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.
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.
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DOI：
10.1093/bioinformatics/btw613
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发表时间：
2017-01-15
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通讯作者：
Neale BM
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文献类型：
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作者：
Zheng J;Erzurumluoglu AM;Elsworth BL;Kemp JP;Howe L;Haycock PC;Hemani G;Tansey K;Laurin C;Early Genetics and Lifecourse Epidemiology (EAGLE) Eczema Consortium;Pourcain BS;Warrington NM;Finucane HK;Price AL;Bulik-Sullivan BK;Anttila V;Paternoster L;Gaunt TR;Evans DM;Neale BM
LD评分回归是一种利用全基因组关联研究（GWAS）总结水平的结果数据来估计复杂性状和疾病的SNP遗传力、将该遗传力划分为功能类别以及估计不同表型之间的遗传相关性的可靠且有效的方法。由于该方法依赖于汇总水平结果数据，因此即使对于非常大的样本量，LD评分回归在计算上也是易于处理的。然而，公开可用的GWAS摘要级数据通常存储在不同的数据库中，并且具有不同的格式，使得难以应用LD评分回归来同时估计许多不同性状的遗传相关性。在本文中，我们描述了LD Hub -一个来自不同公共资源/联盟的173种疾病/性状的汇总级GWAS结果的集中数据库，以及一个自动化LD评分回归分析管道的Web界面。为了证明功能并验证我们的软件，我们使用LD Hub复制了先前报道的49种性状/疾病的LD评分回归分析;并估计了不同表型之间的SNP遗传力和遗传相关性。我们还提出了通过上传最近的特应性皮炎GWAS荟萃分析获得的新结果，以检查条件和其他潜在相关性状之间的遗传相关性。为了应对日益增长的可公开访问的GWAS摘要级结果数据的可用性，我们的数据库和随附的网络界面将确保最大限度地利用LD评分回归方法，为GWAS结果的公开传播提供有用的数据库，并提供一种方法，用于轻松筛选重叠遗传病因的数百个性状。使用LD Hub的网络界面和说明可在http://ldsc.broadinstitute.org/获得补充数据可在Bioinformatics在线获得。
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. 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. The web interface and instructions for using LD Hub are available at http://ldsc.broadinstitute.org/ Supplementary data are available at Bioinformatics online.
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