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Phenotypic Information (metabolism pathway, cancer, disease, phenome) | |
Gene-Gene Network Information: Co-Expression Network, Interacting Genes & KEGG | |
Gene Summary for LIPF |
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Phenotypic Information for LIPF(metabolism pathway, cancer, disease, phenome) |
Cancer Description | |
Cancer | CGAP: LIPF |
Familial Cancer Database: LIPF |
* 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 | |
KEGG_GLYCEROLIPID_METABOLISM |
Others | |
OMIM | |
Orphanet | |
Disease | KEGG Disease: LIPF |
MedGen: LIPF (Human Medical Genetics with Condition) | |
ClinVar: LIPF | |
Phenotype | MGI: LIPF (International Mouse Phenotyping Consortium) |
PhenomicDB: LIPF |
Mutations for LIPF |
* 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 |
There's no structural variation information in COSMIC data for this gene. |
Related fusion transcripts : go to Chitars2.0 |
* From mRNA Sanger sequences, Chitars2.0 arranged chimeric transcripts. This table shows LIPF 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 |
BP341542 | YWHAE | 1 | 472 | 17 | 1265202 | 1303511 | LIPF | 472 | 579 | 10 | 90424200 | 90427102 | |
DA967267 | LIPF | 1 | 454 | 10 | 90424201 | 90428486 | PGA3 | 449 | 568 | 11 | 60974027 | 60975015 | |
BP341172 | LIPF | 1 | 435 | 10 | 90428470 | 90433488 | LIPF | 434 | 583 | 10 | 90424203 | 90427147 | |
AW867927 | FBRSL1 | 1 | 154 | 12 | 133073513 | 133073669 | LIPF | 148 | 312 | 10 | 90435973 | 90438301 |
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=29) | (# total SNVs=9) |
(# total SNVs=1) | (# 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 |
chr10:90438207-90438207 | p.Q322Q | 3 |
chr10:90427426-90427426 | p.K69T | 2 |
chr10:90435384-90435384 | p.T286T | 2 |
chr10:90435980-90435980 | p.G301G | 2 |
chr10:90427342-90427342 | p.Y41F | 2 |
chr10:90427359-90427359 | p.E47K | 2 |
chr10:90428327-90428327 | p.V79A | 2 |
chr10:90433385-90433385 | p.F237S | 2 |
chr10:90427414-90427414 | p.P65H | 2 |
chr10:90438420-90438420 | p.I393M | 2 |
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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 | 1 |   | 3 | 1 |   |   |   | 1 |   |   | 5 | 1 |   |   |   | 17 | 6 |   | 9 |
# mutation | 1 | 1 |   | 4 | 1 |   |   |   | 1 |   |   | 5 | 1 |   |   |   | 20 | 6 |   | 9 |
nonsynonymous SNV |   | 1 |   | 3 | 1 |   |   |   | 1 |   |   | 5 | 1 |   |   |   | 14 | 3 |   | 7 |
synonymous SNV | 1 |   |   | 1 |   |   |   |   |   |   |   |   |   |   |   |   | 6 | 3 |   | 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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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 |
chr10:90435980 | p.P65H,LIPF | 2 |
chr10:90427414 | p.K69I,LIPF | 2 |
chr10:90427426 | p.G268G,LIPF | 2 |
chr10:90429616 | p.G307D,LIPF | 1 |
chr10:90427343 | p.E47K,LIPF | 1 |
chr10:90427435 | p.V102D,LIPF | 1 |
chr10:90438413 | p.P315H,LIPF | 1 |
chr10:90429622 | p.I58S,LIPF | 1 |
chr10:90427345 | p.F104F,LIPF | 1 |
chr10:90436022 | p.G319G,LIPF | 1 |
Other DBs for Point Mutations |
Copy Number for LIPF 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 LIPF |
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 |
BSPH1,LINC00588,LEUTX,LIPF,MBL2,PNMA5,PRAMEF20, PRAMEF2,PRAMEF4,PRAMEF5,PRAMEF6,PRAMEF9,RFPL4B,SIM1, SLC38A8,SPRR1A,SPRR3,TPRX1,TRIM49D2,TRIM53AP,TRIM64 | ACTL7A,LINC00263,DHRS4-AS1,CCDC158,CNNM2,DLG2,FAM161A, FAM63A,FANCE,FAT3,GMCL1,GPRC6A,HOXA5,LIPF, LRIG1,PARP16,RGAG4,RGMB,RNF175,SEMA6D,ZMAT4 | ||||
ADAM3A,BPIFB6,CST9L,FAM19A2,FLJ23867,GPER1,MROH2B, HTN1,IGFALS,ITIH6,KCNU1,LIPF,LRRC52,MUC5B, MYH13,PDIA2,PGC,QSOX1,SHISA2,SNORA54,TFF2 | C6orf223,CST11,DNAH2,EN1,FAM153B,FAM71C,FBXO47, IGFALS,LIPF,MUC2,MYH16,NXNL1,OR2A25,SCGB1A1, SNORA47,SPINK4,SSX4,Z |
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 LIPF |
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 |
DB01083 | lipase, gastric | approved; investigational | Orlistat | ||
DB02457 | lipase, gastric | experimental | Undecyl-Phosphinic Acid Butyl Ester |
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Cross referenced IDs for LIPF |
* 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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