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Protocols

LD Hub specifications

Information


Unique identifier OMICS_30001
Name LD Hub
Restrictions to use None
Community driven No
Data access Browse
User data submission Not allowed
Version 1.9.0
Registration required Yes
Maintained Yes

Maintainers


  • person_outline Jie Zheng
  • person_outline Jie Zheng

Publication for LD Hub

LD Hub citations

 (11)
library_books

Biological Insights Into Muscular Strength: Genetic Findings in the UK Biobank

2018
Sci Rep
PMCID: 5915424
PMID: 29691431
DOI: 10.1038/s41598-018-24735-y

[…] plained divided by the proportion of SNPs in each functional category. We considered FDR ≤ 0.05 to indicate statistically significant enrichments. Genetic correlation was tested against all traits in LD Hub after SNP filtering based on allele frequency, imputation quality, outliers in effect sizes, and removing SNPs in MHC region. To identify significant genetic correlations, we set the P-value th […]

library_books

Genetic validation of bipolar disorder identified by automated phenotyping using electronic health records

2018
PMCID: 5904248
PMID: 29666432
DOI: 10.1038/s41398-018-0133-7

[…] psychiatric disorder phenotypes, most notably schizophrenia (SCZ) and major depressive disorder (MDD). To examine the genetic relationship between EHR-based BD samples and related phenotypes, we used LD Hub to estimate rg with schizophrenia (SCZ), major depressive disorder (MDD), subjective well-being, and, as a negative control, mean platelet volume (MPV). Finally, we performed genome-wide Cochra […]

call_split

Local adaptation in European populations affected the genetics of psychiatric disorders and behavioral traits

2018
Genome Med
PMCID: 5870256
PMID: 29580271
DOI: 10.1186/s13073-018-0532-7
call_split See protocol

[…] ficantly different from the null distribution of the permuted results. To estimate the genetic correlation among psychiatric disorders and behavioral traits, we considered the information provided by LD Hub v1.3.1 [] (available at http://ldsc.broadinstitute.org/ldhub/) and used the LD score regression method [] for the missing pair-wise comparisons. Heritability statistics of the GWAS considered a […]

call_split

A Genome Wide Association Study Finds Genetic Associations with Broadly Defined Headache in UK Biobank (N = 223,773)

2018
PMCID: 5898025
PMID: 29397368
DOI: 10.1016/j.ebiom.2018.01.023
call_split See protocol

[…] extra information to visualize and interpret GWAS results.In order to identify genetic correlations between headache and other complex traits, we used linkage disequilibrium score regression through LD Hub v1.4.1 (available at http://ldsc.broadinstitute.org/ldhub/) (). This web-tool uses individual SNP allele effect sizes and the average linkage disequilibrium in a region to estimate the bivariat […]

library_books

GWAS of epigenetic aging rates in blood reveals a critical role for TERT

2018
Nat Commun
PMCID: 5786029
PMID: 29374233
DOI: 10.1038/s41467-017-02697-5

[…] pt–h2 and –intercept-gencov flags. Toward this end, we used the heritability analysis of the LDSC regression to estimate intercept terms. Additional genetic correlation analysis was performed via the LD Hub software tool that allowed us to analyze 233 traits. The built-in LDSC platform automatically removed all variants in the MHC region on chromosome 6 (26–34 MB). […]

library_books

Genome wide meta analyses of stratified depression in Generation UK and UK Biobank

2018
PMCID: 5802463
PMID: 29317602
DOI: 10.1038/s41398-017-0034-1

[…] REML and LDSC are given in Supplementary Table . Genetic correlations between meta-analyzed depression subgroups and 200 health-related traits were calculated using bivariate LDSR, implemented in the LD Hub software. Traits derived from non-Caucasian or mixed ethnicity samples were removed prior to analysis. False discovery rate (FDR) correction was applied across the 800 tests to correct for mult […]

Citations

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LD Hub institution(s)
MRC Integrative Epidemiology Unit, University of Bristol, Oakfield House, Bristol, UK; Genetic Epidemiology Group, Department of Health Sciences, University of Leicester, Leicester, UK; University of Queensland Diamantina Institute, Translational Research Institute, Brisbane, QLD, Australia; Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA; Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA; Analytical and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
LD Hub funding source(s)
Supported by the Medical Research Council (MC_UU_12013/4 and MC_UU_12013/8), an Australian Research Council Future Fellowship (FT130101709), a Cancer Research UK programme grant number C18281/A19169 (the Integrative Cancer Epidemiology Programme), a Cancer Research UK Population Research Fellow (grant number C52724/A20138) and the following grants: 1R01MH101244-02 (Statistical methods for studies of rare variants) and 1R01MH107649-01 (Methods for linking GWAS peaks to function in psychiatric disease).

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