Mutation Analysis (MutSig v1.5)
Lung Adenocarcinoma (Primary solid tumor)
15 July 2014  |  analyses__2014_07_15
Maintainer Information
Citation Information
doi:10.7908/C14M9396
Maintained by David Heiman (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/C14M9396
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: LUAD-TP

  • Number of patients in set: 229

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:LUAD-TP.final_analysis_set.maf

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

  • Significantly mutated genes (q ≤ 0.1): 216

  • Mutations seen in COSMIC: 515

  • Significantly mutated genes in COSMIC territory: 24

  • Significantly mutated genesets: 16

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

Mutation Preprocessing

  • Read 229 MAFs of type "Broad"

  • Total number of mutations in input MAFs: 251233

  • After removing 79 mutations outside chr1-24: 251154

  • After removing 1775 blacklisted mutations: 249379

  • After removing 144370 noncoding mutations: 105009

  • After collapsing adjacent/redundant mutations: 93596

Mutation Filtering

  • Number of mutations before filtering: 93596

  • After removing 1282 mutations outside gene set: 92314

  • After removing 181 mutations outside category set: 92133

Results
Breakdown of Mutations by Type

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

type count
Frame_Shift_Del 1482
Frame_Shift_Ins 469
In_Frame_Del 154
In_Frame_Ins 20
Missense_Mutation 60363
Nonsense_Mutation 4801
Nonstop_Mutation 56
Silent 22794
Splice_Site 1860
Translation_Start_Site 134
Total 92133
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->A 8867 379287204 0.000023 23 2.3 2.1
*Cp(A/C/T)->A 22038 3108508517 7.1e-06 7.1 0.7 5
C->(T/G) 18886 3487795721 5.4e-06 5.4 0.53 2.8
A->mut 10703 3354933814 3.2e-06 3.2 0.31 3.9
indel+null 8698 6842729535 1.3e-06 1.3 0.13 NaN
double_null 147 6842729535 2.1e-08 0.021 0.0021 NaN
Total 69339 6842729535 1e-05 10 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: LUAD-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->A

  • n2 = number of nonsilent mutations of type: *Cp(A/C/T)->A

  • n3 = number of nonsilent mutations of type: C->(T/G)

  • 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: 216. 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 KRAS v-Ki-ras2 Kirsten rat sarcoma viral oncogene homolog 161903 60 60 6 0 0 47 10 3 0 0 0.002 <1.00e-15 <1.81e-11
2 TP53 tumor protein p53 288082 128 119 106 2 8 22 31 18 49 0 1.2e-10 3.11e-15 2.81e-11
3 STK11 serine/threonine kinase 11 199230 21 20 20 0 0 4 2 4 11 0 0.01 4.88e-15 2.95e-11
4 KEAP1 kelch-like ECH-associated protein 1 418841 39 39 37 0 4 8 13 10 4 0 0.000026 8.10e-15 3.67e-11
5 NAV3 neuron navigator 3 1659792 66 51 66 4 4 36 16 6 3 1 0.0026 4.27e-13 1.54e-09
6 MAGEC1 melanoma antigen family C, 1 774020 39 33 38 2 2 14 13 7 3 0 0.0051 8.12e-13 2.45e-09
7 CDH10 cadherin 10, type 2 (T2-cadherin) 552119 52 41 52 8 4 27 12 1 8 0 0.27 2.53e-12 6.55e-09
8 TMTC1 transmembrane and tetratricopeptide repeat containing 1 543417 32 26 30 3 3 17 7 3 2 0 0.055 4.23e-11 9.57e-08
9 ZNF676 zinc finger protein 676 407391 21 20 20 1 0 9 9 0 3 0 0.12 1.01e-10 2.02e-07
10 ELTD1 EGF, latrophilin and seven transmembrane domain containing 1 482503 20 20 20 0 0 4 4 8 4 0 0.015 1.19e-09 2.15e-06
11 OR4C16 olfactory receptor, family 4, subfamily C, member 16 214115 16 15 15 0 0 9 2 3 2 0 0.035 1.55e-09 2.45e-06
12 OR2L3 olfactory receptor, family 2, subfamily L, member 3 215947 16 15 16 2 1 9 2 4 0 0 0.19 1.62e-09 2.45e-06
13 MUC7 mucin 7, secreted 261518 18 16 18 1 0 8 3 4 3 0 0.13 2.01e-09 2.79e-06
14 RIMS2 regulating synaptic membrane exocytosis 2 994318 45 39 45 4 4 16 10 8 7 0 0.051 2.97e-09 3.84e-06
15 REG3A regenerating islet-derived 3 alpha 125492 15 14 14 2 0 4 7 2 2 0 0.25 3.87e-09 4.67e-06
16 CDKN2A cyclin-dependent kinase inhibitor 2A (melanoma, p16, inhibits CDK4) 226023 14 14 14 1 0 1 4 4 5 0 0.26 4.76e-09 5.39e-06
17 EPHA6 EPH receptor A6 755242 33 30 33 4 3 17 7 3 3 0 0.17 6.58e-09 7.00e-06
18 CNBD1 cyclic nucleotide binding domain containing 1 238160 14 14 14 1 0 5 3 4 2 0 0.32 7.40e-09 7.44e-06
19 OR2T4 olfactory receptor, family 2, subfamily T, member 4 240679 18 17 18 2 1 7 8 2 0 0 0.071 9.26e-09 8.82e-06
20 REG1B regenerating islet-derived 1 beta (pancreatic stone protein, pancreatic thread protein) 119309 15 14 15 2 1 7 1 3 3 0 0.39 1.11e-08 9.91e-06
21 CD5L CD5 molecule-like 244572 15 15 15 1 3 3 0 5 4 0 0.1 1.15e-08 9.91e-06
22 GABRB3 gamma-aminobutyric acid (GABA) A receptor, beta 3 314646 18 17 18 1 3 6 4 4 1 0 0.038 1.49e-08 1.23e-05
23 OR4A5 olfactory receptor, family 4, subfamily A, member 5 218008 13 12 13 0 1 4 3 4 1 0 0.035 3.31e-08 2.60e-05
24 TRIM58 tripartite motif-containing 58 254648 15 15 15 2 1 3 3 5 3 0 0.19 4.25e-08 3.20e-05
25 ZNF804A zinc finger protein 804A 834934 44 38 44 5 0 26 8 4 6 0 0.31 1.59e-07 0.000115
26 C18orf34 chromosome 18 open reading frame 34 606392 23 21 23 2 0 11 4 6 2 0 0.27 2.43e-07 0.000169
27 SERPINB4 serpin peptidase inhibitor, clade B (ovalbumin), member 4 275029 15 15 15 2 0 4 4 5 2 0 0.37 2.54e-07 0.000170
28 OR2L8 olfactory receptor, family 2, subfamily L, member 8 215947 15 13 13 2 1 8 3 2 1 0 0.23 2.86e-07 0.000185
29 BAGE2 B melanoma antigen family, member 2 79234 8 8 8 0 0 4 2 1 1 0 0.16 3.52e-07 0.000219
30 TBX22 T-box 22 353118 16 16 16 1 2 9 2 2 1 0 0.15 4.41e-07 0.000266
31 BRAF v-raf murine sarcoma viral oncogene homolog B1 510899 17 17 12 1 1 7 2 5 2 0 0.096 5.27e-07 0.000308
32 OR5W2 olfactory receptor, family 5, subfamily W, member 2 214115 12 11 12 1 0 3 6 2 1 0 0.13 8.17e-07 0.000462
33 OR8H2 olfactory receptor, family 8, subfamily H, member 2 215489 17 15 17 3 0 9 5 1 2 0 0.24 1.03e-06 0.000562
34 OR5D14 olfactory receptor, family 5, subfamily D, member 14 217092 20 19 19 3 0 9 5 5 1 0 0.17 1.40e-06 0.000746
35 OR5I1 olfactory receptor, family 5, subfamily I, member 1 217092 16 16 15 3 1 3 8 3 1 0 0.25 1.70e-06 0.000876
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: 24. 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 60 52 60 11908 797017 0 0
2 LRP1B low density lipoprotein-related protein 1B (deleted in tumors) 147 18 8 4122 8 0 0
3 TP53 tumor protein p53 128 356 122 81524 18207 0 0
4 BRAF v-raf murine sarcoma viral oncogene homolog B1 17 89 12 20381 28944 0 0
5 STK11 serine/threonine kinase 11 21 130 14 29770 27 0 0
6 EGFR epidermal growth factor receptor (erythroblastic leukemia viral (v-erb-b) oncogene homolog, avian) 33 293 29 67097 10294 0 0
7 CDKN2A cyclin-dependent kinase inhibitor 2A (melanoma, p16, inhibits CDK4) 14 332 14 76028 259 0 0
8 MET met proto-oncogene (hepatocyte growth factor receptor) 12 34 6 7786 64 3.1e-10 1.8e-07
9 PIK3CA phosphoinositide-3-kinase, catalytic, alpha polypeptide 11 220 9 50380 3946 4.1e-09 2.1e-06
10 NF1 neurofibromin 1 (neurofibromatosis, von Recklinghausen disease, Watson disease) 30 285 9 65265 13 3.7e-08 0.000017

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: 16. 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 P53PATHWAY p53 induces cell cycle arrest or apoptosis under conditions of DNA damage. APAF1, ATM, BAX, BCL2, CCND1, CCNE1, CDK2, CDK4, CDKN1A, E2F1, GADD45A, MDM2, PCNA, RB1, TIMP3, TP53 16 APAF1(8), ATM(22), BAX(1), BCL2(1), CCND1(2), CCNE1(3), CDK2(4), CDK4(2), CDKN1A(1), E2F1(3), GADD45A(1), MDM2(2), PCNA(1), RB1(13), TP53(128) 6266585 192 143 169 16 16 37 42 29 68 0 1.9e-06 <1.00e-15 <1.54e-13
2 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 19 ABCB1(20), ATM(22), BAX(1), CDKN1A(1), CPB2(4), CSNK1A1(1), CSNK1D(2), GADD45A(1), HIF1A(1), IGFBP3(2), MAPK8(3), MDM2(2), NQO1(3), TP53(128) 7172280 191 138 167 18 17 40 45 27 62 0 0.000012 <1.00e-15 <1.54e-13
3 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 IFNG(4), IFNGR1(3), IFNGR2(3), IKBKB(3), JAK2(4), LIN7A(2), NFKB1(3), NFKBIA(1), RB1(13), TNFRSF1B(1), TP53(128), USH1C(4), WT1(8) 6332308 177 133 155 16 15 35 41 21 65 0 1.8e-06 <1.00e-15 <1.54e-13
4 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 ARF3(1), CCND1(2), CDK2(4), CDK4(2), CDKN1A(1), CDKN1B(3), CDKN2A(14), E2F1(3), MDM2(2), NXT1(1), PRB1(2), TP53(128) 2958909 163 125 141 8 15 29 38 24 57 0 1.1e-09 <1.00e-15 <1.54e-13
5 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(2), ATM(22), BRCA1(8), CDKN1A(1), CHEK1(6), CHEK2(2), GADD45A(1), JUN(1), MAPK8(3), MDM2(2), MRE11A(6), NFKB1(3), NFKBIA(1), RAD50(3), RAD51(1), RBBP8(3), TP53(128), TP73(4) 10278207 197 139 174 16 15 41 53 28 60 0 1.7e-06 1.78e-15 2.19e-13
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(22), CDC25A(4), CDC25B(1), CDC25C(3), CDK2(4), CDK4(2), CHEK1(6), MYT1(6), RB1(13), TP53(128), WEE1(3) 6070332 192 140 169 13 15 37 43 29 68 0 1.6e-07 2.22e-15 2.28e-13
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(22), ATR(16), CDC25C(3), CHEK1(6), CHEK2(2), TP53(128) 5517526 177 136 154 7 10 35 48 28 56 0 1e-08 3.77e-15 3.16e-13
8 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(3), MAX(3), SP1(1), SP3(4), TP53(128), WT1(8) 2427858 147 122 125 10 9 29 35 21 53 0 1.2e-06 4.11e-15 3.16e-13
9 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(3), DNAJC3(3), MAP3K14(1), NFKB1(3), NFKBIA(1), TP53(128) 3372941 139 121 117 9 9 23 36 18 53 0 2.2e-06 5.77e-15 3.95e-13
10 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(4), DAXX(6), HRAS(1), PAX3(6), PML(7), RARA(3), RB1(13), SIRT1(1), SP100(9), TNFRSF1B(1), TP53(128) 6622222 179 131 157 15 14 30 47 25 63 0 3.8e-07 7.77e-15 4.60e-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 IL18PATHWAY Pro-inflammatory IL-18 is activated in macrophages by caspase-1 cleavage and, in conjunction with IL-12, stimulates Th1 cell differentiation. CASP1, IFNG, IL12A, IL12B, IL18, IL2 6 CASP1(2), IFNG(4), IL12A(3), IL2(5) 1033019 14 12 13 1 2 7 2 2 1 0 0.15 0.23 1
2 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(4), COQ5(5), COQ6(3), COQ7(1), NDUFA12(2), NDUFA13(4), NDUFB11(1) 1380412 20 14 20 2 5 5 5 1 4 0 0.082 0.3 1
3 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 11 CCNE1(3), CDK2(4), CDKN1B(3), CUL1(6), E2F1(3), NEDD8(2), SKP2(4), TFDP1(3), UBE2M(1) 2352746 29 22 29 4 5 6 10 6 2 0 0.082 0.34 1
4 BOTULINPATHWAY Blockade of Neurotransmitter Relase by Botulinum Toxin CHRM1, CHRNA1, SNAP25, STX1A, VAMP2 5 CHRM1(2), CHRNA1(7), SNAP25(4), STX1A(3) 1118665 16 13 16 3 5 3 5 1 2 0 0.2 0.34 1
5 HSA00902_MONOTERPENOID_BIOSYNTHESIS Genes involved in monoterpenoid biosynthesis CYP2C19, CYP2C9 2 CYP2C19(9), CYP2C9(3) 690893 12 11 12 3 2 3 3 2 2 0 0.54 0.39 1
6 HSA00730_THIAMINE_METABOLISM Genes involved in thiamine metabolism LHPP, MTMR1, MTMR2, MTMR6, NFS1, PHPT1, THTPA, TPK1 8 LHPP(2), MTMR1(5), MTMR2(2), MTMR6(6), NFS1(4), PHPT1(1), TPK1(5) 2218323 25 20 25 3 1 9 6 7 1 1 0.15 0.53 1
7 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 CCNE1(3), CDC34(1), CDK2(4), CUL1(6), E2F1(3), FBXW7(4), TFDP1(3) 2268932 24 18 24 2 5 6 8 5 0 0 0.035 0.58 1
8 HSA00031_INOSITOL_METABOLISM Genes involved in inositol metabolism ALDH6A1, TPI1 2 TPI1(6) 566088 6 5 6 0 0 3 2 1 0 0 0.24 0.6 1
9 HSA00830_RETINOL_METABOLISM Genes involved in retinol metabolism ALDH1A1, ALDH1A2, BCMO1, RDH5 4 ALDH1A1(3), ALDH1A2(9), BCMO1(4) 1334612 16 14 16 3 2 4 5 1 4 0 0.33 0.63 1
10 INOSITOL_METABOLISM ALDH6A1, ALDOA, ALDOB, ALDOC, TPI1 5 ALDOA(2), ALDOB(4), ALDOC(1), TPI1(6) 1340337 13 10 13 0 0 5 4 2 2 0 0.043 0.71 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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