Year: 2018
Type: article
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.
Source: Bioinformatics
Language: English
Subfield: Genetics
Domain: Life Sciences
Open Access status: green
Awards: Design and Analysis of Human Gene Mapping Studies, Scalable and Translational Analysis Tools on the Cloud for Deep Integrative Omics Data, Design and Analysis of Human Gene Mapping Studies, Robust Software Tools for Variant Identification and Functional Assessment, G5850737185, Computational and statistical models for human genetics, Design and Analysis of Human Gene Mapping Studies, G9000090537, University of Michigan Training Program in Genomic Science, Michigan Diabetes Research Center (MDRC)
OpenAlex ID: W2949751780