 0 0
4 BRAF v-raf murine sarcoma viral oncogene homolog B1 21 89 19 13706 273106 0 0
5 PIK3CA phosphoinositide-3-kinase, catalytic, alpha polypeptide 33 220 30 33880 11874 0 0
6 APC adenomatous polyposis coli 121 839 87 129206 1536 0 0
7 TP53 tumor protein p53 76 824 76 126896 26644 0 0
8 SMAD4 SMAD family member 4 21 159 13 24486 51 0 0
9 ERBB3 v-erb-b2 erythroblastic leukemia viral oncogene homolog 3 (avian) 11 6 5 924 5 7.1e-13 3.6e-10
10 CDC27 cell division cycle 27 homolog (S. cerevisiae) 9 3 4 462 4 2.3e-11 1.1e-08

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: 32. 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 WNTPATHWAY The Wnt glycoprotein binds to membrane-bound receptors such as Frizzled to activate a number of signaling pathways, including that of beta-catenin. APC, AXIN1, BTRC, CCND1, CREBBP, CSNK1A1, CSNK1D, CSNK2A1, CTBP1, CTNNB1, DVL1, FRAT1, FZD1, GSK3B, HDAC1, MADH4, MAP3K7, MAP3K7IP1, MYC, NLK, PPARD, PPP2CA, TCF1, TLE1, WIF1, WNT1 22 APC(121), AXIN1(1), BTRC(2), CREBBP(21), CSNK1A1(2), CSNK1D(3), CSNK2A1(4), CTBP1(1), CTNNB1(8), GSK3B(7), HDAC1(2), MAP3K7(2), NLK(1), PPARD(1), PPP2CA(1), TLE1(1), WIF1(2), WNT1(1) 6339468 181 120 145 22 26 21 2 24 74 34 2.9e-07 <1.00e-15 <1.11e-13
2 PS1PATHWAY Presenilin is required for gamma-secretase activity to activate Notch signaling; presenilin also inhibits beta-catenin in the Wnt/Frizzled pathway. ADAM17, APC, AXIN1, BTRC, CTNNB1, DLL1, DVL1, FZD1, GSK3B, NOTCH1, PSEN1, RBPSUH, TCF1, WNT1 12 ADAM17(6), APC(121), AXIN1(1), BTRC(2), CTNNB1(8), DLL1(1), GSK3B(7), PSEN1(3), WNT1(1) 4597626 150 112 114 13 16 13 1 16 70 34 3e-09 <1.00e-15 <1.11e-13
3 ST_GRANULE_CELL_SURVIVAL_PATHWAY The survival and differentiation of granule cells in the brain is controlled by pro-growth PACAP and pro-apoptotic ceramides. ADPRT, APC, ASAH1, CAMP, CASP3, CERK, CREB1, CREB3, CREB5, CXCL2, DAG1, EPHB2, FOS, GNAQ, IL8RB, ITPKA, ITPKB, JUN, MAP2K4, MAP2K7, MAPK1, MAPK10, MAPK8, MAPK8IP1, MAPK8IP2, MAPK8IP3, MAPK9, PACAP 25 APC(121), ASAH1(3), CASP3(1), CERK(1), CREB1(1), CREB3(2), CREB5(2), DAG1(4), EPHB2(7), GNAQ(3), ITPKB(4), MAP2K4(9), MAPK1(2), MAPK10(4), MAPK8(2), MAPK8IP1(2), MAPK8IP3(1), MAPK9(3) 6337879 172 112 134 22 19 19 4 25 71 34 1.1e-06 <1.00e-15 <1.11e-13
4 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(27), ATR(13), CDC25C(3), CHEK1(1), CHEK2(1), TP53(76) 3665686 121 94 95 3 38 20 2 24 36 1 5.4e-09 <1.00e-15 <1.11e-13
5 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(121), CDH1(4), CREBBP(21), EP300(13), MAP2K1(3), MAP3K7(2), MAPK3(2), TGFB1(1), TGFB2(5), TGFBR1(6), TGFBR2(7) 5814805 185 118 148 21 29 26 4 18 74 34 1.3e-07 1.22e-15 1.11e-13
6 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(4), DNAJC3(1), EIF2S2(1), MAP3K14(2), NFKB1(3), RELA(2), TP53(76) 2157493 89 78 63 6 36 13 0 12 28 0 0.000018 1.22e-15 1.11e-13
7 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(1), SP1(2), SP3(2), TP53(76), WT1(4) 1573762 87 81 61 4 34 14 1 12 26 0 2.8e-08 1.33e-15 1.11e-13
8 ATMPATHWAY The tumor-suppressing protein kinase ATM responds to radiation-induced DNA damage by blocking cell-cycle progression and activating DNA repair. ABL1, ATM, BRCA1, CDKN1A, CHEK1, CHEK2, GADD45A, JUN, MAPK8, MDM2, MRE11A, NBS1, NFKB1, NFKBIA, RAD50, RAD51, RBBP8, RELA, TP53, TP73 19 ABL1(4), ATM(27), BRCA1(5), CDKN1A(1), CHEK1(1), CHEK2(1), MAPK8(2), MDM2(4), MRE11A(3), NFKB1(3), RAD50(5), RBBP8(2), RELA(2), TP53(76) 6728302 136 96 110 9 41 29 2 26 37 1 2.7e-08 1.44e-15 1.11e-13
9 PITX2PATHWAY The bicoid-related transcription factor Pitx2 is activated by Wnt binding to the Frizzled receptor and induces tissue-specific cell proliferation. APC, AXIN1, CREBBP, CTNNB1, DVL1, EP300, FZD1, GSK3B, HDAC1, HTATIP, LDB1, LEF1, PITX2, PPARBP, TRRAP, WNT1 14 APC(121), AXIN1(1), CREBBP(21), CTNNB1(8), EP300(13), GSK3B(7), HDAC1(2), LDB1(3), LEF1(4), PITX2(2), TRRAP(17), WNT1(1) 7283209 200 122 163 25 38 31 2 19 76 34 1.6e-08 2.66e-15 1.82e-13
10 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 CDK2(2), CDK4(2), CDKN1A(1), CDKN1B(1), CDKN2A(1), CFL1(1), E2F2(1), MDM2(4), NXT1(1), TP53(76) 1731869 90 79 64 5 30 15 0 18 27 0 5e-07 3.22e-15 1.98e-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 EOSINOPHILSPATHWAY Recruitment of eosinophils in the inflammatory response observed in asthma occurs via the chemoattractant eotaxin binding to the CCR3 receptor. CCL11, CCL5, CCR3, CSF2, HLA-DRA, HLA-DRB1, IL3, IL5 8 CCR3(3), HLA-DRA(4), HLA-DRB1(1), IL3(3) 658061 11 11 10 2 5 1 0 3 0 2 0.4 0.015 1
2 SA_FAS_SIGNALING The TNF-type receptor Fas induces apoptosis on ligand binding. BCL2, CASP3, CASP8, CFL1, CFLAR, P11, PDE6D, TNFRSF6, TNFSF6 6 BCL2(1), CASP3(1), CASP8(11), CFL1(1), CFLAR(2), PDE6D(1) 860111 17 16 16 2 3 3 1 6 4 0 0.14 0.015 1
3 HSA00830_RETINOL_METABOLISM Genes involved in retinol metabolism ALDH1A1, ALDH1A2, BCMO1, RDH5 4 ALDH1A1(3), ALDH1A2(6), BCMO1(4), RDH5(1) 869168 14 12 14 1 6 2 1 4 1 0 0.055 0.042 1
4 INOSITOL_METABOLISM ALDH6A1, ALDOA, ALDOB, ALDOC, TPI1 5 ALDH6A1(3), ALDOA(1), ALDOB(5), ALDOC(1), TPI1(1) 843025 11 11 11 1 2 0 0 9 0 0 0.26 0.082 1
5 HSA00902_MONOTERPENOID_BIOSYNTHESIS Genes involved in monoterpenoid biosynthesis CYP2C19, CYP2C9 2 CYP2C19(4), CYP2C9(4) 457981 8 8 8 2 2 1 0 4 1 0 0.71 0.24 1
6 SLRPPATHWAY Small leucine-rich proteoglycans (SLRPs) interact with and reorganize collagen fibers in the extracellular matrix. BGN, DCN, DSPG3, FMOD, KERA, LUM 5 DCN(3), FMOD(2), KERA(5), LUM(5) 802145 15 13 15 3 4 6 0 3 2 0 0.24 0.29 1
7 BLOOD_GROUP_GLYCOLIPID_BIOSYNTHESIS_NEOLACTOSERIES ABO, B3GNT1, FUT1, FUT2, FUT9, GCNT2, ST8SIA1 7 ABO(2), B3GNT1(2), FUT1(1), FUT2(1), FUT9(4), GCNT2(9), ST8SIA1(3) 1344754 22 15 22 4 6 6 1 6 3 0 0.085 0.31 1
8 HSA00472_D_ARGININE_AND_D_ORNITHINE_METABOLISM Genes involved in D-arginine and D-ornithine metabolism DAO 1 DAO(2) 165887 2 2 2 0 1 0 0 0 1 0 0.59 0.31 1
9 HSA00031_INOSITOL_METABOLISM Genes involved in inositol metabolism ALDH6A1, TPI1 2 ALDH6A1(3), TPI1(1) 350147 4 4 4 0 0 0 0 4 0 0 0.45 0.32 1
10 1_AND_2_METHYLNAPHTHALENE_DEGRADATION ADH1A, ADH1A, ADH1B, ADH1C, ADH1B, ADH1C, ADH4, ADH6, ADH7, ADHFE1 7 ADH1B(2), ADH1C(3), ADH4(1), ADH6(5), ADH7(2), ADHFE1(6) 1222107 19 16 19 5 3 4 1 11 0 0 0.36 0.36 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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