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bioRxiv · 10.1101/301366

emeraLD: Rapid Linkage Disequilibrium Estimation with Massive Data Sets

Quick, C.·Fuchsberger, C.·Taliun, D.·Abecasis, G.·Boehnke, M.·Kang, H. M.
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Abstract

SummaryEstimating linkage disequilibrium (LD) is essential for a wide range of summary statistics-based association methods for genome-wide association studies (GWAS). Large genetic data sets, e.g. the TOPMed WGS project and UK Biobank, enable more accurate and comprehensive LD estimates, but increase the computational burden of LD estimation. Here, we describe emeraLD (Efficient Methods for Estimation and Random Access of LD), a computational tool that leverages sparsity and haplotype structure to estimate LD orders of magnitude faster than existing tools.\n\nAvailability and ImplementationemeraLD is implemented in C++, and is open source under GPLv3. Source code, documentation, an R interface, and utilities for analysis of summary statistics are freely available at http://github.com/statgen/emeraLD\n\nContactcorbinq@umich.edu\n\nSupplementary informationSupplementary data are available at Bioinformatics online.

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Quick, C., Fuchsberger, C., Taliun, D., Abecasis, G., Boehnke, M., Kang, H. M.. 2018-04-15. emeraLD: Rapid Linkage Disequilibrium Estimation with Massive Data Sets. https://doi.org/10.1101/301366

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