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Phenotypic Information (metabolism pathway, cancer, disease, phenome) | |
Gene-Gene Network Information: Co-Expression Network, Interacting Genes & KEGG | |
Gene Summary for MED6 |
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Phenotypic Information for MED6(metabolism pathway, cancer, disease, phenome) |
Cancer Description | |
Cancer | CGAP: MED6 |
Familial Cancer Database: MED6 |
* This gene is included in those cancer gene databases. |
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Oncogene 1 | Significant driver gene in |
cf) number; DB name 1 Oncogene; http://nar.oxfordjournals.org/content/35/suppl_1/D721.long, 2 Tumor Suppressor gene; https://bioinfo.uth.edu/TSGene/, 3 Cancer Gene Census; http://www.nature.com/nrc/journal/v4/n3/abs/nrc1299.html, 4 CancerGenes; http://nar.oxfordjournals.org/content/35/suppl_1/D721.long, 5 Network of Cancer Gene; http://ncg.kcl.ac.uk/index.php, 1Therapeutic Vulnerabilities in Cancer; http://cbio.mskcc.org/cancergenomics/statius/ |
Metabolic Pathway Description | |
REACTOME_METABOLISM_OF_LIPIDS_AND_LIPOPROTEINS |
Others | |
OMIM | |
Orphanet | |
Disease | KEGG Disease: MED6 |
MedGen: MED6 (Human Medical Genetics with Condition) | |
ClinVar: MED6 | |
Phenotype | MGI: MED6 (International Mouse Phenotyping Consortium) |
PhenomicDB: MED6 |
Mutations for MED6 |
* Under tables are showing count per each tissue to give us broad intuition about tissue specific mutation patterns.You can go to the detailed page for each mutation database's web site. |
Structural Variants in COSMIC: go to COSMIC mutation histogram |
- Statistics for Tissue and Mutation type | Top |
- For Inter-chromosomal Variations |
There's no inter-chromosomal structural variation. |
- For Intra-chromosomal Variations |
* Intra-chromosomal variantions includes 'intrachromosomal amplicon to amplicon', 'intrachromosomal amplicon to non-amplified dna', 'intrachromosomal deletion', 'intrachromosomal fold-back inversion', 'intrachromosomal inversion', 'intrachromosomal tandem duplication', 'Intrachromosomal unknown type', 'intrachromosomal with inverted orientation', 'intrachromosomal with non-inverted orientation'. |
Sample | Symbol_a | Chr_a | Start_a | End_a | Symbol_b | Chr_b | Start_b | End_b |
prostate | MED6 | chr14 | 71058029 | 71060029 | RGS6 | chr14 | 72901357 | 72903357 |
cf) Tissue number; Tissue name (1;Breast, 2;Central_nervous_system, 3;Haematopoietic_and_lymphoid_tissue, 4;Large_intestine, 5;Liver, 6;Lung, 7;Ovary, 8;Pancreas, 9;Prostate, 10;Skin, 11;Soft_tissue, 12;Upper_aerodigestive_tract) |
Related fusion transcripts : go to Chitars2.0 |
* From mRNA Sanger sequences, Chitars2.0 arranged chimeric transcripts. This table shows MED6 related fusion information. |
ID | Head Gene | Tail Gene | Accession | Gene_a | qStart_a | qEnd_a | Chromosome_a | tStart_a | tEnd_a | Gene_a | qStart_a | qEnd_a | Chromosome_a | tStart_a | tEnd_a |
Other DBs for Structural Variants |
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Copy Number Variations in COSMIC: go to COSMIC mutation CNV/Expr |
There's no copy number variation information in COSMIC data for this gene. |
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SNV Counts per Each Loci in COSMIC data: go to COSMIC point mutation |
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Somatic Mutation Counts per Tissue in COSMIC data |
Stat. for Non-Synonymous SNVs (# total SNVs=11) | (# total SNVs=1) |
(# total SNVs=0) | (# total SNVs=0) |
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Top 10 SNVs Having the Most Samples in COSMIC data |
* When you move the cursor on each content, you can see more deailed mutation information on the Tooltip. Those are primary_site,primary_histology,mutation(aa),pubmedID. |
GRCh37 position | Mutation(aa) | Unique sampleID count |
chr14:71059641-71059641 | p.P141L | 2 |
chr14:71059645-71059645 | p.H140Y | 2 |
chr14:71051554-71051555 | p.E240fs*1 | 2 |
chr14:71063403-71063403 | p.E67K | 2 |
chr14:71063419-71063419 | p.N61K | 2 |
chr14:71058052-71058052 | p.I171M | 1 |
chr14:71064415-71064415 | p.S34S | 1 |
chr14:71064431-71064431 | p.V29A | 1 |
chr14:71059684-71059684 | p.Q127* | 1 |
chr14:71059715-71059715 | p.? | 1 |
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SNV Counts per Each Loci in TCGA data |
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Point Mutation/ Tissue ID | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | 13 | 14 | 15 | 16 | 17 | 18 | 19 | 20 |
# sample |   |   |   | 2 |   |   |   |   | 1 |   |   |   |   |   |   |   |   | 2 | 1 | 3 |
# mutation |   |   |   | 2 |   |   |   |   | 1 |   |   |   |   |   |   |   |   | 2 | 1 | 3 |
nonsynonymous SNV |   |   |   | 1 |   |   |   |   |   |   |   |   |   |   |   |   |   | 2 |   | 3 |
synonymous SNV |   |   |   | 1 |   |   |   |   | 1 |   |   |   |   |   |   |   |   |   | 1 |   |
cf) Tissue ID; Tissue type (1; BLCA[Bladder Urothelial Carcinoma], 2; BRCA[Breast invasive carcinoma], 3; CESC[Cervical squamous cell carcinoma and endocervical adenocarcinoma], 4; COAD[Colon adenocarcinoma], 5; GBM[Glioblastoma multiforme], 6; Glioma Low Grade, 7; HNSC[Head and Neck squamous cell carcinoma], 8; KICH[Kidney Chromophobe], 9; KIRC[Kidney renal clear cell carcinoma], 10; KIRP[Kidney renal papillary cell carcinoma], 11; LAML[Acute Myeloid Leukemia], 12; LUAD[Lung adenocarcinoma], 13; LUSC[Lung squamous cell carcinoma], 14; OV[Ovarian serous cystadenocarcinoma ], 15; PAAD[Pancreatic adenocarcinoma], 16; PRAD[Prostate adenocarcinoma], 17; SKCM[Skin Cutaneous Melanoma], 18:STAD[Stomach adenocarcinoma], 19:THCA[Thyroid carcinoma], 20:UCEC[Uterine Corpus Endometrial Carcinoma]) |
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Top 10 SNVs Having the Most Samples in TCGA data |
* We represented just top 10 SNVs. When you move the cursor on each content, you can see more deailed mutation information on the Tooltip. Those are primary_site, primary_histology, mutation(aa), pubmedID. |
Genomic Position | Mutation(aa) | Unique sampleID count |
chr14:71064415 | p.G244G,MED6 | 1 |
chr14:71064431 | p.I178M,MED6 | 1 |
chr14:71067337 | p.S142P,MED6 | 1 |
chr14:71051560 | p.R82Q,MED6 | 1 |
chr14:71058052 | p.P76S,MED6 | 1 |
chr14:71059660 | p.E67K,MED6 | 1 |
chr14:71063357 | p.S34S,MED6 | 1 |
chr14:71063376 | p.V29A,MED6 | 1 |
chr14:71063403 | p.I6I,MED6 | 1 |
Other DBs for Point Mutations |
Copy Number for MED6 in TCGA |
* Copy number data were extracted from TCGA using R package TCGA-Assembler. The URLs of all public data files on TCGA DCC data server were gathered on Jan-05-2015. Function ProcessCNAData in TCGA-Assembler package was used to obtain gene-level copy number value which is calculated as the average copy number of the genomic region of a gene. |
cf) Tissue ID[Tissue type]: BLCA[Bladder Urothelial Carcinoma], BRCA[Breast invasive carcinoma], CESC[Cervical squamous cell carcinoma and endocervical adenocarcinoma], COAD[Colon adenocarcinoma], GBM[Glioblastoma multiforme], Glioma Low Grade, HNSC[Head and Neck squamous cell carcinoma], KICH[Kidney Chromophobe], KIRC[Kidney renal clear cell carcinoma], KIRP[Kidney renal papillary cell carcinoma], LAML[Acute Myeloid Leukemia], LUAD[Lung adenocarcinoma], LUSC[Lung squamous cell carcinoma], OV[Ovarian serous cystadenocarcinoma ], PAAD[Pancreatic adenocarcinoma], PRAD[Prostate adenocarcinoma], SKCM[Skin Cutaneous Melanoma], STAD[Stomach adenocarcinoma], THCA[Thyroid carcinoma], UCEC[Uterine Corpus Endometrial Carcinoma] |
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Gene Expression for MED6 |
Gene Expression in Cancer Cell-lines (CCLE) |
* CCLE gene expression data were extracted from CCLE_Expression_Entrez_2012-10-18.res: Gene-centric RMA-normalized mRNA expression data. |
Differential Gene Expression in Primary Tumors (TCGA) |
* Normalized gene expression data of RNASeqV2 was extracted from TCGA using R package TCGA-Assembler. The URLs of all public data files on TCGA DCC data server were gathered at Jan-05-2015. Only eight cancer types have enough normal control samples for differential expression analysis. (t test, adjusted p<0.05 (using Benjamini-Hochberg FDR)) |
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CNV vs Gene Expression Plot |
* This plots show the correlation between CNV and gene expression. |
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Gene-Gene Network Information |
Co-Expressed gene's network Plot |
* Co-Expression network figures were drawn using R package igraph. Only the top 20 genes with the highest correlations were shown. Red circle: input gene, orange circle: cell metabolism gene, sky circle: other gene |
AHSA1,ALKBH1,C14orf1,C14orf169,CCNK,COX16,DLST, EIF2B2,EIF2S1,ERH,ISCA2,MED6,PSMA3,PSMC1, SNW1,TDP1,TIMM9,VRK1,VTI1B,WDR89,ZNF410 | BRIX1,YAE1D1,EXOSC9,FAM103A1,FANCL,GNRHR2,GTF2F2, INTS12,MED6,NIFK,N4BP2L1,NUP35,NUP37,PRPF18, RBM22,REPS1,TRMT10C,RSL24D1,RWDD3,SRSF8,TBP |
AHSA1,ALKBH1,APEX1,DNAAF2,SLIRP,C14orf166,COX16, EIF2S1,ERH,FKBP3,ISCA2,MED6,NEDD8,NGDN, LRR1,PSMA3,PSMB5,PSMC6,SNW1,TIMM9,TRMT5 | BUD31,C14orf119,C14orf166,C18orf21,CDC123,COPZ1,DAD1, DAP3,DPM1,HAX1,MED6,MRPL49,NDUFB4,NUP37, ORC5,OSTC,PDRG1,PSMD10,SNRPC,SSR2,ZNHIT3 |
Co-Expressed gene's Protein-protein interaction Network Plot |
* Co-Expression network figures were drawn using R package igraph. Only the top 20 genes with the highest correlations were shown. Red circle: input gene, orange circle: cell metabolism gene, sky circle: other gene |
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Interacting Genes (from Pathway Commons) |
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Pharmacological Information for MED6 |
There's no related Drug. |
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Cross referenced IDs for MED6 |
* We obtained these cross-references from Uniprot database. It covers 150 different DBs, 18 categories. http://www.uniprot.org/help/cross_references_section |
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