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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

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 be...

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Autores principales: Zheng, Jie, Erzurumluoglu, A Mesut, Elsworth, Benjamin L, Kemp, John P, Howe, Laurence, Haycock, Philip C, Hemani, Gibran, Tansey, Katherine, Laurin, Charles, Pourcain, Beate St, Warrington, Nicole M, Finucane, Hilary K, Price, Alkes L, Bulik-Sullivan, Brendan K, Anttila, Verneri, Paternoster, Lavinia, Gaunt, Tom R, Evans, David M, Neale, Benjamin M
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5542030/
https://www.ncbi.nlm.nih.gov/pubmed/27663502
http://dx.doi.org/10.1093/bioinformatics/btw613
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author Zheng, Jie
Erzurumluoglu, A Mesut
Elsworth, Benjamin L
Kemp, John P
Howe, Laurence
Haycock, Philip C
Hemani, Gibran
Tansey, Katherine
Laurin, Charles
Pourcain, Beate St
Warrington, Nicole M
Finucane, Hilary K
Price, Alkes L
Bulik-Sullivan, Brendan K
Anttila, Verneri
Paternoster, Lavinia
Gaunt, Tom R
Evans, David M
Neale, Benjamin M
author_facet Zheng, Jie
Erzurumluoglu, A Mesut
Elsworth, Benjamin L
Kemp, John P
Howe, Laurence
Haycock, Philip C
Hemani, Gibran
Tansey, Katherine
Laurin, Charles
Pourcain, Beate St
Warrington, Nicole M
Finucane, Hilary K
Price, Alkes L
Bulik-Sullivan, Brendan K
Anttila, Verneri
Paternoster, Lavinia
Gaunt, Tom R
Evans, David M
Neale, Benjamin M
author_sort Zheng, Jie
collection PubMed
description 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/ SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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spelling pubmed-55420302017-08-03 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 Zheng, Jie Erzurumluoglu, A Mesut Elsworth, Benjamin L Kemp, John P Howe, Laurence Haycock, Philip C Hemani, Gibran Tansey, Katherine Laurin, Charles Pourcain, Beate St Warrington, Nicole M Finucane, Hilary K Price, Alkes L Bulik-Sullivan, Brendan K Anttila, Verneri Paternoster, Lavinia Gaunt, Tom R Evans, David M Neale, Benjamin M Bioinformatics Original Papers 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/ SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Oxford University Press 2017-01-15 2016-09-22 /pmc/articles/PMC5542030/ /pubmed/27663502 http://dx.doi.org/10.1093/bioinformatics/btw613 Text en © The Author 2016. Published by Oxford University Press. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Papers
Zheng, Jie
Erzurumluoglu, A Mesut
Elsworth, Benjamin L
Kemp, John P
Howe, Laurence
Haycock, Philip C
Hemani, Gibran
Tansey, Katherine
Laurin, Charles
Pourcain, Beate St
Warrington, Nicole M
Finucane, Hilary K
Price, Alkes L
Bulik-Sullivan, Brendan K
Anttila, Verneri
Paternoster, Lavinia
Gaunt, Tom R
Evans, David M
Neale, Benjamin M
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
title 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
title_full 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
title_fullStr 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
title_full_unstemmed 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
title_short 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
title_sort 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
topic Original Papers
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5542030/
https://www.ncbi.nlm.nih.gov/pubmed/27663502
http://dx.doi.org/10.1093/bioinformatics/btw613
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