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Phenotypic Information (metabolism pathway, cancer, disease, phenome) | |
Gene-Gene Network Information: Co-Expression Network, Interacting Genes & KEGG | |
Gene Summary for GMPR |
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Phenotypic Information for GMPR(metabolism pathway, cancer, disease, phenome) |
Cancer Description | |
Cancer | CGAP: GMPR |
Familial Cancer Database: GMPR |
* This gene is included in those cancer gene databases. |
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 | |
KEGG_PURINE_METABOLISM REACTOME_METABOLISM_OF_NUCLEOTIDES REACTOME_PURINE_METABOLISM |
Others | |
OMIM | |
Orphanet | |
Disease | KEGG Disease: GMPR |
MedGen: GMPR (Human Medical Genetics with Condition) | |
ClinVar: GMPR | |
Phenotype | MGI: GMPR (International Mouse Phenotyping Consortium) |
PhenomicDB: GMPR |
Mutations for GMPR |
* 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 |
ovary | GMPR | chr6 | 16266698 | 16266718 | GMPR | chr6 | 16278220 | 16278240 |
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 GMPR 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 |
CV340881 | TXLNG | 399 | 478 | X | 16820112 | 16820486 | GMPR | 479 | 529 | 6 | 16294671 | 16294721 |
Other DBs for Structural Variants |
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Copy Number Variations in COSMIC: go to COSMIC mutation CNV/Expr |
Mutation type/ Tissue ID | brca | cns | cerv | endome | haematopo | kidn | Lintest | liver | lung | ns | ovary | pancre | prost | skin | stoma | thyro | urina | |||
Total # sample |   |   |   | 1 |   |   |   |   |   |   |   |   |   |   |   |   |   | |||
GAIN (# sample) |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   | |||
LOSS (# sample) |   |   |   | 1 |   |   |   |   |   |   |   |   |   |   |   |   |   |
cf) Tissue ID; Tissue type (1; Breast, 2; Central_nervous_system, 3; Cervix, 4; Endometrium, 5; Haematopoietic_and_lymphoid_tissue, 6; Kidney, 7; Large_intestine, 8; Liver, 9; Lung, 10; NS, 11; Ovary, 12; Pancreas, 13; Prostate, 14; Skin, 15; Stomach, 16; Thyroid, 17; Urinary_tract) |
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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=38) | (# total SNVs=15) |
(# 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 |
chr6:16247101-16247101 | p.R39Q | 4 |
chr6:16290697-16290697 | p.A234A | 2 |
chr6:16247135-16247135 | p.I50I | 2 |
chr6:16254938-16254938 | p.R146H | 2 |
chr6:16290796-16290797 | p.M269fs*4 | 2 |
chr6:16286037-16286037 | p.T223M | 2 |
chr6:16247086-16247086 | p.R34H | 2 |
chr6:16290696-16290696 | p.A234V | 2 |
chr6:16274694-16274694 | p.G172R | 2 |
chr6:16247095-16247095 | p.T37M | 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 |   | 1 | 2 | 6 |   |   |   |   | 2 | 1 |   | 4 | 1 | 1 |   |   | 1 | 3 |   | 9 |
# mutation |   | 1 | 2 | 7 |   |   |   |   | 2 | 1 |   | 4 | 1 | 1 |   |   | 1 | 3 |   | 8 |
nonsynonymous SNV |   |   | 1 | 2 |   |   |   |   | 2 | 1 |   | 4 |   |   |   |   |   | 2 |   | 5 |
synonymous SNV |   | 1 | 1 | 5 |   |   |   |   |   |   |   |   | 1 | 1 |   |   | 1 | 1 |   | 3 |
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 |
chr6:16290697 | p.A234A | 2 |
chr6:16247101 | p.R39Q | 2 |
chr6:16247135 | p.I51I | 1 |
chr6:16274681 | p.T223M | 1 |
chr6:16295255 | p.D84G | 1 |
chr6:16247138 | p.A100A | 1 |
chr6:16274694 | p.F238F | 1 |
chr6:16295259 | p.V101M | 1 |
chr6:16250558 | p.A274T | 1 |
chr6:16274705 | p.E111K | 1 |
Other DBs for Point Mutations |
Copy Number for GMPR 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 GMPR |
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 |
ACOT4,AP1G2,DHRS4-AS1,DCAF11,EAPP,GMPR2,HOMEZ, KHNYN,KLHDC2,LRP10,MDP1,NEDD8,OXA1L,PIGH, PSME1,RNF31,THTPA,TINF2,TM9SF1,TOX4,TTC8 | ARMCX6,C10orf35,C11orf52,C14orf93,DALRD3,DGCR2,DNAL4, ELMO3,FBL,GMPR2,ING4,MED29,MRFAP1L1,MRPL49, NR2C2AP,PRKCZ,RAB25,RPL3,SPINT2,STK16,TTLL1 | ||||
ALKBH1,APEX1,DNAAF2,C14orf119,DTD2,C14orf166,CGRRF1, CHMP4A,CNIH1,DAD1,EAPP,GMPR2,HAUS4,ISCA2, KIAA0391,MDP1,NEDD8,RPS29,SNX6,TMEM55B,ZNF410 | BLOC1S1,TEN1,LINC00324,RPP25L,CCNDBP1,CHMP5,DERA, EAPP,GABARAP,GMPR2,HINFP,HOXB7,MAT2B,OAZ1, LAMTOR2,SAT1,TMEM219,TMEM59,UBAC2,VPS28,ZNF706 |
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 GMPR |
Cross-referenced pharmacological DB IDs from Uniprot |
DB Category | DB Name | DB's ID and Url link |
Drug-Gene Interaction Network |
* Gene Centered Interaction Network. |
* Drug Centered Interaction Network. |
DrugBank ID | Target Name | Drug Groups | Generic Name | Drug Centered Network | Drug Structure |
DB01972 | guanosine monophosphate reductase | experimental | Guanosine-5'-Monophosphate |
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Cross referenced IDs for GMPR |
* 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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