Mutation Analysis (MutSig v2.0 and MutSigCV v0.9 merged result)
Kidney Renal Papillary Cell Carcinoma (Primary solid tumor)
15 January 2014  |  analyses__2014_01_15
Maintainer Information
Citation Information
doi:10.7908/C1JH3JM1
Maintained by Dan DiCara (Broad Institute)
Cite as Broad Institute TCGA Genome Data Analysis Center (2014): Mutation Analysis (MutSig v2.0 and MutSigCV v0.9 merged result). Broad Institute of MIT and Harvard. doi:10.7908/C1JH3JM1
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 and MutSigCV v0.9 merged result was used to generate the results found in this report.

  • Working with individual set: KIRP-TP

  • Number of patients in set: 112

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:KIRP-TP.final_analysis_set.maf

  • Significantly mutated genes (q ≤ 0.1): 2

  • Mutations seen in COSMIC: 42

  • Significantly mutated genes in COSMIC territory: 11

  • Significantly mutated genesets: 0

Mutation Preprocessing

  • Read 112 MAFs of type "Broad"

  • Total number of mutations in input MAFs: 10029

  • After removing 78 mutations outside chr1-24: 9951

  • After removing 587 blacklisted mutations: 9364

  • After removing 147 noncoding mutations: 9217

  • After collapsing adjacent/redundant mutations: 7780

Mutation Filtering

  • Number of mutations before filtering: 7780

  • After removing 311 mutations outside gene set: 7469

  • After removing 9 mutations outside category set: 7460

Results
Breakdown of Mutations by Type

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

type count
Frame_Shift_Del 472
Frame_Shift_Ins 172
In_Frame_Del 95
In_Frame_Ins 28
Missense_Mutation 4472
Nonsense_Mutation 247
Nonstop_Mutation 5
Silent 1649
Splice_Site 319
Translation_Start_Site 1
Total 7460
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 468 186386483 2.5e-06 2.5 1.4 2.1
*Cp(A/C/T)->T 855 1509673770 5.7e-07 0.57 0.32 1.7
A->G 845 1622585631 5.2e-07 0.52 0.3 2.3
transver 2304 3318645884 6.9e-07 0.69 0.4 5
indel+null 1330 3318645884 4e-07 0.4 0.23 NaN
double_null 9 3318645884 2.7e-09 0.0027 0.0015 NaN
Total 5811 3318645884 1.8e-06 1.8 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: KIRP-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_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: 2. 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_clust p_cons p_joint p_cv p q
1 KCNK5 potassium channel, subfamily K, member 5 159653 2 2 2 0 0 0 0 0 2 0 0.26 0 0 0.026 0 0
2 NF2 neurofibromin 2 (merlin) 181882 7 7 7 0 0 0 0 0 7 0 0.43 0.98 0.59 9.8e-08 1e-06 0.0092
3 PCDHGC5 protocadherin gamma subfamily C, 5 324524 15 13 15 6 0 3 4 3 4 1 NaN NaN NaN 0.00028 0.00028 1
4 MET met proto-oncogene (hepatocyte growth factor receptor) 478818 9 9 8 0 0 3 2 4 0 0 0.00038 0.0011 0.000066 0.99 0.0007 1
5 PCDHAC2 protocadherin alpha subfamily C, 2 331745 5 5 5 4 3 1 0 1 0 0 NaN NaN NaN 0.0022 0.0022 1
6 PCF11 PCF11, cleavage and polyadenylation factor subunit, homolog (S. cerevisiae) 476303 8 7 7 3 0 1 4 3 0 0 0.00019 0.82 0.00073 0.39 0.0026 1
7 LGI4 leucine-rich repeat LGI family, member 4 78713 4 4 4 0 0 1 1 2 0 0 0.35 0.015 0.046 0.0062 0.0026 1
8 ELF3 E74-like factor 3 (ets domain transcription factor, epithelial-specific ) 127882 3 3 3 0 0 0 0 1 2 0 0.94 0.84 1 0.00031 0.0028 1
9 MLX MAX-like protein X 80381 2 2 2 0 0 0 0 0 2 0 NaN NaN NaN 0.003 0.003 1
10 RAB27B RAB27B, member RAS oncogene family 74294 1 1 1 0 0 0 0 0 1 0 NaN NaN NaN 0.0038 0.0038 1
11 BHMT betaine-homocysteine methyltransferase 139714 4 4 4 0 0 0 2 0 2 0 0.28 0.11 0.22 0.0036 0.0065 1
12 C6orf195 chromosome 6 open reading frame 195 43456 2 2 2 0 0 0 0 0 2 0 0.7 0.41 0.51 0.0017 0.0071 1
13 PIPOX pipecolic acid oxidase 134960 2 2 2 0 0 0 0 0 2 0 0.43 0.55 0.96 0.001 0.0078 1
14 ZNF367 zinc finger protein 367 81410 2 2 2 0 0 0 0 0 2 0 0.017 0.74 0.13 0.011 0.011 1
15 NFE2L2 nuclear factor (erythroid-derived 2)-like 2 199571 3 3 3 0 0 0 1 2 0 0 0.024 0.011 0.005 0.29 0.011 1
16 LHFPL4 lipoma HMGIC fusion partner-like 4 84504 1 1 1 0 0 0 0 0 1 0 NaN NaN NaN 0.012 0.012 1
17 RAET1L retinoic acid early transcript 1L 74711 1 1 1 0 0 0 0 0 1 0 NaN NaN NaN 0.012 0.012 1
18 LYAR Ly1 antibody reactive homolog (mouse) 131222 2 2 2 0 1 0 0 0 1 0 0.059 0.11 0.037 0.045 0.012 1
19 STAG2 stromal antigen 2 436344 5 5 5 1 0 0 0 0 5 0 0.47 0.4 0.49 0.0037 0.013 1
20 SAV1 salvador homolog 1 (Drosophila) 129761 3 3 3 0 0 1 0 0 2 0 0.1 0.97 0.18 0.011 0.014 1
21 KDELR3 KDEL (Lys-Asp-Glu-Leu) endoplasmic reticulum protein retention receptor 3 81071 2 2 2 0 0 0 1 0 1 0 0.11 0.095 0.088 0.024 0.015 1
22 WFDC10A WAP four-disulfide core domain 10A 27693 1 1 1 0 0 0 0 0 1 0 NaN NaN NaN 0.016 0.016 1
23 CYHR1 cysteine/histidine-rich 1 65734 1 1 1 0 0 0 0 0 1 0 NaN NaN NaN 0.017 0.017 1
24 VPS37D vacuolar protein sorting 37 homolog D (S. cerevisiae) 30628 1 1 1 0 0 0 0 0 1 0 NaN NaN NaN 0.018 0.018 1
25 EPSTI1 epithelial stromal interaction 1 (breast) 143344 3 2 3 0 0 1 0 2 0 0 0.0017 0.38 0.0079 0.4 0.021 1
26 STARD3 StAR-related lipid transfer (START) domain containing 3 154249 2 2 2 0 0 0 0 0 2 0 0.96 0.049 0.077 0.041 0.021 1
27 CCDC28B coiled-coil domain containing 28B 69558 2 2 1 0 0 0 0 0 2 0 NaN NaN NaN 0.023 0.023 1
28 PARD6B par-6 partitioning defective 6 homolog beta (C. elegans) 118830 4 4 4 0 0 0 2 0 2 0 0.63 0.71 0.91 0.004 0.024 1
29 PEBP1 phosphatidylethanolamine binding protein 1 49220 2 2 2 0 0 1 0 1 0 0 0.017 0.19 0.061 0.064 0.026 1
30 NLRP9 NLR family, pyrin domain containing 9 337307 2 2 2 0 0 0 0 2 0 0 0.1 0.0044 0.0039 1 0.026 1
31 C10orf95 chromosome 10 open reading frame 95 29310 1 1 1 0 0 0 0 0 1 0 NaN NaN NaN 0.027 0.027 1
32 LRFN4 leucine rich repeat and fibronectin type III domain containing 4 132049 3 3 3 0 1 0 0 0 2 0 0.8 0.65 1 0.0048 0.031 1
33 C9orf24 chromosome 9 open reading frame 24 100008 1 1 1 0 0 0 0 0 1 0 NaN NaN NaN 0.031 0.031 1
34 TMEM37 transmembrane protein 37 62272 1 1 1 0 0 0 1 0 0 0 NaN NaN NaN 0.032 0.032 1
35 FAT1 FAT tumor suppressor homolog 1 (Drosophila) 1538743 8 8 8 1 1 0 2 2 3 0 0.003 0.48 0.0057 0.99 0.035 1
KCNK5

Figure S1.  This figure depicts the distribution of mutations and mutation types across the KCNK5 significant gene.

NF2

Figure S2.  This figure depicts the distribution of mutations and mutation types across the NF2 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: 11. Number of genes displayed: 10

rank gene description n cos n_cos N_cos cos_ev p q
1 MET met proto-oncogene (hepatocyte growth factor receptor) 9 34 4 3808 12 8.2e-11 3.7e-07
2 FGFR3 fibroblast growth factor receptor 3 (achondroplasia, thanatophoric dwarfism) 5 62 3 6944 1469 3e-07 0.00067
3 NF2 neurofibromin 2 (merlin) 7 550 4 61600 29 5.2e-06 0.0078
4 SMARCA4 SWI/SNF related, matrix associated, actin dependent regulator of chromatin, subfamily a, member 4 5 30 2 3360 3 0.000017 0.019
5 KRAS v-Ki-ras2 Kirsten rat sarcoma viral oncogene homolog 2 52 2 5824 29208 0.000052 0.047
6 BRAF v-raf murine sarcoma viral oncogene homolog B1 2 89 2 9968 14380 0.00015 0.081
7 CDCA8 cell division cycle associated 8 1 1 1 112 1 0.0002 0.081
8 FLCN folliculin 1 1 1 112 1 0.0002 0.081
9 G6PC glucose-6-phosphatase, catalytic subunit 1 1 1 112 1 0.0002 0.081
10 PLXDC2 plexin domain containing 2 1 1 1 112 1 0.0002 0.081

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: 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 MTORPATHWAY Mammalian target of rapamycin (mTOR) senses mitogenic factors and nutrients, including ATP, and induces cell proliferation. AKT1, EIF3S10, EIF4A1, EIF4A2, EIF4B, EIF4E, EIF4EBP1, EIF4G1, EIF4G2, EIF4G3, FKBP1A, FRAP1, MKNK1, PDK2, PDPK1, PIK3CA, PIK3R1, PPP2CA, PTEN, RPS6, RPS6KB1, TSC1, TSC2 21 EIF4A1(1), EIF4B(2), EIF4G1(1), EIF4G3(5), PIK3CA(2), PIK3R1(1), PTEN(2), TSC1(2), TSC2(4) 4653778 20 17 20 2 2 6 3 4 5 0 0.056 0.0016 0.4
2 ALANINE_AND_ASPARTATE_METABOLISM AARS, ABAT, ADSL, ADSS, AGXT, AGXT2, ASL, ASNS, ASPA, ASS, CAD, CRAT, DARS, DDO, GAD1, GAD2, GOT1, GOT2, GPT, GPT2, NARS, PC 21 AARS(1), ADSL(1), AGXT(1), AGXT2(1), ASNS(1), CAD(3), CRAT(1), DARS(3), DDO(1), GPT(2), PC(4) 4376807 19 17 19 1 0 3 1 8 7 0 0.078 0.0019 0.4
3 KREBPATHWAY The Krebs (citric acid) cycle takes place in mitochondria, where it extracts energy in the form of electron carriers NADH and FADH2, which drive the electron transport chain. ACO2, CS, FH, IDH2, MDH1, OGDH, SDHA, SUCLA2 8 FH(1), IDH2(1), MDH1(1), OGDH(2), SDHA(3) 1572837 8 8 8 0 0 3 1 1 3 0 0.052 0.0019 0.4
4 CBLPATHWAY Activated EGF receptors undergo endocytosis into clathrin-coated vesicles, where they are recycled to the membrane or ubiquitinated by Cbl. CBL, CSF1R, EGF, EGFR, GRB2, MET, PDGFRA, PRKCA, PRKCB1, SH3GLB1, SH3GLB2, SH3KBP1, SRC 12 CSF1R(1), EGF(1), MET(9), PDGFRA(2) 3254544 13 12 12 1 1 3 2 6 1 0 0.11 0.0048 0.74
5 CITRATE_CYCLE_TCA_CYCLE ACO1, ACO2, CS, DLD, DLST, DLSTP, FH, IDH1, IDH2, IDH3A, IDH3B, IDH3G, MDH1, MDH2, PC, PCK1, SDHA, SDHA, SDHAL2, SDHB, SUCLA2, SUCLG1, SUCLG2 20 ACO1(1), DLD(1), FH(1), IDH2(1), MDH1(1), PC(4), PCK1(1), SDHA(3) 3444763 13 12 13 0 0 2 2 3 6 0 0.035 0.0094 1
6 HSA00252_ALANINE_AND_ASPARTATE_METABOLISM Genes involved in alanine and aspartate metabolism AARS, AARS2, ABAT, ACY3, ADSL, ADSS, ADSSL1, AGXT, AGXT2, ASL, ASNS, ASPA, ASRGL1, ASS1, CAD, CRAT, DARS, DARS2, DDO, DLAT, DLD, GAD1, GAD2, GOT1, GOT2, GPT, GPT2, NARS, NARS2, PC, PDHA1, PDHA2, PDHB 33 AARS(1), AARS2(1), ACY3(1), ADSL(1), AGXT(1), AGXT2(1), ASNS(1), CAD(3), CRAT(1), DARS(3), DDO(1), DLD(1), GPT(2), PC(4) 6354267 22 19 22 1 0 3 2 9 8 0 0.039 0.012 1
7 DNAFRAGMENTPATHWAY DNA fragmentation during apoptosis is effected by DFF, a caspase-activated DNAse, and by endonuclease G. CASP3, CASP7, DFFA, DFFB, ENDOG, GZMB, HMGB1, HMGB2, TOP2A, TOP2B 9 HMGB1(3), HMGB2(2), TOP2B(3) 1518294 8 7 8 0 1 1 1 3 2 0 0.21 0.012 1
8 HSA00830_RETINOL_METABOLISM Genes involved in retinol metabolism ALDH1A1, ALDH1A2, BCMO1, RDH5 4 BCMO1(2), RDH5(2) 649405 4 4 4 1 0 0 3 0 1 0 0.72 0.015 1
9 UBIQUINONE_BIOSYNTHESIS NDUFA1, NDUFA10, NDUFA11, NDUFA4, NDUFA5, NDUFA8, NDUFB2, NDUFB4, NDUFB5, NDUFB6, NDUFB7, NDUFS1, NDUFS2, NDUFV1, NDUFV2 15 NDUFA10(1), NDUFB2(1), NDUFB5(1), NDUFS1(2), NDUFV1(1) 1169848 6 6 6 0 0 1 0 3 2 0 0.32 0.018 1
10 HSA01040_POLYUNSATURATED_FATTY_ACID_BIOSYNTHESIS Genes involved in polyunsaturated fatty acid biosynthesis ACAA1, ACOX1, ACOX3, ELOVL2, ELOVL5, ELOVL6, FADS1, FADS2, FASN, GPSN2, HADHA, HSD17B12, PECR, SCD 13 ACAA1(3), ACOX1(1), ACOX3(2), ELOVL6(1), FADS1(1), FASN(3), HADHA(1) 2460627 12 9 12 1 1 4 0 6 1 0 0.096 0.018 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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