LD Hub: a centralized database and web interface to perform LD score regression that maximizes the potential of summary level GWAS data for SNP heritability and genetic correlation analysis

Clicks: 1
ID: 300187
2016
Free PDF
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 #704 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
Sign in to mint
Abstract
LD score regression is a reliable and efficient method of using genome-wide association study (GWAS) summary-level results data to estimate the SNP heritability of complex traits and diseases, partition this heritability into functional categories, and estimate the genetic correlation between different phenotypes. Because the method relies on summary level results data, LD score regression is computationally tractable even for very large sample sizes. However, publicly available GWAS summary-level data are typically stored in different databases and have different formats, making it difficult to apply LD score regression to estimate genetic correlations across many different traits simultaneously.
Reference Key
openalex_W2345621280 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Jie Zheng, A. Mesut Erzurumluoglu, Benjamin Elsworth, John P. Kemp, Laurence J Howe, Philip Haycock, Gibran Hemani, Katherine E. Tansey, Charles Laurin, Beaté St Pourcain, Nicole M. Warrington, Hilary K. Finucane, Alkes L. Price, Brendan Bulik‐Sullivan, Verneri Anttila, Lavinia Paternoster, Tom R. Gaunt, David M. Evans, Benjamin M. Neale
Journal BMC Bioinformatics
Year 2016
DOI
10.1093/bioinformatics/btw613
URL
https://academic.oup.com/bioinformatics/article-pdf/33/2/272/25331741/btw613.pdf
Keywords Keywords not found

Citations

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

Comments

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