TOP-LD: A tool to explore linkage disequilibrium with TOPMed whole-genome sequence data
Open accessAbstract
Current publicly available tools that allow rapid exploration of linkage disequilibrium (LD) between markers (e.g., HaploReg and LDlink) are based on whole-genome sequence (WGS) data from 2,504 individuals in the 1000 Genomes Project. Here, we present TOP-LD, an online tool to explore LD inferred with high-coverage (∼30×) WGS data from 15,578 individuals in the NHLBI Trans-Omics for Precision Medicine (TOPMed) program. TOP-LD provides a significant upgrade compared to current LD tools, as the TOPMed WGS data provide a more comprehensive representation of genetic variation than the 1000 Genomes data, particularly for rare variants and in the specific populations that we analyzed. For example, TOP-LD encompasses LD information for 150.3, 62.2, and 36.7 million variants for European, African, and East Asian ancestral samples, respectively, offering 2.6- to 9.1-fold increase in variant coverage compared to HaploReg 4.0 or LDlink. In addition, TOP-LD includes tens of thousands of structural variants (SVs). We demonstrate the value of TOP-LD in fine-mapping at the GGT1 locus associated with gamma glutamyltransferase in the African ancestry participants in UK Biobank. Beyond fine-mapping, TOP-LD can facilitate a wide range of applications that are based on summary statistics and estimates of LD. TOP-LD is freely available online.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The index variant rs7481951 was not available in FUMA and was replaced by rs10833712, its best tag variant (r2 = 0.827) according to TopLD.
“The index variant rs7481951 was not available in FUMA and was replaced by rs10833712, its best tag variant (r2 = 0.827) according to TopLD45.”
From Consensus meta-analysis of genome-wide association studies for Alzheimer’s disease and related dementias (2026) · cites this paper as [45]
The Main text (page not available) describes TOP-LD as a tool that reports LD proxies and their R² values, supporting its identification as the tool used. It does not report either rs7481951 or rs10833712, their alleged R² of 0.827, or whether the index variant was unavailable in FUMA. (LLM, conf=0.84)
Experimental — accuracy not yet measured
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
A global reference for human genetic variation
The 1000 Genomes Project Consortium, authors, C., Auton, A., Abecasis, G. R., Steering committee, Altshuler, D. M., Durbin, R. M., Abecasis, G. R., Bentley, D. R., Chakravarti, A., et al. (2015) · Nature · doi:10.1038/nature15393 · Cited by 18,247 · see citing works
Self-citationIntegrating common and rare genetic variation in diverse human populations
The International HapMap 3 Consortium (2010) · Nature · doi:10.1038/nature09298 · Cited by 3,026 · see citing works
Variance component model to account for sample structure in genome-wide association studies
Kang, H. M., Sul, J. H., Service, S. K., Zaitlen, N. A., Kong, S.-Y., Freimer, N. B., Sabatti, C., & Eskin, E. (2010) · Nature Genetics · doi:10.1038/ng.548 · Cited by 2,817 · see citing works
Expanded encyclopaedias of DNA elements in the human and mouse genomes
The ENCODE Project Consortium, Abascal, F., Acosta, R., Addleman, N. J., Adrian, J., Afzal, V., Ai, R., Aken, B., Akiyama, J. A., Jammal, O. A., et al. (2020) · Nature · doi:10.1038/s41586-020-2493-4 · Cited by 2,378 · see citing works
Self-citationSequencing of 53,831 diverse genomes from the NHLBI TOPMed Program
Taliun, D., Harris, D. N., Kessler, M. D., Carlson, J., Szpiech, Z. A., Torres, R., Taliun, S. A. G., Corvelo, A., Gogarten, S. M., Kang, H. M., et al. (2021) · Nature · doi:10.1038/s41586-021-03205-y · Cited by 2,213 · see citing works
Self-citationThe new NHGRI-EBI Catalog of published genome-wide association studies (GWAS Catalog)
MacArthur, J., Bowler, E., Cerezo, M., Gil, L., Hall, P., Hastings, E., Junkins, H., McMahon, A., Milano, A., Morales, J., et al. (2017) · Nucleic Acids Research · doi:10.1093/nar/gkw1133 · Cited by 2,161 · see citing works
Machiela, M. J., & Chanock, S. J. (2015) · Bioinformatics · doi:10.1093/bioinformatics/btv402 · Cited by 2,069 · see citing works
Reference-based phasing using the Haplotype Reference Consortium panel
Loh, P.-R., Danecek, P., Palamara, P. F., Fuchsberger, C., A Reshef, Y., K Finucane, H., Schoenherr, S., Forer, L., McCarthy, S., Abecasis, G. R., et al. (2016) · Nature Genetics · doi:10.1038/ng.3679 · Cited by 1,894 · see citing works
Linkage disequilibrium--understanding the evolutionary past and mapping the medical future.
Slatkin, M. (2008) · Nature Reviews Genetics · doi:10.1038/nrg2361 · Cited by 1,614 · cited 1× · see citing works
“Patterns of LD between genetic markers can be leveraged to gain insights in a variety of different applications, from population genetic research to disease association studies.(1,2) With the growth of whole-genome sequencing (WGS) and high-throughput array and genotype imputation technologies, resources for calculati…”
BackgroundChapter 11: Genome-wide association studies
Bush, W. S., & Moore, J. H. (2012) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1002822 · Cited by 1,171 · see citing works
Ward, L. D., & Kellis, M. (2015) · Nucleic Acids Research · doi:10.1093/nar/gkv1340 · Cited by 925 · see citing works
RFMix: A Discriminative Modeling Approach for Rapid and Robust Local-Ancestry Inference
Maples, B. K., Gravel, S., Kenny, E. E., & Bustamante, C. D. (2013) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2013.06.020 · Cited by 900 · see citing works
Self-citationFINEMAP: efficient variable selection using summary data from genome-wide association studies
Benner, C., Spencer, C. C. A., Havulinna, A. S., Salomaa, V., Ripatti, S., & Pirinen, M. (2016) · Bioinformatics · doi:10.1093/bioinformatics/btw018 · Cited by 815 · see citing works
AnnotSV: an integrated tool for structural variations annotation
Geoffroy, V., Herenger, Y., Kress, A., Stoetzel, C., Piton, A., Dollfus, H., & Muller, J. (2018) · Bioinformatics · doi:10.1093/bioinformatics/bty304 · Cited by 476 · see citing works
Model-free Estimation of Recent Genetic Relatedness
Conomos, M. P., Reiner, A. P., Weir, B. S., & Thornton, T. A. (2016) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2015.11.022 · Cited by 397 · see citing works
Self-citationHigh-depth African genomes inform human migration and health
Choudhury, A., Aron, S., Botigué, L. R., Sengupta, D., Botha, G., Bensellak, T., Wells, G., Kumuthini, J., Shriner, D., Fakim, Y. J., et al. (2020) · Nature · doi:10.1038/s41586-020-2859-7 · Cited by 355 · see citing works
Self-citationWGSA: an annotation pipeline for human genome sequencing studies
Liu, X., White, S. J., Peng, B., Johnson, A. D., Brody, J. A., Li, A. H., Huang, Z., Carroll, A. W., Wei, P., Gibbs, R. A., et al. (2015) · Journal of Medical Genetics · doi:10.1136/jmedgenet-2015-103423 · Cited by 119 · see citing works
Self-citationGenetic analysis in European ancestry individuals identifies 517 loci associated with liver enzymes
Pazoki, R., Vujković, M., Elliott, J., Εvangelou, Ε., Gill, D., Ghanbari, M., van der Most, P. J., Pinto, R. C., Wielscher, M., Farlik, M., et al. (2021) · Nature Communications · doi:10.1038/s41467-021-22338-2 · Cited by 115 · see citing works
Sun, Q., Graff, M., Rowland, B., Wen, J., Huang, L., Miller‐Fleming, T. W., Haessler, J., Preuss, M. H., Chai, J. F., Lee, M. P., et al. (2021) · Journal of Human Genetics · doi:10.1038/s10038-021-00968-0 · Cited by 53 · see citing works
Self-citationMikhaylova, A. V., McHugh, C., Polfus, L. M., Raffield, L. M., Boorgula, M. P., Blackwell, T. W., Brody, J. A., Broome, J., Chami, N., Chen, M., et al. (2021) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2021.08.007 · Cited by 25 · see citing works
Self-citationWheeler, M. M., Stilp, A. M., Rao, S., Halldórsson, B. V., Beyter, D., Wen, J., Mikhaylova, A. V., McHugh, C., Lane, J., Jiang, M.-Z., et al. (2022) · Nature Communications · doi:10.1038/s41467-022-35354-7 · Cited by 21 · see citing works
Self-citationRaffield, L. M., Iyengar, A. K., Wang, B., Gaynor, S. M., Spracklen, C. N., Zhong, X. Y., Kowalski, M. H., Salimi, S., Polfus, L. M., Benjamin, E. J., et al. (2019) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2019.12.002 · Cited by 12 · see citing works
Self-citationWheeler, M. M., Stilp, A. M., Rao, S., Halldórsson, B. V., Beyter, D., Wen, J., Mikhaylova, A. V., McHugh, C., Lane, J., Jiang, M.-Z., et al. (2021) · medRxiv · doi:10.1101/2021.12.16.21267871 · Cited by 5 · see citing works
Self-citation
Flagged first, then by citations
Cited by
Sorted by citations
Leveraging base-pair mammalian constraint to understand genetic variation and human disease
Sullivan, P. F., Meadows, J. R. S., Gazal, S., Phan, B. N., Li, X., Genereux, D. P., Dong, M. X., Bianchi, M., Andrews, G., Sakthikumar, S., et al. (2023) · Science · doi:10.1126/science.abn2937 · Cited by 110 · see citing works
Self-citationMolecular and genetic insights into human ovarian aging from single-nuclei multi-omics analyses
Jin, C., Wang, X., Yang, J., Kim, S.-S., Hudgins, A. D., Gamliel, A., Pei, M., Contreras, D., Devos, M., Guo, Q., et al. (2024) · Nature Aging · doi:10.1038/s43587-024-00762-5 · Cited by 107 · see citing works
Eye-brain connections revealed by multimodal retinal and brain imaging genetics
Zhao, B., Li, Y., Fan, Z., Wu, Z., Shu, J., Yang, X., Yang, Y., Wang, X., Li, B., Wang, X., et al. (2024) · Nature Communications · doi:10.1038/s41467-024-50309-w · Cited by 90 · see citing works
Self-citationWainberg, M., Andrews, S. J., & Tripathy, S. J. (2023) · Alzheimer s Research & Therapy · doi:10.1186/s13195-023-01244-3 · Cited by 82 · see citing works
Functional characterization of Alzheimer’s disease genetic variants in microglia
Yang, X., Wen, J., Yang, H., Jones, I. R., Zhu, X., Liu, W., Li, B., Clelland, C. D., Luo, W., Wong, M. Y., et al. (2023) · Nature Genetics · doi:10.1038/s41588-023-01506-8 · Cited by 71 · see citing works
Self-citationGenetic Variants Associated With Hidradenitis Suppurativa
Sun, Q., Broadaway, K. A., Edmiston, S. N., Fajgenbaum, K., Miller‐Fleming, T. W., Westerkam, L., Melendez-Gonzalez, M. D. M., Bui, H., Blum, F. R., Levitt, B. E., et al. (2023) · JAMA Dermatology · doi:10.1001/jamadermatol.2023.2217 · Cited by 71 · see citing works
Self-citationSun, Q., Rowland, B., Chen, J. C., Mikhaylova, A. V., Avery, C. L., Peters, U., Lundin, J. I., Matise, T. C., Buyske, S. G., Tao, R., et al. (2024) · Nature Communications · doi:10.1038/s41467-024-45135-z · Cited by 55 · see citing works
Self-citationThe Psychiatric Genomics Consortium: Discoveries and Directions
Arpana Agrawal, A., Bulik, C. M., Abebe, D., Andreassen, O. A., Atkinson, E. G., Choi, K. W., Corvin, A. P., Davies, H. L., Davis, L. K., Docherty, A. R., et al. (2025) · The Lancet Psychiatry · doi:10.1016/s2215-0366(25)00124-5 · Cited by 39 · see citing works
Koch, E. M., Connally, N. J., Baya, N. A., Reeve, M. P., Daly, M. J., Neale, B. M., Lander, E. S., Bloemendal, A., & Sunyaev, S. R. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.06.19.599789 · Cited by 34 · see citing works
Animal-SNPAtlas: a comprehensive SNP database for multiple animals
Gao, Y., Jiang, G., Yang, W., Jin, W., Gong, J., Xu, X., & Niu, X. (2022) · Nucleic Acids Research · doi:10.1093/nar/gkac954 · Cited by 24 · see citing works
Structural variation across 138,134 samples in the TOPMed consortiumPreprint
Jun, G., English, A. C., Metcalf, G., Yang, J., Chaisson, M., Pankratz, N., Menon, V. K., Salerno, W. J., Krasheninina, O. A., Smith, A. V., et al. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.01.25.525428 · Cited by 23 · see citing works
Self-citationZhong, W., Liu, W., Chen, J. C., Sun, Q., Hu, M., & Li, Y. (2022) · Frontiers in Cell and Developmental Biology · doi:10.3389/fcell.2022.957292 · Cited by 22 · see citing works
Self-citationDecoding Genetics, Ancestry, and Geospatial Context for Precision HealthPreprint
Koyama, S., Wang, Y., Paruchuri, K., Uddin, M. M., Cho, S. M. J., Urbut, S., Haidermota, S., Hornsby, W., Green, R. C., Daly, M. J., et al. (2023) · medRxiv · doi:10.1101/2023.10.24.23297096 · Cited by 23 · see citing works
Opportunities and challenges of local ancestry in genetic association analyses
Sun, Q., Horimoto, A. R. V. R., Chen, B., Ockerman, F. P., Mohlke, K. L., Blue, E., Raffield, L. M., & Li, Y. (2025) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2025.03.004 · Cited by 18 · see citing works
Self-citationMagicalRsq: Machine-learning-based genotype imputation quality calibration
Sun, Q., Yang, Y., Rosen, J. D., Jiang, M.-Z., Chen, J. C., Liu, W., Wen, J., Raffield, L. M., Pace, R. G., Zhou, Y., et al. (2022) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2022.09.009 · Cited by 18 · see citing works
Self-citationHuffman, J. E., Nicholas, J. C., Hahn, J. M., Heath, A. S., Raffield, L. M., Yanek, L. R., Brody, J. A., Thibord, F., Almasy, L. A., Bartz, T. M., et al. (2024) · Blood · doi:10.1182/blood.2023022596 · Cited by 18 · see citing works
Self-citationLi, H., Mazumder, R., & Lin, X. (2023) · Nature Communications · doi:10.1038/s41467-023-43565-9 · Cited by 16 · see citing works
Wen, J., Sun, Q., Huang, L., Zhou, L., Doyle, M. F., Ekunwe, L., Durda, P., Olson, N. C., Reiner, A. P., Li, Y., et al. (2024) · Genetics · doi:10.1093/genetics/iyae098 · Cited by 12 · see citing works
Self-citationPolygenic Scores of Cardiometabolic Risk Factors in American Indian Adults
Sun, Q., Du, J., Tang, Y., Best, L. G., Haack, K., Zhang, Y., Cole, S. A., & Franceschini, N. (2025) · JAMA Network Open · doi:10.1001/jamanetworkopen.2025.0535 · Cited by 12 · see citing works
Self-citationEye-brain connections revealed by multimodal retinal and brain imaging genetics in the UK BiobankPreprint
Zhao, B., Li, Y., Fan, Z., Wu, Z., Shu, J., Yang, X., Yang, Y., Wang, X., Li, B., Wang, X., et al. (2023) · medRxiv · doi:10.1101/2023.02.16.23286035 · Cited by 12 · see citing works
Self-citationFrom variants to mechanisms: Neurogenomics in the post-GWAS era
Margolis, M. P., Tang, M., Gagliardi, M., Wen, C. H., Wu, Y., Wray, N. R., Ziller, M. J., & Gandal, M. J. (2025) · Neuron · doi:10.1016/j.neuron.2025.10.014 · Cited by 11 · see citing works
Genetics and context for precision health in Greater Boston
Koyama, S., Wang, Y., Paruchuri, K., Uddin, M. M., Cho, S. M. J., Urbut, S., Sui, Y., Fahed, A. C., Kamineni, H., Haidermota, S., et al. (2025) · Nature Communications · doi:10.1038/s41467-025-66598-8 · Cited by 36 · see citing works
Lecluze, E., & Lettre, G. (2023) · Canadian Journal of Cardiology · doi:10.1016/j.cjca.2023.07.011 · Cited by 11 · see citing works
Yang, C., Gorijala, P., Timsina, J., Wang, L., Liu, M., Wang, C., Brock, W., Wang, Y., Urano, F., Sung, Y. J., et al. (2025) · Nature Communications · doi:10.1038/s41467-025-62463-w · Cited by 13 · see citing works
Yang, X., Jones, I. R., Chen, P. B., Yang, H., Ren, X., Zheng, L., Li, B., Li, Y. E., Sun, Q., Wen, J., et al. (2023) · doi:10.1101/2023.08.30.555359 · Cited by 10 · see citing works
Self-citationStructural variation across 138,134 samples in the TOPMed consortium
Jun, G., English, A., Metcalf, G., Yang, J., Chaisson, M., Pankratz, N., Menon, V., Salerno, W., Krasheninina, O., Smith, A., et al. (2023) · doi:10.21203/rs.3.rs-2515453/v1 · Cited by 24 · see citing works
Self-citationTrang, B. K., Pahl, M. C., Pippin, J. A., Su, C., Littleton, S. H., Sharma, P. K., Kulkarni, N. N., Ghanem, L. R., Terry, N. A., O’Brien, J. M., et al. (2024) · eLife · doi:10.7554/elife.95411.3 · Cited by 12 · see citing works
Multi-ancestry genome-wide association study of severe pregnancy nausea and vomiting
Fejzo, M. S., Wang, X., Tan, Q., Zöllner, J., Pujol‐Gualdo, N., Laisk, T., Metspalu, A., Milani, L. A., Esko, T., Mägi, R., et al. (2026) · Nature Genetics · doi:10.1038/s41588-026-02564-4 · Cited by 9 · see citing works
Chignon, A., & Lettre, G. (2025) · Atherosclerosis · doi:10.1016/j.atherosclerosis.2024.118621 · Cited by 9 · see citing works
Physiological role and mechanisms of action for a long noncoding haplotype region
Xue, H., Mishra, M. K., Liu, Y. U., Liu, P., Grzybowski, M. N., Pandey, R., Usa, K., Avond, M. A. V., Bala, N., Alli, A. A., et al. (2025) · Cell Reports · doi:10.1016/j.celrep.2025.115805 · Cited by 8 · see citing works
EADB, Bellenguez, C., Castillo Morales, A., Amin, N., van der Lee, S. J., Muntaner, M., Parveen, K., Küçükali, F., Grenier-Boley, B., Heikkinen, S., et al. (2026) · Nature Genetics · doi:10.1038/s41588-026-02583-1 · Cited by 7 · see citing works
“The index variant rs7481951 was not available in FUMA and was replaced by rs10833712, its best tag variant ( r 2 = 0.827) according to TopLD 45 .”
InfluentialDNA-binding factor footprints and enhancer RNAs identify functional non-coding genetic variants
Biddie, S. C., Weykopf, G., Hird, E. F., Friman, E. T., & Bickmore, W. A. (2024) · Genome biology · doi:10.1186/s13059-024-03352-1 · Cited by 7 · see citing works
Iyer, K. R., Clarke, S. L., Guarischi‐Sousa, R., Gjoni, K., Heath, A. S., Young, E. P., Stitziel, N. O., Laurie, C. A., Broome, J., Khan, A., et al. (2025) · Journal of the American Heart Association · doi:10.1161/jaha.124.036499 · Cited by 8 · see citing works
Self-citationWeak signal inclusion under dependence and applications in genome-wide association study
Jeng, X. J., Hu, Y., Sun, Q., & Li, Y. (2024) · The Annals of Applied Statistics · doi:10.1214/23-aoas1815 · Cited by 6 · see citing works
Self-citationRecommendations for responsible use of population descriptors in polygenic risk score development
Smith, J. L., Adebamowo, C., Adebamowo, S. N., Darst, B. F., Fullerton, S. M., Gogarten, S. M., Hamed, M. E., Hirbo, J. B., Hysong, M. R., Johar, A., et al. (2025) · Nature Genetics · doi:10.1038/s41588-025-02395-9 · Cited by 7 · see citing works
Self-citationZhang, X., Brody, J. A., Graff, M., Highland, H. M., Chami, N., Xu, H., Wang, Z., Ferrier, K., Chittoor, G., Josyula, N. S., et al. (2025) · Nature Communications · doi:10.1038/s41467-025-58420-2 · Cited by 6 · see citing works
Self-citationKarim, M. A., Ariano, B., Schwartzentruber, J., Roldán‐Romero, J. M., Mountjoy, E., Hayhurst, J. D., Buniello, A., Mohammed, E. S. E., Carmona, M., Holmes, M. V., et al. (2023) · medRxiv · doi:10.1101/2023.06.01.23290252 · Cited by 4 · see citing works
Currin, K. W., Perrin, H. J., Pandey, G. K., Alkhawaja, A. A., Vadlamudi, S., Musser, A. E., Etheridge, A. S., Broadaway, K. A., Rosen, J. D., Varshney, A., et al. (2025) · Genome Research · doi:10.1101/gr.279741.124 · Cited by 7 · see citing works
Self-citationMagicalRsq-X: A cross-cohort transferable genotype imputation quality metric
Sun, Q., Yang, Y., Rosen, J. D., Chen, J. C., Li, X., Guan, W., Jiang, M.-Z., Wen, J., Pace, R. G., Blackman, S. M., et al. (2024) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2024.04.001 · Cited by 5 · see citing works
Self-citationPérez-Gutiérrez, A. M., Carmona, R., Loucera, C., Cervilla, J. A., Gutiérrez, B., Molina, E., López-López, D., Pérez-Florido, J., Zarza-Rebollo, J. A., López‐Isac, E., et al. (2024) · Molecular Psychiatry · doi:10.1038/s41380-024-02609-2 · Cited by 5 · see citing works
Deciphering cis -regulatory elements using REgulamentary
Riva, S. G., Sanders, E., Georgiades, E., Venkatesh, S. S., Sergeant, M. J., Gür, E. R., Herrmann, J. C., Baxter, M. D., & Hughes, J. R. (2026) · Bioinformatics Advances · doi:10.1093/bioadv/vbag079 · Cited by 5 · see citing works
Ilboudo, Y., Brosseau, N., Lo, K. S., Belhaj, H., Moutereau, S., Marshall, K., Reid, M. E., Kutlar, A., Ashley‐Koch, A. E., Telen, M. J., et al. (2025) · Human Molecular Genetics · doi:10.1093/hmg/ddaf015 · Cited by 5 · see citing works
Vogi, V., Haschka, D., Forer, L., Schwendinger, S., Petzer, V., Coassin, S., Tancevski, I., Sonnweber, T., Löffler‐Ragg, J., Puchhammer‐Stöckl, E., et al. (2025) · Scientific Reports · doi:10.1038/s41598-025-89306-4 · Cited by 5 · see citing works
Re-analysis and meta-analysis of summary statistics from gene–environment interaction studies
Pham, D. T., Westerman, K. E., Pan, C., Chen, L., Srinivasan, S., ISGANAITIS, E. M., Vajravelu, M. E., Bacha, F. F., Chernausek, S. D., Gubitosi‐Klug, R., et al. (2023) · Bioinformatics · doi:10.1093/bioinformatics/btad730 · Cited by 4 · see citing works
Liver single-nucleus multiome profiling reveals cell-type mechanisms for cardiometabolic traits
Alkhawaja, A. A., Currin, K. W., Perrin, H. J., Vadlamudi, S., Etheridge, A. S., Broadaway, K. A., Cannon, G. H., Anderson, C. W., Moxley, A. H., Iuga, A. C., et al. (2025) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2025.11.009 · Cited by 5 · see citing works
Trang, B. K., Sharma, P. K., Cook, L. E., Mount, Z., Thomas, R. M., Kulkarni, N. N., Cabrera, E. C., Rachimi, S., Pahl, M. C., Pippin, J. A., et al. (2025) · Genome biology · doi:10.1186/s13059-025-03880-4 · Cited by 3 · see citing works
Nanopore sequencing as a novel method of characterising anorexia nervosa risk loci
Berthold, N., Gaudieri, S., Hood, S. D., Tschochner, M., Miller, A. L., Jordan, J., Thornton, L. M., Bulik, C. M., Akkari, P. A., & Kennedy, M. A. (2024) · BMC Genomics · doi:10.1186/s12864-024-11172-7 · Cited by 3 · see citing works
Barnes, D. R., Tyrer, J. P., Dennis, J., Leslie, G., Bolla, M. K., Lush, M. J., Aeilts, A. M., Aittomäki, K., Andrieu, N., Andrulis, I. L., et al. (2024) · medRxiv · doi:10.1101/2024.02.29.24303243 · Cited by 3 · see citing works
Fejzo, M. S., Wang, X., Zöllner, J., Pujol‐Gualdo, N., Laisk, T., Finer, S., van Heel, D. A., Brumpton, B. M., Bhatta, L., Hveem, K., et al. (2024) · medRxiv · doi:10.1101/2024.11.19.24317559 · Cited by 3 · see citing works
Liu, P., Ray, A., Liu, Y., Mishra, M. K., Qiu, Q., Pandey, R., Therani, B., Huang, J., Ren, J., Stelloh, C. T., et al. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.12.25.630318 · Cited by 3 · see citing works
PRED-LD: efficient imputation of GWAS summary statistics
Μανιός, Γ., Michailidi, A., Kontou, P. I., & Bagos, P. G. (2025) · BMC Bioinformatics · doi:10.1186/s12859-025-06119-y · Cited by 2 · see citing works
Molecular systems, human noncoding sequence variants, and blood pressure
Qiu, Q., & Liang, M. (2026) · Physiological Reviews · doi:10.1152/physrev.00029.2025 · Cited by 2 · see citing works
Li, Z., Zhao, W., Zhou, X., Leung, Y. Y., Schellenberg, G. D., Wang, L.-S., Schönherr, S., Forer, L., Fuchsberger, C., Dey, S., et al. (2026) · Human Genetics and Genomics Advances · doi:10.1016/j.xhgg.2026.100579 · Cited by 2 · see citing works
A cross-organ single-cell analysis of hypertension
Qiu, Q., Liu, Y., Xue, H., Pandey, R., Liu, J., He, L., Liu, P., Therani, B., Kumar, V. D., Huang, J., et al. (2026) · Science · doi:10.1126/science.aea6187 · Cited by 2 · see citing works
Sun, Q., Karafin, M. S., Garrett, M. E., Li, Y., Ashley‐Koch, A. E., & Telen, M. J. (2024) · Transfusion · doi:10.1111/trf.17944 · Cited by 2 · see citing works
Self-citationGenetic examination of hematological parameters in SARS-CoV-2 infection and COVID-19
Sun, Q., Rowland, B., Wang, W., Miller‐Fleming, T. W., Cox, N. J., Graff, M., Faucon, A. B., Shuey, M. M., Blue, E., Auer, P. L., et al. (2023) · Blood Cells Molecules and Diseases · doi:10.1016/j.bcmd.2023.102782 · Cited by 2 · see citing works
Self-citationZhang, X., Brody, J. A., Graff, M., Highland, H. M., Chami, N., Xu, H., Wang, Z., Ferrier, K., Chittoor, G., Josyula, N. S., et al. (2023) · medRxiv · doi:10.1101/2023.08.21.23293271 · Cited by 2 · see citing works
Self-citationTrang, B. K., Sharma, P. K., Cook, L. E., Mount, Z., Thomas, R. M., Kulkarni, N. N., Cabrera, E. C., Rachimi, S., Pahl, M. C., Pippin, J. A., et al. (2024) · medRxiv · doi:10.1101/2024.08.12.24311676 · Cited by 2 · see citing works
A single-cell map of hypertensionPreprint
Qiu, Q., Liu, Y., Xue, H., Pandey, R., He, L., Liu, J., Liu, P., Therani, B., Kumar, V., Huang, J., et al. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.12.25.630332 · Cited by 2 · see citing works
ADGC, Bonn, CHARGE, EADB, Bellenguez, C., EADI, FinnGen, GERAD, GR@ACE/DEGESCO, & PGC-ALZ (2025) · medRxiv · doi:10.1101/2025.10.20.25338060 · Cited by 2 · see citing works
Ubiquitous dysregulation of the Wnt pathway in immune thrombocytopenia genetic susceptibility
Lecluze, E., Faria, S. D. S., Saby, M., Yu, J., Lisi, V., Lavallée, V., Olmsted, T., Scheurer, M. E., Grimes, A. B., & Pincez, T. (2025) · Blood Vessels Thrombosis & Hemostasis · doi:10.1016/j.bvth.2025.100107 · Cited by 1 · see citing works
Barnes, D. R., Tyrer, J. P., Dennis, J., Leslie, G., Bolla, M. K., Lush, M. J., Aeilts, A. M., Aittomäki, K., Andrieu, N., Andrulis, I. L., et al. (2025) · npj Genomic Medicine · doi:10.1038/s41525-025-00529-w · Cited by 1 · see citing works
AncientProxy: A catalog of ancient proxies for modern genetic variants
Brand, C. M., & Capra, J. A. (2026) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2026.01.001 · Cited by 1 · see citing works
Cruchaga, C., Yang, C., Gorijala, P., Timsina, J., Wang, L., Liu, M., Wang, C., Brock, W., Wang, Y., & Sung, Y. J. (2024) · Research Square · doi:10.21203/rs.3.rs-3617016/v1 · Cited by 1 · see citing works
Trang, B. K., Pahl, M. C., Pippin, J. A., Su, C., Littleton, S. H., Sharma, P. K., Kulkarni, N. N., Ghanem, L. R., Terry, N. A., O’Brien, J. M., et al. (2024) · eLife · doi:10.7554/elife.95411.1.sa0 · Cited by 1 · see citing works
Trang, B. K., Pahl, M. C., Pippin, J. A., Su, C., Littleton, S. H., Sharma, P. K., Kulkarni, N. N., Ghanem, L. R., Terry, N. A., O’Brien, J. M., et al. (2024) · eLife · doi:10.7554/elife.95411.1 · Cited by 1 · see citing works
Wen, J., Lin, B. M., Sun, Q., Jiang, M.-Z., Linchangco, G. V., Li, G., Chen, R., Go, A. S., Miller‐Fleming, T. W., Shuey, M. M., et al. (2025) · medRxiv · doi:10.1101/2025.02.19.25322572 · Cited by 1 · see citing works
Self-citationRodríguez-Nunez, I., Bartley, S. C., Taylor, J. W., Johnston, S. Q., Rogers, B. B., Meadows, S. K., Newberry, K. M., Cochran, J. N., & Myers, R. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.05.30.657077 · Cited by 1 · see citing works
Peng, J., & Zhang, W. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2025.12.18.695261 · Cited by 1 · see citing works
Vrathasha, V., Pahl, M. C., Pippin, J. A., Nikonov, S. S., He, J., Halimitabrizi, M., Moksha, L., Salowe, R., Edziah, A.-A., Bradford, Y., et al. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.02.20.707051 · Cited by 1 · see citing works
Biddanda, A., de Arce, K. P., Eze-Echesi, G., Nwuba, C., Ibrahim, Y., Oyedele, O., Joshi, E., Alalade, B. A., Ajayi, O., Nwatu, C. B., et al. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.12.09.519773
eQTL in diseased colon tissue identifies novel target genes associated with IBDPreprint
Nishiyama, N. C., Silverstein, S., Darlington, K., Ng, M. M. K., Clough, K., Bauer, M. J., Beasley, C., Bharadwaj, A., Ganesan, R., Kapadia, M. R., et al. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.10.14.618229
Nanopore Sequencing as a Novel Method of Characterising Anorexia Nervosa Risk LociPreprint
Berthold, N., Gaudieri, S., Hood, S. D., Tschochner, M., Akkari, P. A., & Kennedy, M. A. (2024) · Research Square · doi:10.21203/rs.3.rs-4949322/v1
Trang, B. K., Pahl, M. C., Pippin, J. A., Su, C., Littleton, S. H., Sharma, P. K., Kulkarni, N. N., Ghanem, L. R., Terry, N. A., O’Brien, J. M., et al. (2024) · eLife · doi:10.7554/elife.95411.2
Common tandem repeat variants associated with glaucoma risk in individuals of African ancestryPreprint
Pham, K., Lee, R., Rosa, I. D., Salowe, R., Jin, F., Bradford, Y., Ying, G., Phillips‐Cremins, J. E., Verma, S. S., & O’Brien, J. M. (2025) · medRxiv · doi:10.1101/2025.02.19.25322489
A catalog of ancient proxies for modern genetic variantsPreprint
Brand, C. M., & Capra, J. A. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.05.19.654975
CREST-GV: Cell types Ranking and Enrichment Score for selecTive Genetic VariantsPreprint
Riva, S. G., Venkatesh, S. S., Gür, E. R., Stranieri, N., Sergeant, M. J., Baxter, M. D., & Hughes, J. R. (2025) · medRxiv · doi:10.1101/2025.07.29.25332311
Global Evaluation of Congenital Heart Disease-Associated Non-Coding VariantsPreprint
Peña-Martínez, E. G., Peña-Martínez, E., Sharma, S., Medina-Feliciano, J., Root, E., Parks, L., Granitto, M., Pomales-Matos, D., Bird, J. M., Barreiro-Rosario, A., et al. (2025) · Research Square · doi:10.21203/rs.3.rs-8429365/v1
fastMETA: a fast and efficient tool for multivariate meta-analysis of GWAS
Μανιός, Γ., Kandylas, D., Kylonis, A., Bagos, P. G., & Kontou, P. I. (2025) · Frontiers in Genetics · doi:10.3389/fgene.2025.1718626
Biddie, S. C., Weykopf, G., Hird, E. F., Friman, E. T., & Bickmore, W. A. (2024) · Figshare · doi:10.6084/m9.figshare.26758288
Biddie, S. C., Weykopf, G., Hird, E. F., Friman, E. T., & Bickmore, W. A. (2024) · Figshare · doi:10.6084/m9.figshare.26758285
Gerlach, P. A., Gadgaard, S., Madsen, J. S., Lindquist, P., Lorente, J. S., Faas, F., Gabe, M. B. N., ROSENKILDE, M. M., & Hauser, A. S. (2026) · Metabolism · doi:10.1016/j.metabol.2025.156489
COMPREHENSIVE GENETIC INVESTIGATION REVEALS HETEROGENEOUS PATHWAYS TO OBSTRUCTIVE SLEEP APNEAPreprint
Justice, A. E., Keenan, B. T., Chittoor, G., Pahl, M. C., Hoskens, H., Josyula, N. S., Gupta, S., Kim, S., Þorleifsson, G., Manduchi, E., et al. (2026) · medRxiv · doi:10.64898/2026.01.08.26343696
PYRAMA: an open-source tool for advanced meta-analysis of genome wide association studies
Μανιός, Γ., Nteli, S., Kontou, P. I., & Bagos, P. G. (2026) · Bioinformatics · doi:10.1093/bioinformatics/btag054
eQTL in diseased colon tissue identifies potential target genes associated with IBD
Nishiyama, N. C., Silverstein, S., Darlington, K., Ng, M. M. K., Clough, K., Bauer, M. J., Beasley, C., Bharadwaj, A., Ganesan, R., Kapadia, M. R., et al. (2026) · Nature Communications · doi:10.1038/s41467-026-69364-6
Cao, H., Zheng, Z., Zhou, X., Kikuchi, M., Wong, H. Y., Cheng, E. Y. L., Wong, B. W. Y., Lo, R. M. N., Shoai, M., Chong, J. R., et al. (2026) · Alzheimer s & Dementia · doi:10.1002/alz.71219
Impact of proteogenomic evidence on clinical successPreprint
Karim, M. A., Hukku, A., Ariano, B., Holzinger, E. R., Tsepilov, Y. A., Hayhurst, J. D., Buniello, A., McDonagh, E. M., Castel, S. E., Nelson, M. R., et al. (2026) · medRxiv · doi:10.64898/2026.02.23.26346731
McDowell, S., Beaumont, R. N., Green, H., Kingdom, R., Vabistsevits, M., Prague, J., Murray, A., Tyrrell, J., & Ruth, K. S. (2026) · medRxiv · doi:10.64898/2026.03.06.26347586
Molecular analysis of STAT3 and their association in non-Hodgkin lymphoma incidence
AL-SARRAJ, B. M., & Altaee, M. F. (2026) · Iraqi Journal of Hematology · doi:10.4103/ijh.ijh_121_25
Cell-specific variant-to-gene mapping identifies conserved neural and glial regulators of sleepPreprint
Zimmerman, A. J., Biglari, S., Trang, B. K., Valle, E. A. D., Pack, A. I., Grant, S. F. A., & Keene, A. C. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.04.07.715910
A Novel PTPN2 Isoform Differentially Regulates Immune Response
Li, X., Rahimov, F., Wang, R., Gao, L., Ma, R., Han, T., Bi, Y., Cruz, F., Wang, J., Grosskurth, S., et al. (2026) · European Journal of Immunology · doi:10.1002/eji.70207
Cross-population metabolome-wide Mendelian randomization study of prostate cancer riskPreprint
Fuller, H., Rohde, R., Highland, H. M., Haessler, J., Wu, L., Graff, M., Platz, E. A., Alkis, T., Yu, B., Boerwinkle, E., et al. (2026) · Research Square · doi:10.21203/rs.3.rs-9708129/v1
Self-citationPositioning personal polygenic risk score against the population background
Escott‐Price, V., Leonenko, G., & Schmidt, K. M. (2026) · Research in Statistics · doi:10.1080/27684520.2026.2685935
Esmaeili-Fard, S. M., Maihofer, A. X., Willis, T. W., Mikita, E. A., Johnson, J. A., Munro, D. B., Kumar, A. V., Pokhrel, N., Palmer, A. A., Nievergelt, C. M., et al. (2026) · medRxiv · doi:10.64898/2026.08.21.26360655
Álvarez-González, B., Morales-Álvarez, C. M., Porras-Quesada, P. M., Chica-Redecillas, L., Cañadas‐Garre, M., Hernández, A. F., Álvarez-Cubero, M. J., & Martínez-González, L. J. (2026) · Free Radical Biology and Medicine · doi:10.1016/j.freeradbiomed.2026.08.048
Genetic variation in BDNF is associated with opioid use disorder severity
Kusic, D., Salzman, M., Heil, J., Grant, S. F. A., Trang, K. B., Zajic, S. C., Madžo, J., Brown, C., Jelı́nek, J., Calendo, G., et al. (2026) · Human Genetics · doi:10.1007/s00439-026-02866-x
Ma, W., Cheng, Y., Li, H., & Lv, H. (2026) · Genes · doi:10.3390/genes17101277
- Authors
- Huang, L., Rosen, J. D., Sun, Q., Chen, J., Wheeler, M. M., Zhou, Y., Min, Y.-I., Kooperberg, C., Conomos, M. P., Stilp, A. M., Rich, S. S., Rotter, J. I., Manichaikul, A., Loos, R. J. F., Kenny, E. E., Blackwell, T. W., Smith, A. V., Jun, G., Sedlazeck, F. J., Metcalf, G., Boerwinkle, E., Raffield, L. M., Reiner, A. P., Auer, P. L., & Li, Y.
- Affiliations
- University of North Carolina at Chapel Hill (US)
- University of Washington (US)
- Fred Hutch Cancer Center (US)
- University of Mississippi Medical Center (US)
- University of Virginia (US)
- The Lundquist Institute (US)
- University of Copenhagen (DK)
- Icahn School of Medicine at Mount Sinai (US)
- University of Michigan (US)
- The University of Texas Health Science Center at Houston (US)
- Baylor College of Medicine (US)
- Medical College of Wisconsin (US)
- Corresponding author
- Auer, Paul L.
- Li, Yun
- ORCID
- Huang, Le
- Rosen, Jonathan D.
- Sun, Quan
- Chen, Jiawen
- Wheeler, Marsha M.
- Zhou, Ying
- Min, Yuan-I
- Kooperberg, Charles
- Conomos, Matthew P.
- Stilp, Adrienne M.
- Rich, Stephen S.
- Rotter, Jerome I.
- Manichaikul, Ani
- Loos, Ruth J.F.
- Kenny, Eimear E.
- Blackwell, Thomas W.
- Smith, Albert V.
- Jun, Goo
- Sedlazeck, Fritz J.
- Metcalf, Ginger
- Boerwinkle, Eric
- Raffield, Laura M.
- Reiner, Alex P.
- Auer, Paul L.
- Li, Yun
- Venue
- The American Journal of Human Genetics
- Publisher
- Elsevier BV
- Published
- 2022-06
- Volume
- 109
- Issue
- 6
- Pages
- 1175-1181
- ISSN
- 0002-9297 (ISSN-L)
- PMC
- PMC9247832
- OpenAlex
- W4225286463
- Cited by
- 97
- References
- 23
- Citations by year
- 2026: 24 · 2025: 29 · 2024: 26 · 2023: 14 · 2022: 4
- FWCI
- 11.01
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- The American Journal of Human Genetics (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Research at the University of Copenhagen (University of Copenhagen) (publishedVersion, cc-by)
- Digital Commons-TMC (Texas Medical Center) (submittedVersion)
- Carolina Digital Repository (University of North Carolina at Chapel Hill) (submittedVersion, cc-by)
- eScholarship (California Digital Library) (submittedVersion, cc-by)
- UNC Libraries
- Funders
- National Institutes of Health (KL2TR002490, R01HL129132, R01HL146500, U01DA052713, U01HG011720, U24 AR076730)
- 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, TOPMed, web-based tool, rare variants, structural variants, fine mapping, GGT1, gamma-glutamyl transferase, African ancestry, 1000 Genomes Project, genetic variation
- MeSH terms
- Whole Genome Sequencing, Humans, Linkage Disequilibrium, Polymorphism, Single Nucleotide, Asian People, Genome-Wide Association Study, Precision Medicine
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
