PhenoScanner V2: an expanded tool for searching human genotype–phenotype associations

Abstract Summary PhenoScanner is a curated database of publicly available results from large-scale genetic association studies in humans. This online tool facilitates ‘phenome scans’, where genetic variants are cross-referenced for association with many phenotypes of different types. Here we present...

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Vydáno v:Bioinformatics Ročník 35; číslo 22; s. 4851 - 4853
Hlavní autoři: Kamat, Mihir A, Blackshaw, James A, Young, Robin, Surendran, Praveen, Burgess, Stephen, Danesh, John, Butterworth, Adam S, Staley, James R
Médium: Journal Article
Jazyk:angličtina
Vydáno: England Oxford University Press 01.11.2019
Témata:
Applications Notes
Genetic Association Studies
Genome
Genome-Wide Association Study
Genotype
Humans
Linkage Disequilibrium
Phenotype
Polymorphism, Single Nucleotide
Software
ISSN:1367-4803, 1367-4811, 1460-2059, 1367-4811
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Shrnutí:Abstract Summary PhenoScanner is a curated database of publicly available results from large-scale genetic association studies in humans. This online tool facilitates ‘phenome scans’, where genetic variants are cross-referenced for association with many phenotypes of different types. Here we present a major update of PhenoScanner (‘PhenoScanner V2’), including over 150 million genetic variants and more than 65 billion associations (compared to 350 million associations in PhenoScanner V1) with diseases and traits, gene expression, metabolite and protein levels, and epigenetic markers. The query options have been extended to include searches by genes, genomic regions and phenotypes, as well as for genetic variants. All variants are positionally annotated using the Variant Effect Predictor and the phenotypes are mapped to Experimental Factor Ontology terms. Linkage disequilibrium statistics from the 1000 Genomes project can be used to search for phenotype associations with proxy variants. Availability and implementation PhenoScanner V2 is available at www.phenoscanner.medschl.cam.ac.uk.
Bibliografie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
ISSN:1367-4803
1367-4811
1460-2059
1367-4811
DOI:10.1093/bioinformatics/btz469