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Phenotypic Information (metabolism pathway, cancer, disease, phenome) | |
Gene-Gene Network Information: Co-Expression Network, Interacting Genes & KEGG | |
Gene Summary for RPS2 |
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Phenotypic Information for RPS2(metabolism pathway, cancer, disease, phenome) |
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Cancer | CGAP: RPS2 |
Familial Cancer Database: RPS2 |
* This gene is included in those cancer gene databases. |
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Oncogene 1 | Significant driver gene in CLL 6, |
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, 6 http://www.nature.com/nature/journal/v505/n7484/full/nature12912.html, 7Therapeutic Vulnerabilities in Cancer; http://cbio.mskcc.org/cancergenomics/statius/ |
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REACTOME_METABOLISM_OF_PROTEINS REACTOME_METABOLISM_OF_MRNA REACTOME_METABOLISM_OF_RNA |
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OMIM | 603624; gene. |
Orphanet | |
Disease | KEGG Disease: RPS2 |
MedGen: RPS2 (Human Medical Genetics with Condition) | |
ClinVar: RPS2 | |
Phenotype | MGI: RPS2 (International Mouse Phenotyping Consortium) |
PhenomicDB: RPS2 |
Mutations for RPS2 |
* 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. |
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There's no structural variation information in COSMIC data for this gene. |
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* From mRNA Sanger sequences, Chitars2.0 arranged chimeric transcripts. This table shows RPS2 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 |
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There's no copy number variation information in COSMIC data for this gene. |
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Stat. for Non-Synonymous SNVs (# total SNVs=12) | (# total SNVs=9) |
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(# total SNVs=0) | (# total SNVs=0) |
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* 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 |
chr16:2012182-2012182 | p.Q267* | 3 |
chr16:2014591-2014591 | p.G12G | 3 |
chr16:2012592-2012592 | p.V205V | 2 |
chr16:2012609-2012609 | p.R200G | 2 |
chr16:2014528-2014528 | p.I33I | 2 |
chr16:2012794-2012794 | p.P164P | 2 |
chr16:2012222-2012222 | p.P253P | 2 |
chr16:2014271-2014271 | p.? | 1 |
chr16:2014292-2014292 | p.F84L | 1 |
chr16:2012119-2012119 | p.P288S | 1 |
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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 |   | 3 |   |   |   |   | 1 |   |   |   |   |   |   |   | 4 | 2 |   | 2 |
# mutation | 2 | 1 |   | 3 |   |   |   |   | 1 |   |   |   |   |   |   |   | 4 | 2 |   | 2 |
nonsynonymous SNV |   | 1 |   | 2 |   |   |   |   | 1 |   |   |   |   |   |   |   | 2 | 1 |   |   |
synonymous SNV | 2 |   |   | 1 |   |   |   |   |   |   |   |   |   |   |   |   | 2 | 1 |   | 2 |
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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* 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 |
chr16:2012222 | p.P253P | 2 |
chr16:2012818 | p.E105E | 1 |
chr16:2012881 | p.F84L | 1 |
chr16:2012119 | p.P288S | 1 |
chr16:2012906 | p.V282M | 1 |
chr16:2012137 | p.L273L | 1 |
chr16:2013210 | p.Q267E | 1 |
chr16:2012162 | p.A243V | 1 |
chr16:2014292 | p.F236F | 1 |
chr16:2012182 | p.K212K | 1 |
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* 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. |
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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 RPS2 |
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* CCLE gene expression data were extracted from CCLE_Expression_Entrez_2012-10-18.res: Gene-centric RMA-normalized mRNA expression data. |
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* 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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* This plots show the correlation between CNV and gene expression. |
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Gene-Gene Network Information |
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* 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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RPL10,RPL10A,RPL11,RPL27A,RPL32,RPL35A,RPL36, RPL36AL,RPL37A,RPL41,RPLP2,RPS10,RPS11,RPS13, RPS14,RPS15A,RPS27A,RPS29,RPS9,RPSA,RPSAP58 | BTF3,CCT4,DPH5,EIF3M,RPL15,RPL22,RPL24, RPL26,RPL30,RPL32,RPL35A,RPL38,RPL41,RPL6, RPS13,RPS15A,RPS24,RPS29,RPS3A,RPS7,UXT |
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EEF1B2,RPL10A,RPL27,RPL29,RPL35,RPL36,RPL41, RPLP0,RPS10,RPS14,RPS16,RPS18,RPS29,RPS3, RPS3A,RPS5,RPS6,RPS8,RPS9,RPSAP58,TIMM9 | SMDT1,COX16,EEF1B2,RPL26,RPL32,RPL36,RPL37A, RPL38,RPL39,RPLP0,RPS10,RPS13,RPS14,RPS18, RPS21,RPS29,RPS3,TPT1,UQCRH,UQCRHL,UXT |
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* 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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Pharmacological Information for RPS2 |
There's no related Drug. |
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Cross referenced IDs for RPS2 |
* 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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