Dataset Information

EmeraLD: rapid linkage disequilibrium estimation with massive datasets.

ABSTRACT:

Summary

Estimating linkage disequilibrium (LD) is essential for a wide range of summary statistics-based association methods for genome-wide association studies. Large genetic datasets, 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 up to 2 orders of magnitude faster than current tools.

Availability and implementation

emeraLD is implemented in C++, and is open source under GPLv3. Source code and documentation are freely available at http://github.com/statgen/emeraLD.

Supplementary information

Supplementary data are available at Bioinformatics online.

SUBMITTER: Quick C

PROVIDER: S-EPMC6298049 | biostudies-literature | 2019 Jan

REPOSITORIES: biostudies-literature

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Publications

emeraLD: rapid linkage disequilibrium estimation with massive datasets.

Quick Corbin C Fuchsberger Christian C Taliun Daniel D Abecasis Gonçalo G Boehnke Michael M Kang Hyun Min HM

Bioinformatics (Oxford, England) 20190101 1

<h4>Summary</h4>Estimating linkage disequilibrium (LD) is essential for a wide range of summary statistics-based association methods for genome-wide association studies. Large genetic datasets, 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 structur ...[more]

PMID: 30204848

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Project description:BackgroundGenomic technologies, such as high-throughput genotyping based on SNP arrays, have great potential to decipher the genetic architecture of complex traits and provide background information concerning genome structure in domestic animals, including the extent of linkage disequilibrium (LD) and haplotype blocks. The objective of this study was to estimate LD, the population evolution (past effective population size) and the level of inbreeding in Spanish Churra sheep.ResultsA total of 43,784 SNPs distributed in the ovine autosomal genome was analyzed in 1,681 Churra ewes. LD was assessed by measuring r2 between all pairs of loci. For SNPs up to 10 ?kb apart, the average r2 was 0.329; for SNPs separated by 200-500? kb the average r2 was 0.061. When SNPs are separated by more than 50 Mbp, the average r2 is the same as between non-syntenic SNP pairs (0.003). The effective population size has decreased through time, faster from 1,000 to 100 ?years ago and slower since the selection scheme started (15-25 generations ago). In the last generation, four years ago, the effective population size was estimated to be 128 animals. Inbreeding coefficients, although differed depending on the estimation approaches, were generally low and showed the same trend, which indicates that since 2003, inbreeding has been slightly increasing in the studied resource population.ConclusionsThe extent of LD in Churra sheep persists over much more limited distances than reported in dairy cattle and seems to be similar to other ovine populations. Churra sheep show a wide genetic base, with a long-term viable effective population size that has been slightly decreasing since selection scheme began in 1986. The genomic dataset analyzed provided useful information for identifying low-level inbreeding in the sample, whereas based on the parameters reported here, a higher marker density than that analyzed here will be needed to successfully conduct accurate mapping of genes underlying production traits and genomic selection prediction in this sheep breed. Although the Ovine Assembly development is still in a draft stage and future refinements will provide a more accurate physical map that will improve LD estimations, this work is a first step towards the understanding of the genetic architecture in sheep.