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emeraLD: Rapid Linkage Disequilibrium Estimation with Massive Data Sets

By Corbin Quick, Christian Fuchsberger, Daniel Taliun, Gonçalo Abecasis, Michael Boehnke, Hyun Min Kang

Posted 15 Apr 2018
bioRxiv DOI: 10.1101/301366 (published DOI: 10.1093/bioinformatics/bty547)

Summary: Estimating 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. Availability and Implementation: emeraLD 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

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