The DOI matches its Crossref record; 15 of the 15 references it cites were found in a registry or an index.
Genotype imputation for genome-wide association studies
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.
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
Statistical Analysis with Missing Data
Little, R. J. A., & Rubin, D. B. (2002) · Wiley Series in Probability and Statistics · doi:10.1002/9781119013563 · Cited by 8,473
A second generation human haplotype map of over 3.1 million SNPs
The International HapMap Consortium (2007) · Nature · doi:10.1038/nature06258 · Cited by 4,438
Howie, B. N., Donnelly, P., & Marchini, J. (2009) · PLoS Genetics · doi:10.1371/journal.pgen.1000529 · Cited by 3,928
Self-citationA new multipoint method for genome-wide association studies by imputation of genotypes
Marchini, J., Howie, B., Myers, S., McVean, G., & Donnelly, P. (2007) · Nature Genetics · doi:10.1038/ng2088 · Cited by 2,609
Self-citationReplication of Genome-Wide Association Signals in UK Samples Reveals Risk Loci for Type 2 Diabetes
Zeggini, E., Weedon, M. N., Lindgren, C. M., Frayling, T. M., Elliott, K. S., Lango, H., Timpson, N. J., Perry, J. R. B., Rayner, N. W., Freathy, R. M., et al. (2007) · Science · doi:10.1126/science.1142364 · Cited by 2,194
Self-citationMaximum-likelihood estimation of molecular haplotype frequencies in a diploid population.
(1995) · Molecular Biology and Evolution · doi:10.1093/oxfordjournals.molbev.a040269 · Cited by 1,950
Browning, B. L., & Browning, S. R. (2009) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2009.01.005 · Cited by 1,640
Common variants near MC4R are associated with fat mass, weight and risk of obesity
The Prostate, L., Loos, R. J. F., KORA, Study, N. H., Initiative, D. G., Study, T. S., The Wellcome Trust Case Control Consortium, FUSION, Lindgren, C. M., Li, S., et al. (2008) · Nature Genetics · doi:10.1038/ng.140 · Cited by 1,325
Self-citationHaplotype tagging for the identification of common disease genes
Johnson, G. C. L., Esposito, L., Barratt, B. J., Smith, A. N., Heward, J., Di Genova, G., Ueda, H., Cordell, H. J., Eaves, I. A., Dudbridge, F., et al. (2001) · Nature Genetics · doi:10.1038/ng1001-233 · Cited by 1,174
Cited by
A map of human genome variation from population-scale sequencing.
The 1000 Genomes Project Consortium (2010) · Nature · doi:10.1038/nature09534 · Cited by 7,877
Giambartolomei, C., Vukcevic, D., Schadt, E. E., Franke, L., Hingorani, A. D., Wallace, C., & Plagnol, V. (2014) · PLoS Genetics · doi:10.1371/journal.pgen.1004383 · Cited by 4,261
Next-generation genotype imputation service and methods
Das, S., Forer, L., Schönherr, S., Sidore, C., Locke, A. E., Kwong, A., Vrieze, S. I., Chew, E. Y., Levy, S., McGue, M., et al. (2016) · Nature Genetics · doi:10.1038/ng.3656 · Cited by 3,808
A reference panel of 64,976 haplotypes for genotype imputation
the Haplotype Reference Consortium (2016) · Nature Genetics · doi:10.1038/ng.3643 · Cited by 2,836
A linear complexity phasing method for thousands of genomes
Delaneau, O., Marchini, J., & Zagury, J.-F. (2012) · Nature Methods · doi:10.1038/nmeth.1785 · Cited by 1,850
Self-citationFast and accurate genotype imputation in genome-wide association studies through pre-phasing
Howie, B., Fuchsberger, C., Stephens, M., Marchini, J., & Abecasis, G. R. (2012) · Nature Genetics · doi:10.1038/ng.2354 · Cited by 1,737
Self-citationGenotype and SNP calling from next-generation sequencing data
Nielsen, R., Paul, J. S., Albrechtsen, A., & Song, Y. S. (2011) · Nature Reviews Genetics · doi:10.1038/nrg2986 · Cited by 1,396
Analysis of immune-related loci identifies 48 new susceptibility variants for multiple sclerosis
International Multiple Sclerosis Genetics Consortium (IMSGC) (2013) · Nature Genetics · doi:10.1038/ng.2770 · Cited by 1,386
Leveraging Polygenic Functional Enrichment to Improve GWAS Power
Kichaev, G., Bhatia, G., Loh, P.-R., Gazal, S., Burch, K., Freund, M. K., Schoech, A., Pasaniuc, B., & Price, A. L. (2019) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2018.11.008 · Cited by 926
Pleiotropy in complex traits: challenges and strategies
Solovieff, N., Cotsapas, C., Lee, P. H., Purcell, S. M., & Smoller, J. W. (2013) · Nature Reviews Genetics · doi:10.1038/nrg3461 · Cited by 1,085
Rare-Variant Association Analysis: Study Designs and Statistical Tests
Lee, S., Abecasis, G. R., Boehnke, M., & Lin, X. (2014) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2014.06.009 · Cited by 1,042
Genotype Imputation with Thousands of Genomes
Howie, B., Marchini, J., & Stephens, M. (2011) · G3 Genes|Genomes|Genetics · doi:10.1534/g3.111.001198 · Cited by 966
Self-citationHartwig, F. P., Davies, N. M., Hemani, G., & Davey Smith, G. (2016) · International Journal of Epidemiology · doi:10.1093/ije/dyx028 · Cited by 860
Genome-wide association study identifies multiple susceptibility loci for pulmonary fibrosis
Fingerlin, T. E., Murphy, E., Zhang, W., Peljto, A. L., Brown, K. K., Steele, M. P., Loyd, J. E., Cosgrove, G. P., Lynch, D., Groshong, S., et al. (2013) · Nature Genetics · doi:10.1038/ng.2609 · Cited by 809
Innate Immune Activity Conditions the Effect of Regulatory Variants upon Monocyte Gene Expression
Fairfax, B. P., Humburg, P., Makino, S., Naranbhai, V., Wong, D., Lau, E., Jostins, L., Plant, K., Andrews, R., McGee, C., et al. (2014) · Science · doi:10.1126/science.1246949 · Cited by 764
Ahola-Olli, A. V., Würtz, P., Havulinna, A. S., Aalto, K., Pitkänen, N., Lehtimäki, T., Kähönen, M., Lyytikäinen, L.-P., Raitoharju, E., Seppälä, I., et al. (2017) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2016.11.007 · Cited by 628
Meta-analysis methods for genome-wide association studies and beyond
Evangelou, E., & Ioannidis, J. P. A. (2013) · Nature Reviews Genetics · doi:10.1038/nrg3472 · Cited by 596
The MHC locus and genetic susceptibility to autoimmune and infectious diseases
Matzaraki, V., Kumar, V., Wijmenga, C., & Zhernakova, A. (2017) · Genome biology · doi:10.1186/s13059-017-1207-1 · Cited by 566
Partitioning Heritability of Regulatory and Cell-Type-Specific Variants across 11 Common Diseases
Gusev, A., Lee, S. H., Trynka, G., Finucane, H., Vilhjálmsson, B. J., Xu, H., Zang, C., Ripke, S., Bulik-Sullivan, B., Stahl, E., et al. (2014) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2014.10.004 · Cited by 544
Mahajan, A., Wessel, J., Willems, S. M., Zhao, W., Robertson, N. R., Chu, A. Y., Gan, W., Kitajima, H., Taliun, D., Rayner, N. W., et al. (2018) · Nature Genetics · doi:10.1038/s41588-018-0084-1 · Cited by 442
Self-citationLotta, L. A., Scott, R. A., Sharp, S. J., Burgess, S., Luan, J., Tillin, T., Schmidt, A. F., Imamura, F., Stewart, I. D., Perry, J. R. B., et al. (2016) · PLOS Medicine · doi:10.1371/journal.pmed.1002179 · Cited by 417
Fast and accurate long-range phasing in a UK Biobank cohort
Loh, P.-R., Palamara, P. F., & Price, A. L. (2016) · Nature Genetics · doi:10.1038/ng.3571 · Cited by 342
Genome‐wide meta‐analysis identifies novel multiple sclerosis susceptibility loci
Patsopoulos, N. A., the Bayer Pharma MS Genetics Working Group, T. S. C. O. S. E. I. A. A. C., & de Bakker, P. I. W. (2011) · Annals of Neurology · doi:10.1002/ana.22609 · Cited by 353
Transethnic Genetic-Correlation Estimates from Summary Statistics
Brown, B. C., Ye, C. J., Price, A. L., & Zaitlen, N. (2016) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2016.05.001 · Cited by 340
Liu, S., Huang, S., Chen, F., Zhao, L., Yuan, Y., Francis, S. S., Fang, L., Li, Z., Lin, L., Liu, R., et al. (2018) · Cell · doi:10.1016/j.cell.2018.08.016 · Cited by 279
Robertson, C. C., Inshaw, J. R. J., Onengut-Gumuscu, S., Chen, W.-M., Santa Cruz, D. F., Yang, H., Cutler, A. J., Crouch, D. J. M., Farber, E., Bridges, S. L., et al. (2021) · Nature Genetics · doi:10.1038/s41588-021-00880-5 · Cited by 302
Lane, J. M., Vlasac, I., Anderson, S. G., Kyle, S. D., Dixon, W. G., Bechtold, D. A., Gill, S., Little, M. A., Luik, A., Loudon, A., et al. (2016) · Nature Communications · doi:10.1038/ncomms10889 · Cited by 312
Extremely low-coverage sequencing and imputation increases power for genome-wide association studies
Pasaniuc, B., Rohland, N., McLaren, P. J., Garimella, K., Zaitlen, N., Li, H., Gupta, N., Neale, B. M., Daly, M. J., Sklar, P., et al. (2012) · Nature Genetics · doi:10.1038/ng.2283 · Cited by 299
Naveed, M., Ayday, E., Clayton, E. W., Fellay, J., Gunter, C. A., Hubaux, J.-P., Malin, B. A., & Wang, X. (2015) · ACM Computing Surveys · doi:10.1145/2767007 · Cited by 261
Genome-wide meta-analysis identifies five new susceptibility loci for pancreatic cancer
Klein, A. P., Wolpin, B. M., Risch, H. A., Stolzenberg-Solomon, R. Z., Mocci, E., Zhang, M., Canzian, F., Childs, E. J., Hoskins, J. W., Jermusyk, A., et al. (2018) · Nature Communications · doi:10.1038/s41467-018-02942-5 · Cited by 268
Li, Y. R., & Keating, B. J. (2014) · Genome Medicine · doi:10.1186/s13073-014-0091-5 · Cited by 214
Adhikari, K., Fuentes-Guajardo, M., Quinto-Sánchez, M., Mendoza-Revilla, J., Camilo Chacón-Duque, J., Acuña-Alonzo, V., Jaramillo, C., Arias, W., Lozano, R. B., Pérez, G. M., et al. (2016) · Nature Communications · doi:10.1038/ncomms11616 · Cited by 200
Naj, A. C., Jun, G., Reitz, C., Kunkle, B. W., Perry, W., Park, Y. S., Beecham, G. W., Rajbhandary, R. A., Hamilton-Nelson, K. L., Wang, L.-S., et al. (2014) · JAMA Neurology · doi:10.1001/jamaneurol.2014.1491 · Cited by 185
Comprehensive literature review and statistical considerations for GWAS meta-analysis
Begum, F., Ghosh, D., Tseng, G. C., & Feingold, E. (2012) · Nucleic Acids Research · doi:10.1093/nar/gkr1255 · Cited by 179
Saxena, R., Saleheen, D., Been, L. F., Garavito, M. L., Braun, T., Bjonnes, A., Young, R., Ho, W. K., Rasheed, A., Frossard, P., et al. (2013) · Diabetes · doi:10.2337/db12-1077 · Cited by 185
Progress and promise in understanding the genetic basis of common diseases
Price, A. L., Spencer, C. C. A., & Donnelly, P. (2015) · Proceedings of the Royal Society B: Biological Sciences · doi:10.1098/rspb.2015.1684 · Cited by 147
Common variants associated with general and MMR vaccine–related febrile seizures
Feenstra, B., Pasternak, B., Geller, F., Carstensen, L., Wang, T., Huang, F., Eitson, J. L., Hollegaard, M. V., Svanström, H., Vestergaard, M., et al. (2014) · Nature Genetics · doi:10.1038/ng.3129 · Cited by 152
Luo, Y., de Lange, K. M., Jostins, L., Moutsianas, L., Randall, J., Kennedy, N. A., Lamb, C. A., McCarthy, S., Ahmad, T., Edwards, C., et al. (2017) · Nature Genetics · doi:10.1038/ng.3761 · Cited by 162
Gazal, S., Loh, P.-R., Finucane, H. K., Ganna, A., Schoech, A., Sunyaev, S., & Price, A. L. (2018) · Nature Genetics · doi:10.1038/s41588-018-0231-8 · Cited by 154
Jorgenson, E., Thai, K. K., Hoffmann, T. J., Sakoda, L. C., Kvale, M. N., Banda, Y., Schaefer, C., Risch, N., Mertens, J., Weisner, C., et al. (2017) · Molecular Psychiatry · doi:10.1038/mp.2017.101 · Cited by 136
Ruth, K. S., Campbell, P. J., Chew, S., Lim, E. M., Hadlow, N., Stuckey, B. G., Brown, S. J., Feenstra, B., Joseph, J., Surdulescu, G. L., et al. (2016) · European Journal of Human Genetics · doi:10.1038/ejhg.2015.102 · Cited by 121
How to Include Chromosome X in Your Genome‐Wide Association Study
König, I. R., Loley, C., Erdmann, J., & Ziegler, A. (2014) · Genetic Epidemiology · doi:10.1002/gepi.21782 · Cited by 113
Common variant at 16p11.2 conferring risk of psychosis
Steinberg, S., de Jong, S., Mattheisen, M., Costas, J., Demontis, D., Jamain, S., Pietiläinen, O. P. H., Lin, K., Papiol, S., Huttenlocher, J., et al. (2014) · Molecular Psychiatry · doi:10.1038/mp.2012.157 · Cited by 104
Blood CSF1 and CXCL12 as Causal Mediators of Coronary Artery Disease
Sjaarda, J., Gerstein, H., Chong, M., Yusuf, S., Meyre, D., Anand, S. S., Hess, S., & Paré, G. (2018) · Journal of the American College of Cardiology · doi:10.1016/j.jacc.2018.04.067 · Cited by 94
Hancock, D. B., Reginsson, G. W., Gaddis, N. C., Chen, X., Saccone, N. L., Lutz, S. M., Qaiser, B., Sherva, R., Steinberg, S., Zink, F., et al. (2015) · Translational Psychiatry · doi:10.1038/tp.2015.149 · Cited by 85
Ojha, J., Codd, V., Nelson, C. P., Samani, N. J., Smirnov, I. V., Madsen, N. R., Hansen, H. M., de Smith, A. J., Bracci, P. M., Wiencke, J. K., et al. (2016) · Cancer Epidemiology, Biomarkers & Prevention · doi:10.1158/1055-9965.epi-15-1329 · Cited by 71
Genetic study of multimodal imaging Alzheimer’s disease progression score implicates novel loci
Scelsi, M. A., Khan, R. R., Lorenzi, M., Christopher, L., Greicius, M. D., Schott, J. M., Ourselin, S., & Altmann, A. (2018) · Brain · doi:10.1093/brain/awy141 · Cited by 73
Guan, F., Niu, Y., Zhang, T., Liu, S., Ma, L., Qi, T., Feng, J., Zuo, H., Li, G., Liu, X., et al. (2016) · Scientific Reports · doi:10.1038/srep29586 · Cited by 72
A genome-wide association study for extremely high intelligence
Zabaneh, D., Krapohl, E., Gaspar, H. A., Curtis, C., Lee, S. H., Patel, H., Newhouse, S., Wu, H. M., Simpson, M. A., Putallaz, M., et al. (2018) · Molecular Psychiatry · doi:10.1038/mp.2017.121 · Cited by 71
Sliz, E., Kalaoja, M., Ahola-Olli, A., Raitakari, O., Perola, M., Salomaa, V., Lehtimäki, T., Karhu, T., Viinamäki, H., Salmi, M., et al. (2019) · Journal of Medical Genetics · doi:10.1136/jmedgenet-2018-105965 · Cited by 60
Haddick, P. C. G., Alzheimer’s Disease Genetic Consortium (ADGC), A. D. N. I. (., Larson, J. L., Rathore, N., Bhangale, T. R., Phung, Q. T., Srinivasan, K., Hansen, D. V., Lill, J. R., Pericak-Vance, M. A., et al. (2017) · Journal of Alzheimer's Disease · doi:10.3233/jad-160524 · Cited by 55
Sharp, S. I., McQuillin, A., Marks, M., Hunt, S. P., Stanford, S. C., Lydall, G. J., Morgan, M. Y., Asherson, P., Curtis, D., & Gurling, H. M. D. (2014) · American Journal of Medical Genetics Part B: Neuropsychiatric Genetics · doi:10.1002/ajmg.b.32241 · Cited by 52
Enrichment pathway analysis. The inflammatory genetic background in Bipolar Disorder
Drago, A., Crisafulli, C., Calabrò, M., & Serretti, A. (2015) · Journal of Affective Disorders · doi:10.1016/j.jad.2015.03.032 · Cited by 47
Batai, K., Cui, Z., Arora, A., Shah-Williams, E., Hernandez, W., Ruden, M., Hollowell, C. M. P., Hooker, S. E., Bathina, M., Murphy, A. B., et al. (2021) · PLOS Genetics · doi:10.1371/journal.pgen.1009319 · Cited by 28
Dannemann, M., Milaneschi, Y., Yermakovich, D., Stiglbauer, V., Kariis, H. M., Krebs, K., Friese, M. A., Otte, C., Estonian Biobank Research Team, Esko, T., et al. (2022) · Translational Psychiatry · doi:10.1038/s41398-022-02196-2 · Cited by 23
“Genomewide association analyses assuming an additive model were carried out using SNPTEST [28].”
MethodZhang, H., Zhang, Y., Wang, Y.-F., Morris, D., Hirankarn, N., Sheng, Y., Shen, J., Pan, H.-F., Yang, J., Yang, S., et al. (2018) · Arthritis Research & Therapy · doi:10.1186/s13075-018-1590-3 · Cited by 25
Kap, E. J., Seibold, P., Richter, S., Scherer, D., Habermann, N., Balavarca, Y., Jansen, L., Becker, N., Pfütze, K., Popanda, O., et al. (2015) · The Pharmacogenomics Journal · doi:10.1038/tpj.2015.8 · Cited by 20
Social-Science Genomics: Progress, Challenges, and Future Directions
Benjamin, D., Cesarini, D., Turley, P., & Young, A. S. (2024) · doi:10.3386/w32404 · Cited by 20
Chen, Y., & Chen, W. (2022) · Journal of Investigative Dermatology · doi:10.1016/j.jid.2022.04.021 · Cited by 19
Salvatore, J. E., Meyers, J. L., Yan, J., Aliev, F., Lansford, J. E., Pettit, G. S., Bates, J. E., Dodge, K. A., Rose, R. J., Pulkkinen, L., et al. (2015) · Journal of Abnormal Psychology · doi:10.1037/abn0000066 · Cited by 17
Rapid, Reference-Free human genotype imputation with denoising autoencoders
Dias, R., Evans, D., Chen, S.-F., Chen, K.-Y., Loguercio, S., Chan, L., & Torkamani, A. (2022) · eLife · doi:10.7554/elife.75600 · Cited by 16
Metadata
- Authors
- Marchini, J., & Howie, B.
- Venue
- Nature Reviews Genetics
- Published
- 2010-06-02
- Volume
- 11
- Issue
- 7
- Pages
- 499-511
- ISSN
- 1471-0056 (ISSN-L)
- 1471-0064
- OpenAlex
- W2087036932
- Cited by
- 1,627
- References
- 15
- FWCI
- 6.62
- Type
- journal article
- Language
- en
- Open access
- closed
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
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
