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GREML-LDMS specifications

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Unique identifier OMICS_13778
Name GREML-LDMS
Software type Package/Module
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux
Computer skills Advanced
Stability No
Maintained No

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Publication for GREML-LDMS

GREML-LDMS in publications

 (3)
PMCID: 5847615
PMID: 29531279
DOI: 10.1038/s41598-018-21603-7

[…] from 1kgp ceu population., we estimated the heritability from the original and imputed variants within the most promising loci, using methods of estimation of variance explained by snps (greml) and greml-ldms programs implemented in the package of the genome-wide complex trait analysis (gcta)., snp identified in the current study that reached suggestive level of association (p < 5 × 10−6) […]

PMCID: 5539983
PMID: 28764638
DOI: 10.1186/s12711-017-0336-z

[…] in ld on heritability estimates is relatively small in bovine populations., recently, yang et al. [] proposed an ld- and maf-stratified genomic-relatedness-based restricted maximum-likelihood (greml-ldms) method for human data that partitions the variance explained across classes of variants with different maf. it also accounts for region-specific heterogeneity in ld []. they showed […]

PMCID: 5408227
PMID: 28452372
DOI: 10.1038/srep45040

[…] conditional p-value was genome-wide significant (p-value < 5 × 10−8) after conditioning on the previously reported variant in a locus., the heritability of egfrcrea was estimated using gcta greml-ldms methods (version 1.25) with imputed genotype accounting for linkage disequilibrium. the imputed genotype was based on dosage (probability > 0.9) imputed using the 1000 genomes phase […]

GREML-LDMS institution(s)
Queensland Brain Institute, The University of Queensland, Queensland, Australia; The University of Queensland Diamantina Institute, The Translation Research Institute, Queensland, Australia; MRC Integrative Epidemiology Unit at the University of Bristol, School of Social and Community Medicine, Bristol, UK; School of Environmental and Rural Science, The University of New England, New South Wales, Australia; MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Institute of Metabolic Science, Cambridge Biomedical Campus, Cambridge, UK; Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, Netherlands; Department of Endocrinology, University of Groningen, University Medical Center Groningen, Groningen, Netherlands; Estonian Genome Center, University of Tartu, Tartu, Estonia; Division of Endocrinology, Boston Children’s Hospital, Cambridge, MA, USA; Program in Medical and Populational Genetics, Broad Institute, Cambridge, MA, USA; Department of Genetics, Harvard Medical School, Boston, MA, USA; Institute of Molecular and Cell Biology, University of Tartu, Tartu, Estonia; Cardiovascular Genetics and Genomics Group, Atherosclerosis Research Unit, Department of Medicine Solna, Karolinska Institutet, Stockholm, Sweden; Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden; Department of Medical Sciences, Molecular Epidemiology and Science for Life Laboratory, Uppsala University, Uppsala, Sweden; Department of Medicine, Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, CA, USA; Department of Human Genetics, Wellcome Trust Sanger Institute, Genome Campus, Hinxton, UK; Department of Haematology, University of Cambridge, Long Road, Cambridge, UK; Department of Psychology and Neuroscience, University of Colorado, Boulder, CO, USA; Institute for Behavioral Genetics, University of Colorado, Boulder, CO, USA; Faculty of Veterinary and Agricultural Science, University of Melbourne, Parkville, Victoria, Australia; Biosciences Research Division, Department of Economic Development, Jobs, Transport and Resources, Bundoora, Victoria, Australia
GREML-LDMS funding source(s)
This work was supported by the Australian National Health and Medical Research Council (grants n°1052684, 1078037 and 1050218); the Australian Research Council (grant n°130102666); the National Institutes of Health (grant n°R01MH100141); the Sylvia & Charles Viertel Charitable Foundation, and the UQ Foundation.

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