Zheng, J.* ; Erzurumluoglu, A.M.* ; Elsworth, B.L.* ; Kemp, J.P.* ; Howe, L.* ; Haycock, P.C.* ; Hemani, G.* ; Tansey, K.* ; Laurin, C.* ; St. Pourcain, B.* ; Warrington, N.M.* ; Finucane, H.K.* ; Price, A.L.* ; Bulik-Sullivan, B.* ; Anttila, V.* ; Paternoster, L.* ; Gaunt, T.R.* ; Evans, D.M* ; Neale, B.M.* ; EUMODIC Consortium (Heinrich, J.)
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.
Bioinformatics 33, 272-279 (2017)
MOTIVATION: 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. RESULTS: In this manuscript, we describe LD Hub - a centralized database of summary-level GWAS results for 173 diseases/traits from different publicly available resources/consortia and a web interface that automates the LD score regression analysis pipeline. To demonstrate functionality and validate our software, we replicated previously reported LD score regression analyses of 49 traits/diseases using LD Hub; and estimated SNP heritability and the genetic correlation across the different phenotypes. We also present new results obtained by uploading a recent atopic dermatitis GWAS meta-analysis to examine the genetic correlation between the condition and other potentially related traits. In response to the growing availability of publicly accessible GWAS summary-level results data, our database and the accompanying web interface will ensure maximal uptake of the LD score regression methodology, provide a useful database for the public dissemination of GWAS results, and provide a method for easily screening hundreds of traits for overlapping genetic aetiologies. AVAILABILITY AND IMPLEMENTATION: The web interface and instructions for using LD Hub are available at http://ldsc.broadinstitute.org/ CONTACT: jie.zheng@bristol.ac.ukSupplementary information: Supplementary data are available at Bioinformatics online.
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Publikationstyp
Artikel: Journalartikel
Dokumenttyp
Wissenschaftlicher Artikel
Typ der Hochschulschrift
Herausgeber
Schlagwörter
Keywords plus
Sprache
Veröffentlichungsjahr
2017
Prepublished im Jahr
2016
HGF-Berichtsjahr
2016
ISSN (print) / ISBN
e-ISSN
1367-4811
ISBN
Bandtitel
Konferenztitel
Konferzenzdatum
Konferenzort
Konferenzband
Quellenangaben
Band: 33,
Heft: 2,
Seiten: 272-279
Artikelnummer: ,
Supplement: ,
Reihe
Verlag
Oxford University Press
Verlagsort
Oxford
Tag d. mündl. Prüfung
0000-00-00
Betreuer
Gutachter
Prüfer
Topic
Hochschule
Hochschulort
Fakultät
Veröffentlichungsdatum
0000-00-00
Anmeldedatum
0000-00-00
Anmelder/Inhaber
weitere Inhaber
Anmeldeland
Priorität
Begutachtungsstatus
Peer reviewed
Institut(e)
Institute of Epidemiology (EPI)
POF Topic(s)
30503 - Chronic Diseases of the Lung and Allergies
80000 - German Center for Lung Research
Forschungsfeld(er)
Genetics and Epidemiology
Lung Research
PSP-Element(e)
G-503900-001
G-501800-392
Förderungen
Copyright
Erfassungsdatum
2016-12-31