The DOI matches its Crossref record; 59 of the 60 references it cites were found in a registry or an index.
A second generation human haplotype map of over 3.1 million SNPs
Open accessAbstract
We describe the Phase II HapMap, which characterizes over 3.1 million human single nucleotide polymorphisms (SNPs) genotyped in 270 individuals from four geographically diverse populations and includes 25-35% of common SNP variation in the populations surveyed. The map is estimated to capture untyped common variation with an average maximum r2 of between 0.9 and 0.96 depending on population. We demonstrate that the current generation of commercial genome-wide genotyping products captures common Phase II SNPs with an average maximum r2 of up to 0.8 in African and up to 0.95 in non-African populations, and that potential gains in power in association studies can be obtained through imputation. These data also reveal novel aspects of the structure of linkage disequilibrium. We show that 10-30% of pairs of individuals within a population share at least one region of extended genetic identity arising from recent ancestry and that up to 1% of all common variants are untaggable, primarily because they lie within recombination hotspots. We show that recombination rates vary systematically around genes and between genes of different function. Finally, we demonstrate increased differentiation at non-synonymous, compared to synonymous, SNPs, resulting from systematic differences in the strength or efficacy of natural selection between populations.
Overview
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
Verification
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 source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“The fine-scale pattern of LD in humans confirms that the human genome is comprised of haplotype blocks within which most or all SNPs are in high LD21.”
From Linkage disequilibrium--understanding the evolutionary past and mapping the medical future. (2008) · cites this paper as [21]
Experimental — accuracy not yet measuredThe cited source says what the claim attributes to it.
In the citing paper
“The second generation HapMap published recently characterized 3.1 million SNPs in the same group of individuals21.”
From Linkage disequilibrium--understanding the evolutionary past and mapping the medical future. (2008) · cites this paper as [21]
The cited source says what the claim attributes to it.
In the citing paper
“that the number of inferred ancestral recombination events per genomic window agrees with a previously published population recombination map (17) (fig. S20B; Spearman’s rho = 0.46; P < 2.2 × 10−16), as expected.”
From An ancestral recombination graph of human, Neanderthal, and Denisovan genomes (2021) · cites this paper as [17]
The cited source says what the claim attributes to it.
In the citing paper
“As expected, the tag SNP allele frequencies in our samples mirrored previously described distributions in major geographic groups (Lamason et al. 2005;Yuasa et al. 2006;Frazer et al. 2007;Miller et al. 2007;Norton et al. 2007;Soejima and Koda 2007) (table 1).”
From The timing of pigmentation lightening in Europeans (2013) · cites this paper as Frazer et al. 2007
The check wasn’t confident either way, so it gives no verdict — never disputed.
In the citing paper
“Haplotype blocks vary somewhat among human populations — they tend to be somewhat shorter in African populations15,20,21.”
From Linkage disequilibrium--understanding the evolutionary past and mapping the medical future. (2008) · cites this paper as [21]
Experimental — accuracy not yet measured
The check wasn’t confident either way, so it gives no verdict — never disputed.
In the citing paper
“Previous studies using several population samples from different continents have shown that, unlike SLC45A2, derived alleles at SLC24A5, TYRP1, and KITLG are present at low frequencies in some sub-Saharan populations (table 1, see also Yuasa et al. 2006;Frazer et al. 2007;Norton et al. 2007;Soejima and Koda 2007;Coop et al. 2009;Pickrell et al. 2009).”
From The timing of pigmentation lightening in Europeans (2013) · cites this paper as Frazer et al. 2007
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.
Citations
Cites
PLINK: a tool set for whole-genome association and population-based linkage analyses.
Purcell, S., Neale, B., Todd-Brown, K., Thomas, L., Ferreira, M. A. R., Bender, D., Maller, J., Sklar, P., de Bakker, P. I. W., Daly, M. J., et al. (2007) · The American Journal of Human Genetics · doi:10.1086/519795 · Cited by 34,089
ESTIMATING F -STATISTICS FOR THE ANALYSIS OF POPULATION STRUCTURE
Weir, B. S., & Cockerham, C. C. (1984) · Evolution · doi:10.1111/j.1558-5646.1984.tb05657.x · Cited by 18,909
Principal components analysis corrects for stratification in genome-wide association studies
Price, A. L., Patterson, N. J., Plenge, R. M., Weinblatt, M. E., Shadick, N. A., & Reich, D. (2006) · Nature Genetics · doi:10.1038/ng1847 · Cited by 10,248
Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls
The Wellcome Trust Case Control Consortium, Management Committee, Burton, P. R., Clayton, D. G., Cardon, L. R., Craddock, N., Deloukas, P., Duncanson, A., Kwiatkowski, D. P., McCarthy, M. I., et al. (2007) · Nature · doi:10.1038/nature05911 · Cited by 9,442
Self-citationThe International HapMap Project
†The International HapMap Consortium, Genotyping centres: Baylor College of Medicine and ParAllele BioScience, Gibbs, R. A., Belmont, J. W., Hardenbol, P., Willis, T. D., Yu, F., Chinese HapMap Consortium, Yang, H., Ch'ang, L.-Y., et al. (2003) · Nature · doi:10.1038/nature02168 · Cited by 6,057
A haplotype map of the human genome
The International HapMap Consortium (2005) · Nature · doi:10.1038/nature04226 · Cited by 5,858
Self-citationGlobal variation in copy number in the human genome
Redon, R., Ishikawa, S., Fitch, K. R., Feuk, L., Perry, G. H., Andrews, T. D., Fiegler, H., Shapero, M. H., Carson, A. R., Chen, W., et al. (2006) · Nature · doi:10.1038/nature05329 · Cited by 4,377
PANTHER: A Library of Protein Families and Subfamilies Indexed by FunctionPreprint
Thomas, P. D., Campbell, M. J., Kejariwal, A., Mi, H., Karlak, B., Daverman, R., Diemer, K., Muruganujan, A., & Narechania, A. (2003) · Genome Research · doi:10.1101/gr.772403 · Cited by 2,978
A Map of Recent Positive Selection in the Human Genome
Voight, B. F., Kudaravalli, S., Wen, X., & Pritchard, J. K. (2006) · PLoS Biology · doi:10.1371/journal.pbio.0040072 · Cited by 2,925
A genome-wide association study of type 2 diabetes in Finns detects multiple susceptibility variants
Scott, L. J., Mohlke, K. L., Bonnycastle, L. L., Willer, C. J., Li, Y., Duren, W. L., Erdos, M. R., Stringham, H. M., Chines, P. S., Jackson, A. U., et al. (2007) · Science · doi:10.1126/science.1142382 · Cited by 2,753
Flagged first, then by citations
1 of the 60 references couldn’t be matched to a known paper.
Research works printed but not linked: 1
- Purcell, S. et al. PLINK: a tool set for whole-genome association and population-based linkage analyses. Am. J. Hum. Genet. 81, 559–575 (2007) · DOI · Paper page
Cited by
Sorted by citations
Items 901–1,000 of 1,030
Awh, C. C., Hawken, S., & Zanke, B. W. (2014) · Ophthalmology · doi:10.1016/j.ophtha.2014.07.049 · Cited by 91
Genomics of type 2 diabetes mellitus: implications for the clinician
Stolerman, E. S., & Florez, J. C. (2009) · Nature Reviews Endocrinology · doi:10.1038/nrendo.2009.129 · Cited by 91
Ko, D. C., Shukla, K. P., Fong, C. T., Wasnick, M., Brittnacher, M., Wurfel, M. M., Holden, T. D., O’Keefe, G. E., Yserloo, B. V., Akey, J. M., et al. (2009) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2009.07.012 · Cited by 91
TCF7L2 genetic defect and type 2 diabetes
Cauchi, S., & Froguel, P. (2008) · Current Diabetes Reports · doi:10.1007/s11892-008-0026-x · Cited by 91
The mid p-value in exact tests for Hardy-Weinberg equilibrium
Graffelman, J., & Moreno, V. R. (2013) · Statistical Applications in Genetics and Molecular Biology · doi:10.1515/sagmb-2012-0039 · Cited by 91
Genome-wide detection of natural selection in African Americans pre- and post-admixturePreprint
Jin, W., Xu, S., Wang, H., Yu, Y., Shen, Y., Wu, B.-L., & Li, J. (2011) · Genome Research · doi:10.1101/gr.124784.111 · Cited by 91
Heinrichs, S., Kulkarni, R. V., Bueso‐Ramos, C. E., Levine, R. L., Loh, M. L., Li, C., Neuberg, D. S., Kornblau, S. M., Issa, J. J., Gilliland, D. G., et al. (2009) · Leukemia · doi:10.1038/leu.2009.82 · Cited by 90
An imputation platform to enhance integration of rice genetic resources
Wang, D., Agosto-Perez, F., Chebotarov, D., Shi, Y., Marchini, J., Fitzgerald, M. A., McNally, K. L., Alexandrov, N. N., & McCouch, S. R. (2018) · Nature Communications · doi:10.1038/s41467-018-05538-1 · Cited by 90
A genome-wide association study identifies ITGA9 conferring risk of nasopharyngeal carcinoma
Ng, C. C., Yew, P. Y., Puah, S. M., Krishnan, G., Yap, L. F., Teo, S. H., Lim, P. V. H., Govindaraju, S., Ratnavelu, K., Sam, C. K., et al. (2009) · Journal of Human Genetics · doi:10.1038/jhg.2009.49 · Cited by 90
Hao, K., Chudin, E., McElwee, J. J., & Schadt, E. E. (2009) · BMC Genetics · doi:10.1186/1471-2156-10-27 · Cited by 90
Lingappa, J. R., Petrovski, S., Kahle, E., Fellay, J., Shianna, K. V., McElrath, M. J., Thomas, K. K., Baeten, J. M., Celum, C., Wald, A., et al. (2011) · PLoS ONE · doi:10.1371/journal.pone.0028632 · Cited by 90
Tintle, N., Pottala, J. V., Lacey, S., Vasan, R. S., Westra, J., Rogers, A., Clark, J., Olthoff, B., Larson, M. G., Harris, W. S., et al. (2014) · Prostaglandins Leukotrienes and Essential Fatty Acids · doi:10.1016/j.plefa.2014.11.007 · Cited by 91
Population identification using genetic data
Lawson, D. J., & Falush, D. (2012) · Annual Review of Genomics and Human Genetics · doi:10.1146/annurev-genom-082410-101510 · Cited by 89
Design of association studies with pooled or un‐pooled next‐generation sequencing data
Kim, S. Y., Li, Y., Guo, Y., Li, R., Holmkvist, J., Hansen, T. F., Pedersen, O. B., Wang, J., & Nielsen, R. (2010) · Genetic Epidemiology · doi:10.1002/gepi.20501 · Cited by 89
Dating the age of admixture via wavelet transform analysis of genome-wide data
Pugach, I., Matveyev, R., Wollstein, A., Kayser, M., & Stoneking, M. (2011) · Genome biology · doi:10.1186/gb-2011-12-2-r19 · Cited by 89
Megens, H., Crooijmans, R. P. M. A., Bastiaansen, J. W. M., Kerstens, H. H. D., Coster, A., Jalving, R., Vereijken, A., Silva, P., Muir, W. M., Cheng, H. H., et al. (2009) · BMC Genetics · doi:10.1186/1471-2156-10-86 · Cited by 89
Li, M. J., Yan, B., Sham, P. C., & Wang, J. (2014) · Briefings in Bioinformatics · doi:10.1093/bib/bbu018 · Cited by 89
Genetic Variation in the Dectin-1/CARD9 Recognition Pathway and Susceptibility to Candidemia
Rosentul, D. C., Plantinga, T. S., Oosting, M., Scott, W. K., Edwards, D. R. V., Smith, P. B., Alexander, B. D., Yang, J. C., Laird, G. M., Joosten, L. A. B., et al. (2011) · The Journal of Infectious Diseases · doi:10.1093/infdis/jir458 · Cited by 89
Hong, H., Su, Z., Ge, W., Shi, L. M., Perkins, R., Fang, H., Xu, J., Chen, J. J., Han, T., Kaput, J., et al. (2008) · BMC Bioinformatics · doi:10.1186/1471-2105-9-s9-s17 · Cited by 89
APOL1 variants and kidney disease in people of recent African ancestry
Genovese, G., Friedman, D. J., & Pollak, M. R. (2013) · Nature Reviews Nephrology · doi:10.1038/nrneph.2013.34 · Cited by 88
Perspectives on Human Population Structure at the Cusp of the Sequencing Era
Novembre, J., & Ramachandran, S. (2011) · Annual Review of Genomics and Human Genetics · doi:10.1146/annurev-genom-090810-183123 · Cited by 88
Holm, K., Melum, E., Franke, A., & Karlsen, T. H. (2010) · BMC Bioinformatics · doi:10.1186/1471-2105-11-600 · Cited by 88
Cotsapas, C. J., Mitrovič, M., & Hafler, D. A. (2018) · Handbook of clinical neurology · doi:10.1016/b978-0-444-64076-5.00046-6 · Cited by 88
Jaeger, M., van der Lee, R., Cheng, S., Johnson, M. D., Kumar, V., Ng, A., Plantinga, T. S., Smeekens, S. P., Oosting, M., Wang, X., et al. (2015) · European Journal of Clinical Microbiology & Infectious Diseases · doi:10.1007/s10096-014-2309-2 · Cited by 88
Bhatia, G., Patterson, N. J., Paşaniuc, B., Zaitlen, N., Genovese, G., Pollack, S. J., Mallick, S., Myers, S., Tandon, A., Spencer, C. C. A., et al. (2011) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2011.07.025 · Cited by 88
Dereeper, A., Nicolas, S., Cunff, L. L., Baciliéri, R., Doligez, A., Péros, J., Ruíz, M., & This, P. (2011) · BMC Bioinformatics · doi:10.1186/1471-2105-12-134 · Cited by 88
Natural Selection in a Bangladeshi Population from the Cholera-Endemic Ganges River Delta
Karlsson, E. K., Harris, J. B., Tabrizi, S., Rahman, A., Shlyakhter, I. A., Patterson, N. J., O’Dushlaine, C. T., Schaffner, S. F., Gupta, S., Chowdhury, F., et al. (2013) · Science Translational Medicine · doi:10.1126/scitranslmed.3006338 · Cited by 88
Replication of restless legs syndrome loci in three European populations
Kemlink, D., Polo, O. J., Frauscher, B., Gschliesser, V., Högl, B., Poewe, W. H., Vodička, P., Vávrová, J., Šonka, K., Nevšímalová, S., et al. (2009) · Journal of Medical Genetics · doi:10.1136/jmg.2008.062992 · Cited by 88
Lee, P. H., Perlis, R. H., Jung, J. Y., Byrne, E. M., Rueckert, E. H., Siburian, R., Haddad, S. A., Mayerfeld, C., Heath, A. C., Pergadia, M. L., et al. (2012) · Translational Psychiatry · doi:10.1038/tp.2012.95 · Cited by 88
Chang, M., Lindegren, M. L., Butler, M. A., Chanock, S. J., Dowling, N. F., Gallagher, M., Moonesinghe, R., Moore, C. A., Ned, R. M., Reichler, M. R., et al. (2008) · American Journal of Epidemiology · doi:10.1093/aje/kwn286 · Cited by 88
Ge, T., Feng, J., Hibar, D. P., Thompson, P. M., & Nichols, T. E. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2012.07.012 · Cited by 88
The Myocardial Infarction Genetics Consortium, Shea, J., Agarwala, V., Philippakis, A. A., Maguire, J., Banks, E., DePristo, M., Thomson, B., Guiducci, C., Onofrio, R. C., et al. (2011) · Nature Genetics · doi:10.1038/ng.871 · Cited by 87
Li, Y., Byrnes, A., & Li, M. (2010) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2010.10.014 · Cited by 87
van Setten, J., Brody, J. A., Jamshidi, Y., Swenson, B. R., Butler, A. M., Campbell, H., Fabiola Del Greco, M., Evans, D. S., Gibson, Q., Gudbjartsson, D. F., et al. (2018) · Nature Communications · doi:10.1038/s41467-018-04766-9 · Cited by 87
Polygenic risk scores in psychiatry: Will they be useful for clinicians?
Fullerton, J. M., & Nürnberger, J. I. (2019) · F1000Research · doi:10.12688/f1000research.18491.1 · Cited by 87
Zhu, N., Swietlik, E. M., Welch, C. L., Pauciulo, M. W., Hagen, J., Zhou, X., Guo, Y., Karten, J., Pandya, D., Tilly, T., et al. (2021) · Genome Medicine · doi:10.1186/s13073-021-00891-1 · Cited by 87
Single nucleotide polymorphisms in clinics: Fantasy or reality for cancer?
Srinivasan, S., Clements, J. A., & Batra, J. (2015) · Critical Reviews in Clinical Laboratory Sciences · doi:10.3109/10408363.2015.1075469 · Cited by 87
Cortés, A., Maksymowych, W. P., Wordsworth, B. P., Inman, R. D., Danoy, P., Rahman, P., Stone, M., Corr, M., Gensler, L. S., Gladman, D., et al. (2014) · Annals of the Rheumatic Diseases · doi:10.1136/annrheumdis-2013-204835 · Cited by 87
Nakabayashi, K., Komaki, G., Tajima, A., Ando, T., Ishikawa, M., Nomoto, J., Hata, K., Oka, A., Inoko, H., Sasazuki, T., et al. (2009) · Journal of Human Genetics · doi:10.1038/jhg.2009.74 · Cited by 87
Bressler, J., Kao, W. H. L., Pankow, J. S., & Boerwinkle, E. (2010) · PLoS ONE · doi:10.1371/journal.pone.0010521 · Cited by 87
Nakayama, K., Tumenbayar, B., Yamanaka, K., Kumada, M., Gotoh, T., Utsumi, N., Yanagisawa, Y., Okayama, M., Kajii, E., Ishibashi, S., et al. (2009) · Journal of Medical Genetics · doi:10.1136/jmg.2008.064063 · Cited by 87
Concise Review: Induced Pluripotent Stem Cell Research in the Era of Precision Medicine
Hamazaki, T., Rouby, N. M. E., Fredette, N. C., Santostefano, K. E., & Terada, N. (2017) · Stem Cells · doi:10.1002/stem.2570 · Cited by 87
Toward an integrated pipeline for protein biomarker development
Drabovich, A. P., Martínez‐Morillo, E., & Diamandis, E. P. (2014) · Biochimica et Biophysica Acta (BBA) - Proteins and Proteomics · doi:10.1016/j.bbapap.2014.09.006 · Cited by 86
Genomic convergence and network analysis approach to identify candidate genes in Alzheimer's disease
Talwar, P., Silla, Y., Grover, S., Gupta, M., Agarwal, R., Kushwaha, S. S., & Kukreti, R. (2014) · BMC Genomics · doi:10.1186/1471-2164-15-199 · Cited by 86
Hsieh, P., Vollger, M. R., Dang, V., Porubskỳ, D., Baker, C. A., Cantsilieris, S., Hoekzema, K., Lewis, A. P., Munson, K. M., Sorensen, M., et al. (2019) · Science · doi:10.1126/science.aax2083 · Cited by 86
A gene‐based SNP linkage map for pacific white shrimp, Litopenaeus vannamei
Du, Z. ‐., Ciobanu, D. C., Onteru, S. K., Gorbach, D. M., Mileham, A. J., Jaramillo, G., & Rothschild, M. F. (2009) · Animal Genetics · doi:10.1111/j.1365-2052.2009.02002.x · Cited by 86
DNA variations in human and medical genetics: 25 years of my experience
Nakamura, Y. (2009) · Journal of Human Genetics · doi:10.1038/jhg.2008.6 · Cited by 86
Phillips, C., Ballard, D., Gill, P., Court, D. S., Carracedo, Á., & Lareu, M. V. (2011) · Forensic Science International Genetics · doi:10.1016/j.fsigen.2011.07.012 · Cited by 86
Detecting and Characterizing Genomic Signatures of Positive Selection in Global Populations
Liu, X., Ong, R. T., Pillai, N. E., Elzein, A., Small, K. S., Clark, T. G., Kwiatkowski, D. P., & Teo, Y.-Y. (2013) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2013.04.021 · Cited by 86
Li, X., Bykhovskaya, Y., Canedo, A. L., Haritunians, T., Siscovick, D. S., Aldave, A. J., Szczotka‐Flynn, L. B., Iyengar, S. K., Rotter, J. I., Taylor, K. D., et al. (2013) · Investigative Ophthalmology & Visual Science · doi:10.1167/iovs.13-11601 · Cited by 86
Insights into Pancreatic Cancer Etiology from Pathway Analysis of Genome-Wide Association Study Data
Wei, P., Tang, H., & Li, D. (2012) · PLoS ONE · doi:10.1371/journal.pone.0046887 · Cited by 86
Osteoarthritis: a problem of growth not decay?
Aspden, R. M. (2008) · Rheumatology · doi:10.1093/rheumatology/ken199 · Cited by 86
Detection and correction of false segmental duplications caused by genome mis-assembly
Kelley, D. R., & Salzberg, S. L. (2010) · Genome biology · doi:10.1186/gb-2010-11-3-r28 · Cited by 86
Signatures of Purifying and Local Positive Selection in Human miRNAs
Quach, H., Barreiro, L. B., Laval, G., Zidane, N., Patin, E., Kidd, K. K., Kidd, J. R., Bouchier, C., Veuille, M., Antoniewski, C., et al. (2009) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2009.01.022 · Cited by 85
Genetics of Coronary Artery Disease
Musunuru, K., & Kathiresan, S. (2010) · Annual Review of Genomics and Human Genetics · doi:10.1146/annurev-genom-082509-141637 · Cited by 85
Seidman, D. N., Shenoy, S. A., Kim, M., Babu, R. K., Woods, I. G., Dyer, T. D., Lehman, D. M., Curran, J. E., Duggirala, R., Blangero, J., et al. (2020) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2020.02.012 · Cited by 85
Recombination affects accumulation of damaging and disease-associated mutations in human populations
Hussin, J., Hodgkinson, A., Idaghdour, Y., Grenier, J., Goulet, J.-P., Gbeha, E., Hip-Ki, E., & Awadalla, P. (2015) · Nature Genetics · doi:10.1038/ng.3216 · Cited by 85
Understanding cardiovascular disease through the lens of genome-wide association studies
Arking, D. E., & Chakravarti, A. (2009) · Trends in Genetics · doi:10.1016/j.tig.2009.07.007 · Cited by 85
Zhang, W., Duan, S., Bleibel, W. K., Wisel, S. A., Huang, R. S., Wu, X., He, L., Clark, T. A., Chen, T. X., Schweitzer, A. C., et al. (2008) · Human Genetics · doi:10.1007/s00439-008-0601-x · Cited by 85
Li, H., Reksten, T. R., Ice, J. A., Kelly, J. A., Adrianto, I., Rasmussen, A., Wang, S., He, B., Grundahl, K. M., Glenn, S. B., et al. (2017) · PLoS Genetics · doi:10.1371/journal.pgen.1006820 · Cited by 84
Harris, A. M., Garud, N. R., & DeGiorgio, M. (2018) · Genetics · doi:10.1534/genetics.118.301502 · Cited by 87
McCrae, R. R., Scally, M., Terracciano, A., Abecasis, G. R., & Costa, P. T. (2010) · Journal of Personality and Social Psychology · doi:10.1037/a0020964 · Cited by 84
Smith, K. R., Bromhead, C. J., Hildebrand, M. S., Shearer, A. E., Lockhart, P. J., Najmabadi, H., Leventer, R. J., McGillivray, G., Amor, D. J., Smith, R. J., et al. (2011) · Genome biology · doi:10.1186/gb-2011-12-9-r85 · Cited by 84
FORGe: prioritizing variants for graph genomes
Pritt, J., Chen, N.-C., & Langmead, B. (2018) · Genome biology · doi:10.1186/s13059-018-1595-x · Cited by 84
Polygenic architecture informs potential vulnerability to drug-induced liver injury
Koido, M., Kawakami, E., Fukumura, J., Noguchi, Y., Ohori, M., Nio, Y., Nicoletti, P., Aithal, G. P., Daly, A. K., Watkins, P. B., et al. (2020) · Nature Medicine · doi:10.1038/s41591-020-1023-0 · Cited by 84
Xie, S., Ji, Z., Suo, T., Li, B., & Zhang, X. (2021) · Analytica Chimica Acta · doi:10.1016/j.aca.2021.338848 · Cited by 84
Receptor Polymorphism and Genomic Structure Interact to Shape Bitter Taste Perception
Roudnitzky, N., Behrens, M., Engel, A., Kohl, S., Thalmann, S., Hübner, S., Lossow, K., Wooding, S., & Meyerhof, W. (2015) · PLoS Genetics · doi:10.1371/journal.pgen.1005530 · Cited by 84
Fareed, M., & Afzal, M. (2012) · Egyptian Journal of Medical Human Genetics · doi:10.1016/j.ejmhg.2012.08.001 · Cited by 84
Alzheimer Disease Susceptibility Loci: Evidence for a Protein Network under Natural Selection
Raj, T., Shulman, J. M., Keenan, B. T., Chibnik, L. B., Evans, D. A., Bennett, D. A., Stranger, B. E., & Jager, P. L. D. (2012) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2012.02.022 · Cited by 84
Global Genomic Characterization of Acute Lymphoblastic Leukemia
Mullighan, C. G., & Downing, J. R. (2008) · Seminars in Hematology · doi:10.1053/j.seminhematol.2008.09.005 · Cited by 84
Functional Organization of the Genome May Shape the Species Boundary in the House Mouse
Janoušek, V., Munclinger, P., Wang, L., Teeter, K. C., & Tucker, P. K. (2015) · Molecular Biology and Evolution · doi:10.1093/molbev/msv011 · Cited by 84
From SNPs to Genes: Disease Association at the Gene Level
Lehne, B. C., Lewis, C. M., & Schlitt, T. (2011) · PLoS ONE · doi:10.1371/journal.pone.0020133 · Cited by 84
Genes, physical fitness and ageing
Garatachea, N., & Lucía, A. (2012) · Ageing Research Reviews · doi:10.1016/j.arr.2012.09.003 · Cited by 84
Positive Selection in the Human Genome: From Genome Scans to Biological Significance
Kelley, J. L., & Swanson, W. J. (2008) · Annual Review of Genomics and Human Genetics · doi:10.1146/annurev.genom.9.081307.164411 · Cited by 84
Mu, X. J., Lu, Z. J., Kong, Y., Lam, H. Y. K., & Gerstein, M. (2011) · Nucleic Acids Research · doi:10.1093/nar/gkr342 · Cited by 84
Functional genetic variation of human miRNAs and phenotypic consequences
Borel, C., & Antonarakis, S. E. (2008) · Mammalian Genome · doi:10.1007/s00335-008-9137-6 · Cited by 83
Lessard, C. J., Adrianto, I., Kelly, J. A., Kaufman, K. M., Grundahl, K. M., Adler, A., Williams, A. H., Gallant, C. J., Anaya, J., Bae, S., et al. (2010) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2010.11.014 · Cited by 83
Fagny, M., Patin, É., Enard, D., Barreiro, L. B., Quintana‐Murci, L., & Laval, G. (2014) · Molecular Biology and Evolution · doi:10.1093/molbev/msu118 · Cited by 83
Distinct germ line polymorphisms underlie glioma morphologic heterogeneity
Jenkins, R. B., Wrensch, M., Johnson, D. R., Fridley, B. L., Decker, P. A., Xiao, Y., Kollmeyer, T. M., Rynearson, A. L., Fink, S. R., Rice, T., et al. (2011) · Cancer Genetics · doi:10.1016/j.cancergencyto.2010.10.002 · Cited by 83
Genetic and epigenetic variants influencing the development of nonalcoholic fatty liver disease
Li, Y. (2012) · World Journal of Gastroenterology · doi:10.3748/wjg.v18.i45.6546 · Cited by 83
Lesecque, Y., Glémin, S., Lartillot, N., Mouchiroud, D., & Duret, L. (2014) · PLoS Genetics · doi:10.1371/journal.pgen.1004790 · Cited by 83
MEP1A allele for meprin A metalloprotease is a susceptibility gene for inflammatory bowel disease
Banerjee, S., Oneda, B., Yap, L. M., Jewell, D. P., Matters, G. L., Fitzpatrick, L. R., Seibold, F., Sterchi, E. E., Ahmad, T., Lottaz, D., et al. (2009) · Mucosal Immunology · doi:10.1038/mi.2009.3 · Cited by 83
PhosSNP for Systematic Analysis of Genetic Polymorphisms That Influence Protein Phosphorylation
Ren, J. M., Jiang, C., Gao, X., Liu, Z., Yuan, Z., Jin, C., Wen, L., Zhang, Z., Xue, Y., & Yao, X. (2009) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m900273-mcp200 · Cited by 83
Sequence and Structure Signatures of Cancer Mutation Hotspots in Protein Kinases
Dixit, A., Yi, L., Gowthaman, R., Torkamani, A., Schork, N. J., & Verkhivker, G. M. (2009) · PLoS ONE · doi:10.1371/journal.pone.0007485 · Cited by 83
Huang, Y. Y., Hidalgo‐Bravo, A., Zhang, E., Cotton, V. E., Méndez-Bermúdez, A., Wig, G., Medina-Calzada, Z., Neumann, R., Jeffreys, A. J., WINNEY, B. J., et al. (2013) · Nucleic Acids Research · doi:10.1093/nar/gkt840 · Cited by 83
Major Population Expansion of East Asians Began before Neolithic Time: Evidence of mtDNA Genomes
Zheng, H., Yan, S. L., Qin, Z., Wang, Y., Tan, J., Li, H., & Li, J. (2011) · PLoS ONE · doi:10.1371/journal.pone.0025835 · Cited by 83
Richmond, R. C., Timpson, N. J., Felix, J. F., Palmer, T., Gaillard, R., McMahon, G., Smith, G. D., Jaddoe, V. W. V., & Lawlor, D. A. (2017) · PLoS Medicine · doi:10.1371/journal.pmed.1002221 · Cited by 83
Halvorsen, M., Huh, R., Oskolkov, N., Wen, J., Netotea, S., Giusti‐Rodríguez, P., Karlsson, R., Bryois, J., Nystedt, B., Ameur, A., et al. (2020) · Nature Communications · doi:10.1038/s41467-020-15707-w · Cited by 83
A comprehensively molecular haplotype-resolved genome of a European individualPreprint
Suk, E.-K., McEwen, G. K., Duitama, J., Nowick, K., Schulz, S., Palczewski, S., Schreiber, S., Holloway, D. T., McLaughlin, S., Peckham, H. E., et al. (2011) · Genome Research · doi:10.1101/gr.125047.111 · Cited by 83
The Genetics of Major Depression
Flint, J., & Kendler, K. S. (2014) · Neuron · doi:10.1016/j.neuron.2014.02.033 · Cited by 81
Cheng, L., Zhuang, H., Yang, S., Jiang, H., Wang, S., & Zhang, J. (2018) · Frontiers in Genetics · doi:10.3389/fgene.2018.00657 · Cited by 82
Mani, P., Yadav, V. K., Das, S. K., & Chowdhury, S. (2009) · PLoS ONE · doi:10.1371/journal.pone.0004399 · Cited by 82
Creary, L. E., Ulug, P., Menzel, S., McKenzie, C. A., Hanchard, N. A., Taylor, V., Farrall, M., Forrester, T. E., & Thein, S. L. (2009) · PLoS ONE · doi:10.1371/journal.pone.0004218 · Cited by 82
Direct Detection of Point Mutations in Nonamplified Human Genomic DNA
D’Agata, R., Breveglieri, G., Zanoli, L. M., Borgatti, M., Spoto, G., & Gambari, R. (2011) · Analytical Chemistry · doi:10.1021/ac2021932 · Cited by 82
Genomic and genealogical investigation of the French Canadian founder population structure
Roy‐Gagnon, M., Moreau, C., Bhérer, C., St-Onge, P., Sinnett, D., Laprise, C., Vézina, H., & Labuda, D. (2011) · Human Genetics · doi:10.1007/s00439-010-0945-x · Cited by 82
Bossé, Y., Bacot, F., Montpetit, A., Rung, J., Qu, H., Engert, J. C., Polychronakos, C., Hudson, T. J., Froguel, P., SLADEK, R. M., et al. (2009) · Human Genetics · doi:10.1007/s00439-009-0626-9 · Cited by 82
Genetic evidence for the involvement of lipid metabolism in Alzheimer's disease
Jones, L., Harold, D. H., & Williams, J. H. (2010) · Biochimica et Biophysica Acta (BBA) - Molecular and Cell Biology of Lipids · doi:10.1016/j.bbalip.2010.04.005 · Cited by 82
A Survey on Latent Tree Models and Applications
Mourad, R., Sinoquet, C., Zhang, N. L., Liu, T., & Leray, P. (2013) · Journal of Artificial Intelligence Research · doi:10.1613/jair.3879 · Cited by 82
IL12A, MPHOSPH9/CDK2AP1 and RGS1 are novel multiple sclerosis susceptibility loci
(IMSGC), T. I. M. S. G. C. (2010) · Genes and Immunity · doi:10.1038/gene.2010.28 · Cited by 84
Obesity and eating behavior from the perspective of twin and genetic research
Silventoinen, K., & Konttinen, H. (2020) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2019.12.012 · Cited by 80
Metadata
- Authors
- The International HapMap Consortium
- Venue
- Nature
- Published
- 2007-10
- Volume
- 449
- Issue
- 7164
- Pages
- 851-861
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- PMC
- PMC2689609
- OpenAlex
- W2119279196
- Cited by
- 4,438
- References
- 60
- Citations by year
- 2026: 53 · 2025: 67 · 2024: 77 · 2023: 71 · 2022: 114 · 2021: 129 · 2020: 111 · 2019: 133 · 2018: 150 · 2017: 153 · 2016: 162 · 2015: 232 · 2014: 275 · 2013: 317 · 2012: 412
- FWCI
- 270.06
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Nature (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Cold Spring Harbor Laboratory Institutional Repository (Cold Spring Harbor Laboratory) (acceptedVersion)
- Deep Blue (University of Michigan) (submittedVersion)
- Rare & Special e-Zone (The Hong Kong University of Science and Technology) (submittedVersion)
- The HKU Scholars Hub (University of Hong Kong) (submittedVersion)
- Leicester Research Archive (University of Leicester) (submittedVersion)
- Funders
- W. M. Keck Foundation
- Genome Canada
- Wellcome Trust (081682, 077011, 077008, 077046)
- Ministry of Education, Culture, Sports, Science and Technology
- National Natural Science Foundation of China
- University Grants Committee
- Chinese Academy of Sciences
- Beijing Normal University
- Ministry of Science and Technology of the People's Republic of China
- Innovation and Technology Commission
- National Institutes of Health
- Engineering and Physical Sciences Research Council
- National Institute on Alcohol Abuse and Alcoholism
- National Institute on Aging
- National Institute of Mental Health
- National Institute on Drug Abuse
- National Human Genome Research Institute
- National Eye Institute
- National Cancer Institute
- National Institute on Deafness and Other Communication Disorders
- National Institute of General Medical Sciences
- National Institute of Allergy and Infectious Diseases
- National Institute of Diabetes and Digestive and Kidney Diseases
- National Institute of Neurological Disorders and Stroke
- National Institute of Environmental Health Sciences
- National Institute of Arthritis and Musculoskeletal and Skin Diseases
- National Institute of Biomedical Imaging and Bioengineering
- National Institute of Dental and Craniofacial Research
- National Center for Research Resources
- 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
- single nucleotide polymorphisms, linkage disequilibrium, SNP genotyping, imputation, recombination hotspots, recombination rate, genetic differentiation, natural selection, non-synonymous SNPs, genetic ancestry, genome-wide association study, Lassa virus, skin pigmentation, hair follicle development
- MeSH terms
- Female, Haplotypes, Homozygote, Humans, Male, Recombination, Genetic, Selection, Genetic, Linkage Disequilibrium, Polymorphism, Single Nucleotide, Racial Groups
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
