emeraLD: rapid linkage disequilibrium estimation with massive datasets.
Journal
Bioinformatics (Oxford, England)
ISSN: 1367-4811
Titre abrégé: Bioinformatics
Pays: England
ID NLM: 9808944
Informations de publication
Date de publication:
01 01 2019
01 01 2019
Historique:
received:
16
04
2018
accepted:
28
06
2018
pubmed:
12
9
2018
medline:
28
10
2019
entrez:
12
9
2018
Statut:
ppublish
Résumé
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. 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 data are available at Bioinformatics online.
Identifiants
pubmed: 30204848
pii: 5047763
doi: 10.1093/bioinformatics/bty547
pmc: PMC6298049
doi:
Types de publication
Journal Article
Research Support, N.I.H., Extramural
Langues
eng
Sous-ensembles de citation
IM
Pagination
164-166Subventions
Organisme : NHGRI NIH HHS
ID : R01 HG000376
Pays : United States
Organisme : NHGRI NIH HHS
ID : T32 HG000040
Pays : United States
Organisme : NHGRI NIH HHS
ID : R56 HG000376
Pays : United States
Organisme : NHGRI NIH HHS
ID : R01 HG009976
Pays : United States
Organisme : Medical Research Council
ID : MC_QA137853
Pays : United Kingdom
Organisme : NHGRI NIH HHS
ID : U01 HG006513
Pays : United States
Organisme : NIDDK NIH HHS
ID : P30 DK020572
Pays : United States
Organisme : NHLBI NIH HHS
ID : U01 HL137182
Pays : United States
Organisme : NHGRI NIH HHS
ID : R01 HG007022
Pays : United States
Organisme : Medical Research Council
ID : MC_PC_17228
Pays : United Kingdom
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