PhenoScanner: a database of human genotype–phenotype associations

Clicks: 1
ID: 294547
2016
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This article has not been analysed, so there is no overall score — reader engagement is measured and shown alongside.
AI Quality Assessment
Not analyzed
Readership in this journal

Ranked #706 of 829 articles by views in BMC Bioinformatics

Most read Least read

Bar heights use a square-root scale. Only the 120 most-read articles are drawn; the journal has 829 in total.

Mint this article as an NFT
Not yet minted

Create a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.

5 SUSD one-off · no wallet required
Abstract
Abstract Summary: PhenoScanner is a curated database of publicly available results from large-scale genetic association studies. This tool aims to facilitate ‘phenome scans’, the cross-referencing of genetic variants with many phenotypes, to help aid understanding of disease pathways and biology. The database currently contains over 350 million association results and over 10 million unique genetic variants, mostly single nucleotide polymorphisms. It is accompanied by a web-based tool that queries the database for associations with user-specified variants, providing results according to the same effect and non-effect alleles for each input variant. The tool provides the option of searching for trait associations with proxies of the input variants, calculated using the European samples from 1000 Genomes and Hapmap. Availability and Implementation: PhenoScanner is available at www.phenoscanner.medschl.cam.ac.uk. Contact: jrs95@medschl.cam.ac.uk Supplementary information: Supplementary data are available at Bioinformatics online.
Reference Key
openalex_W2398690791 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors James R Staley, James Blackshaw, Mihir Kamat, Ian O. Ellis, Praveen Surendran, Benjamin B. Sun, Dirk S. Paul, Daniel Freitag, Stephen Burgess, John Danesh, Robin Young, Adam S. Butterworth
Journal BMC Bioinformatics
Year 2016
DOI
10.1093/bioinformatics/btw373
URL
Keywords Keywords not found

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

No comments yet. Be the first to comment on this article.