LDlink: a web-based application for exploring population-specific haplotype structure and linking correlated alleles of possible functional variants
Open accessAbstract
UNLABELLED: Assessing linkage disequilibrium (LD) across ancestral populations is a powerful approach for investigating population-specific genetic structure as well as functionally mapping regions of disease susceptibility. Here, we present LDlink, a web-based collection of bioinformatic modules that query single nucleotide polymorphisms (SNPs) in population groups of interest to generate haplotype tables and interactive plots. Modules are designed with an emphasis on ease of use, query flexibility, and interactive visualization of results. Phase 3 haplotype data from the 1000 Genomes Project are referenced for calculating pairwise metrics of LD, searching for proxies in high LD, and enumerating all observed haplotypes. LDlink is tailored for investigators interested in mapping common and uncommon disease susceptibility loci by focusing on output linking correlated alleles and highlighting putative functional variants. AVAILABILITY AND IMPLEMENTATION: LDlink is a free and publically available web tool which can be accessed at http://analysistools.nci.nih.gov/LDlink/. CONTACT: mitchell.machiela@nih.gov.
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The two HFE SNPs are in low linkage disequilibrium (LD r2 < 0.01) in combined European populations.
“The two SNPs in the HFE gene were in low linkage disequilibrium (LD r2 < 0.01) when considering combined European populations with the LDlink resource [2,17].”
From Associations of genetically determined iron status across the phenome: A mendelian randomization study (2019) · cites this paper as [17]
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Cites
Haploview: analysis and visualization of LD and haplotype maps
Barrett, J., Fry, B., Maller, J., & Daly, M. (2005) · Bioinform. · doi:10.1093/bioinformatics/bth457 · Cited by 15,086 · see citing works
An integrated map of genetic variation from 1,092 human genomes
The 1000 Genomes Project Consortium (2012) · Nature · doi:10.1038/nature11632 · Cited by 7,711 · see citing works
Annotation of functional variation in personal genomes using RegulomeDB
Boyle, A. P., Hong, E. L., Hariharan, M., Cheng, Y., Schaub, M. A., Kasowski, M., Karczewski, K. J., Park, J., Hitz, B. C., Weng, S., et al. (2012) · Genome Research · doi:10.1101/gr.137323.112 · Cited by 2,722 · see citing works
The NHGRI GWAS Catalog, a curated resource of SNP-trait associations
Welter, D., MacArthur, J., Morales, J., Burdett, T., Hall, P., Junkins, H., Klemm, A., Flicek, P., Manolio, T., Hindorff, L., et al. (2014) · Nucleic Acids Research · doi:10.1093/nar/gkt1229 · Cited by 2,707 · see citing works
Stewart, B. W., & Kleihues, P. (2003) · Cited by 2,389 · see citing works
SNAP: a web-based tool for identification and annotation of proxy SNPs using HapMap
Johnson, A. D., Handsaker, R., Pulit, S., Nizzari, M. M., O'Donnell, C., & de Bakker, P. D. (2008) · Bioinform. · doi:10.1093/bioinformatics/btn564 · Cited by 1,530 · see citing works
Tabix: fast retrieval of sequence features from generic TAB-delimited files
Li, H. (2011) · Bioinformatics · doi:10.1093/bioinformatics/btq671 · Cited by 575 · see citing works
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Alzheimer Disease Genetics Consortium (ADGC), Kunkle, B. W., The European Alzheimer’s Disease Initiative (EADI), Cohorts for Heart and Aging Research in Genomic Epidemiology Consortium (CHARGE), Genetic and Environmental Risk in AD/Defining Genetic, P. A. E. R. F. A. D. C. (., Grenier-Boley, B., Sims, R., Bis, J. C., Damotte, V., Naj, A. C., et al. (2019) · Nature Genetics · doi:10.1038/s41588-019-0358-2 · Cited by 2,946 · see citing works
Large-scale association analyses identify host factors influencing human gut microbiome composition
Kurilshikov, A., Medina-Gomez, C., Bacigalupe, R., Radjabzadeh, D., Wang, J., Demirkan, A., Le Roy, C. I., Raygoza Garay, J. A., Finnicum, C. T., Liu, X., et al. (2021) · Nature Genetics · doi:10.1038/s41588-020-00763-1 · Cited by 1,786 · see citing works
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Graham, S. E., Clarke, S. L., Wu, K.-H. H., Kanoni, S., Zajac, G. J. M., Ramdas, S., Surakka, I., Ntalla, I., Vedantam, S., Winkler, T. W., et al. (2021) · Nature · doi:10.1038/s41586-021-04064-3 · Cited by 972 · see citing works
“We considered variants to be independent if they were outside this region, had LD R 2 0.7 or were not available in the LDpair reference populations.”
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Corces, M. R., Shcherbina, A., Kundu, S., Gloudemans, M. J., Frésard, L., Granja, J. M., Louie, B. H., Eulalio, T., Shams, S., Bagdatli, S. T., et al. (2020) · Nature Genetics · doi:10.1038/s41588-020-00721-x · Cited by 358 · see citing works
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Dapas, M., & Dunaif, A. (2022) · Endocrine Reviews · doi:10.1210/endrev/bnac001 · Cited by 300 · see citing works
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Perry, B. I., Upthegrove, R., Kappelmann, N., Jones, P. B., Burgess, S., & Khandaker, G. M. (2021) · Brain, Behavior, and Immunity · doi:10.1016/j.bbi.2021.07.009 · Cited by 187 · see citing works
Walker, K. A., Chen, J., Shi, L., Yang, Y., Fornage, M., Zhou, L., Schlosser, P., Surapaneni, A., Grams, M. E., Duggan, M. R., et al. (2023) · Science Translational Medicine · doi:10.1126/scitranslmed.adf5681 · Cited by 148 · see citing works
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Huang, S.-Y., Yang, Y.-X., Kuo, K., Li, H.-Q., Shen, X.-N., Chen, S.-D., Cui, M., Tan, L., Dong, Q., & Yu, J.-T. (2021) · Alzheimer's Research & Therapy · doi:10.1186/s13195-021-00905-5 · Cited by 82 · see citing works
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McArthur, E., Rinker, D. C., & Capra, J. A. (2021) · Nature Communications · doi:10.1038/s41467-021-24582-y · Cited by 71 · see citing works
Gill, D., Benyamin, B., Moore, L. S. P., Monori, G., Zhou, A., Koskeridis, F., Evangelou, E., Laffan, M., Walker, A. P., Tsilidis, K. K., et al. (2019) · PLOS Medicine · doi:10.1371/journal.pmed.1002833 · Cited by 63 · see citing works
Costas, J. (2018) · American Journal of Medical Genetics Part B: Neuropsychiatric Genetics · doi:10.1002/ajmg.b.32545 · Cited by 58 · see citing works
Fang, S., Yarmolinsky, J., Gill, D., Bull, C. J., Perks, C. M., the PRACTICAL Consortium, Davey Smith, G., Gaunt, T. R., & Richardson, T. G. (2023) · PLOS Medicine · doi:10.1371/journal.pmed.1003988 · Cited by 55 · see citing works
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Ciuculete, D. M., Boström, A. E., Voisin, S., Philipps, H., Titova, O. E., Bandstein, M., Nikontovic, L., Williams, M. J., Mwinyi, J., & Schiöth, H. B. (2017) · Translational Psychiatry · doi:10.1038/tp.2016.275 · Cited by 40 · see citing works
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Wallen, Z. D., Stone, W. J., Factor, S. A., Molho, E., Zabetian, C. P., Standaert, D. G., & Payami, H. (2021) · npj Parkinson s Disease · doi:10.1038/s41531-021-00218-2 · Cited by 41 · see citing works
Sun, H., Gao, X., Que, X., Liu, L., Ma, J., He, S., Gao, Q., & Wang, T. (2020) · Journal of Affective Disorders · doi:10.1016/j.jad.2019.11.034 · Cited by 33 · see citing works
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Pillai, J. A., Bebek, G., Khrestian, M., Bena, J., Bergmann, C. C., Bush, W. S., Leverenz, J. B., & Bekris, L. M. (2021) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2021.638922 · Cited by 29 · see citing works
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Alexander, J., Potamianou, H., Xing, J., Deng, L., Karagiannidis, I., Tsetsos, F., Drineas, P., Tarnok, Z., Rizzo, R., Wolanczyk, T., et al. (2016) · Frontiers in Neuroscience · doi:10.3389/fnins.2016.00428 · Cited by 27 · see citing works
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Zhang, X., Deng, H., Shen, H., & Ehrlich, M. (2021) · JBMR Plus · doi:10.1002/jbm4.10481 · Cited by 20 · see citing works
Zajac, D. J., Simpson, J., Zhang, E., Parikh, I., & Estus, S. (2023) · Genes · doi:10.3390/genes14030763 · Cited by 18 · see citing works
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van Weerd, J. H., Mohan, R. A., van Duijvenboden, K., Hooijkaas, I. B., Wakker, V., Boukens, B. J., Barnett, P., & Christoffels, V. M. (2020) · eLife · doi:10.7554/elife.56697 · Cited by 12 · see citing works
Strunz, T., Pöllmann, M., Gamulescu, M.-A., Tamm, S., & Weber, B. H. F. (2022) · International Journal of Molecular Sciences · doi:10.3390/ijms23116094 · Cited by 10 · see citing works
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Pauly, R., Johnson, L., Feltus, F. A., & Casanova, E. L. (2024) · Molecular Psychiatry · doi:10.1038/s41380-024-02593-7 · Cited by 7 · see citing works
A genetic and proteomic comparison of key AD biomarkers across tissues
Marsh, T. W., Western, D., Timsina, J., Gorijala, P., Yang, C., Pastor, P., Liu, M., Morris, J. C., Bateman, R. J., Schindler, S. E., et al. (2024) · Alzheimer's & Dementia · doi:10.1002/alz.14139 · Cited by 6 · see citing works
Western, D., Yang, C., Timsina, J., Liu, M., Wang, C., Campbell, M. C., Kotzbauer, P., Perlmutter, J. S., Schindler, S. E., Morris, J. C., et al. (2026) · Science Translational Medicine · doi:10.1126/scitranslmed.adz2016 · Cited by 1 · see citing works
- Authors
- Machiela, M. J., & Chanock, S. J.
- Affiliations
- Division of Cancer Epidemiology and Genetics (US)
- Corresponding author
- Machiela, Mitchell J.
- Venue
- Bioinformatics
- Publisher
- Oxford University Press (OUP)
- Published
- 2015-07-02
- Volume
- 31
- Issue
- 21
- Pages
- 3555-3557
- ISSN
- 1367-4803 (ISSN-L)
- 1367-4811
- PMC
- PMC4626747
- OpenAlex
- W2166320441
- Cited by
- 2,069
- References
- 7
- Citations by year
- 2026: 156 · 2025: 236 · 2024: 346 · 2023: 244 · 2022: 235 · 2021: 278 · 2020: 210 · 2019: 155 · 2018: 104 · 2017: 75 · 2016: 26 · 2015: 2 · 2014: 1
- FWCI
- 47.43
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Licence
- public-domain
- Locations
- Bioinformatics (publishedVersion, public-domain)
- Europe PMC (PubMed Central) (publishedVersion, public-domain)
- PubMed Central (publishedVersion, public-domain)
- PubMed (publishedVersion)
- HighWire Press Open Archive (submittedVersion)
- Funders
- National Institutes of Health
- National Cancer Institute
- Center for Biomedical Informatics and Information Technology, National Cancer Institute
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Forensic and Genetic Research
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Mapping and Diversity in Plants and Animals
- Keywords
- linkage disequilibrium, haplotype structure, single nucleotide polymorphisms, 1000 Genomes Project, disease susceptibility loci, functional variants, web-based bioinformatics tool, interactive visualization
- MeSH terms
- Alleles, Chromosome Mapping, Haplotypes, Humans, Software, Linkage Disequilibrium, Genetic Predisposition to Disease, Internet, Polymorphism, Single Nucleotide, Population Groups
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