Dataset Information

Using Fisher's method with PLINK 'LD clumped' output to compare SNP effects across Genome-wide Association Study (GWAS) datasets.

ABSTRACT:

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As the number of publically available GWAS datasets continues to grow, bioinformatic tools which enable routine manipulation of data are becoming increasingly useful. Meta-analysis using multiple GWAS datasets has become essential to elucidate novel SNP associations which may not be readily discovered in each GWAS individually due to insufficient power. Replication of GWAS findings is critical and is the 'arbiter' of genuine SNP associations. We have developed an 'LD aware' bioinformatics application which allows efficient comparison of SNP effects across multiple GWAS datasets using Fisher's combined probability test from PLINK (v1.06) 'LD clumped' output.

Availability

the application is freely available from the authors.

SUBMITTER: Shi H

PROVIDER: S-EPMC3077236 | biostudies-literature | 2011 Jan

REPOSITORIES: biostudies-literature

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Publications

Using Fisher's method with PLINK 'LD clumped' output to compare SNP effects across Genome-wide Association Study (GWAS) datasets.

Shi Hui H Medway Christopher C Brown Kristelle K Kalsheker Noor N Morgan Kevin K

International journal of molecular epidemiology and genetics 20101125 1

<h4>Unlabelled</h4>As the number of publically available GWAS datasets continues to grow, bioinformatic tools which enable routine manipulation of data are becoming increasingly useful. Meta-analysis using multiple GWAS datasets has become essential to elucidate novel SNP associations which may not be readily discovered in each GWAS individually due to insufficient power. Replication of GWAS findings is critical and is the 'arbiter' of genuine SNP associations. We have developed an 'LD aware' bi ...[more]

PMID: 21537399

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Project description:MotivationLD 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.ResultsIn 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 implementationThe 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.

Dataset Information

Using Fisher's method with PLINK 'LD clumped' output to compare SNP effects across Genome-wide Association Study (GWAS) datasets.

Unlabelled

Availability

Publications

Using Fisher's method with PLINK 'LD clumped' output to compare SNP effects across Genome-wide Association Study (GWAS) datasets.

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