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A Versatile Gene-Based Test for Genome-wide Association Studies
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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
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
Hindorff, L. A., Sethupathy, P., Junkins, H. A., Ramos, E. M., Mehta, J. P., Collins, F. S., & Manolio, T. A. (2009) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0903103106 · Cited by 4,013
Gene Ontology Analysis of GWA Study Data Sets Provides Insights into the Biology of Bipolar Disorder
Holmans, P., Green, E. K., Pahwa, J. S., Ferreira, M. A. R., Purcell, S. M., Sklar, P., Owen, M. J., O'Donovan, M. C., & Craddock, N. (2009) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2009.05.011 · Cited by 378
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10 Years of GWAS Discovery: Biology, Function, and Translation
Visscher, P. M., Wray, N. R., Zhang, Q., Sklar, P., McCarthy, M. I., Brown, M. A., & Yang, J. (2017) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2017.06.005 · Cited by 3,719
Self-citationMAGMA: Generalized Gene-Set Analysis of GWAS Data
de Leeuw, C. A., Mooij, J. M., Heskes, T., & Posthuma, D. (2015) · PLOS Computational Biology · doi:10.1371/journal.pcbi.1004219 · Cited by 3,653
23andMe Research Team, Lee, J. J., COGENT (Cognitive Genomics Consortium), Social Science Genetic Association Consortium, Wedow, R., Okbay, A., Kong, E., Maghzian, O., Zacher, M., Nguyen-Viet, T. A., et al. (2018) · Nature Genetics · doi:10.1038/s41588-018-0147-3 · Cited by 2,470
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Karczewski, K. J., & Snyder, M. P. (2018) · Nature Reviews Genetics · doi:10.1038/nrg.2018.4 · Cited by 1,158
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Yang, J., Manolio, T. A., Pasquale, L. R., Boerwinkle, E., Caporaso, N., Cunningham, J. M., de Andrade, M., Feenstra, B., Feingold, E., Hayes, M. G., et al. (2011) · Nature Genetics · doi:10.1038/ng.823 · Cited by 890
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Greene, C. S., Krishnan, A., Wong, A. K., Ricciotti, E., Zelaya, R. A., Himmelstein, D. S., Zhang, R., Hartmann, B. M., Zaslavsky, E., Sealfon, S. C., et al. (2015) · Nature Genetics · doi:10.1038/ng.3259 · Cited by 832
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Rietveld, C. A., Medland, S. E., Derringer, J., Yang, J., Esko, T., Martin, N. W., Westra, H.-J., Shakhbazov, K., Abdellaoui, A., Agrawal, A., et al. (2013) · Science · doi:10.1126/science.1235488 · Cited by 827
Self-citationReadhead, B., Haure-Mirande, J.-V., Funk, C. C., Richards, M. A., Shannon, P., Haroutunian, V., Sano, M., Liang, W. S., Beckmann, N. D., Price, N. D., et al. (2018) · Neuron · doi:10.1016/j.neuron.2018.05.023 · Cited by 708
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Davies, G., Tenesa, A., Payton, A., Yang, J., Harris, S. E., Liewald, D., Ke, X., Le Hellard, S., Christoforou, A., Luciano, M., et al. (2011) · Molecular Psychiatry · doi:10.1038/mp.2011.85 · Cited by 608
Self-citationThe Autism Spectrum Disorders Working Group of The Psychiatric Genomics Consortium (2017) · Molecular Autism · doi:10.1186/s13229-017-0137-9 · Cited by 587
Wray, N. R., Pergadia, M. L., Blackwood, D. H. R., Penninx, B. W. J. H., Gordon, S. D., Nyholt, D. R., Ripke, S., MacIntyre, D. J., McGhee, K. A., Maclean, A. W., et al. (2012) · Molecular Psychiatry · doi:10.1038/mp.2010.109 · Cited by 444
Self-citationReitz, C., Jun, G., Naj, A., Rajbhandary, R., Vardarajan, B. N., Wang, L.-S., Valladares, O., Lin, C.-F., Larson, E. B., Graff-Radford, N. R., et al. (2013) · JAMA · doi:10.1001/jama.2013.2973 · Cited by 431
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Marbach, D., Lamparter, D., Quon, G., Kellis, M., Kutalik, Z., & Bergmann, S. (2016) · Nature Methods · doi:10.1038/nmeth.3799 · Cited by 326
Davies, G., Armstrong, N., Bis, J. C., Bressler, J., Chouraki, V, Giddaluru, S., Hofer, E., Ibrahim-Verbaas, C. A., Kirin, M., Lahti, J., et al. (2015) · Molecular Psychiatry · doi:10.1038/mp.2014.188 · Cited by 384
de Moor, M. H. M., van den Berg, S. M., Verweij, K. J. H., Krueger, R. F., Luciano, M., Arias Vasquez, A., Matteson, L. K., Derringer, J., Esko, T., Amin, N., et al. (2015) · JAMA Psychiatry · doi:10.1001/jamapsychiatry.2015.0554 · Cited by 345
Porcu, E., Rüeger, S., Lepik, K., eQTLGen Consortium, Agbessi, M., Ahsan, H., Alves, I., Andiappan, A., Arindrarto, W., Awadalla, P., et al. (2019) · Nature Communications · doi:10.1038/s41467-019-10936-0 · Cited by 322
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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
Hill, W. D., Marioni, R. E., Maghzian, O., Ritchie, S. J., Hagenaars, S. P., McIntosh, A. M., Gale, C. R., Davies, G., & Deary, I. J. (2019) · Molecular Psychiatry · doi:10.1038/s41380-017-0001-5 · Cited by 311
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Mishra, A., & Macgregor, S. (2015) · Twin Research and Human Genetics · doi:10.1017/thg.2014.79 · Cited by 257
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He, X., Fuller, C. K., Song, Y., Meng, Q., Zhang, B., Yang, X., & Li, H. (2013) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2013.03.022 · Cited by 241
Cornelis, M. C., Monda, K. L., Yu, K., Paynter, N., Azzato, E. M., Bennett, S. N., Berndt, S. I., Boerwinkle, E., Chanock, S., Chatterjee, N., et al. (2011) · PLoS Genetics · doi:10.1371/journal.pgen.1002033 · Cited by 228
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Jansen, R., Penninx, B. W. J. H., Madar, V, Xia, K., Milaneschi, Y., Hottenga, J. J., Hammerschlag, A. R., Beekman, A., van der Wee, N., Smit, J. H., et al. (2016) · Molecular Psychiatry · doi:10.1038/mp.2015.57 · Cited by 224
Li, Y. R., & Keating, B. J. (2014) · Genome Medicine · doi:10.1186/s13073-014-0091-5 · Cited by 214
Hughes, C. D., Choi, M. L., Ryten, M., Hopkins, L., Drews, A., Botía, J. A., Iljina, M., Rodrigues, M., Gagliano, S. A., Gandhi, S., et al. (2019) · Acta Neuropathologica · doi:10.1007/s00401-018-1907-y · Cited by 177
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Pappa, I., St Pourcain, B., Benke, K., Cavadino, A., Hakulinen, C., Nivard, M. G., Nolte, I. M., Tiesler, C. M. T., Bakermans‐Kranenburg, M. J., Davies, G. E., et al. (2016) · American Journal of Medical Genetics Part B: Neuropsychiatric Genetics · doi:10.1002/ajmg.b.32333 · Cited by 195
Cornelis, M. C., Kacprowski, T., Menni, C., Gustafsson, S., Pivin, E., Adamski, J., Artati, A., Eap, C. B., Ehret, G., Friedrich, N., et al. (2016) · Human Molecular Genetics · doi:10.1093/hmg/ddw334 · Cited by 175
Himmelstein, D. S., & Baranzini, S. E. (2015) · PLOS Computational Biology · doi:10.1371/journal.pcbi.1004259 · Cited by 172
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Bralten, J., Franke, B., Waldman, I., Rommelse, N., Hartman, C., Asherson, P., Banaschewski, T., Ebstein, R. P., Gill, M., Miranda, A., et al. (2013) · Journal of the American Academy of Child & Adolescent Psychiatry · doi:10.1016/j.jaac.2013.08.020 · Cited by 93
Unraveling the Genetic Etiology of Adult Antisocial Behavior: A Genome-Wide Association Study
Tielbeek, J. J., Medland, S. E., Benyamin, B., Byrne, E. M., Heath, A. C., Madden, P. A. F., Martin, N. G., Wray, N. R., & Verweij, K. J. H. (2012) · PLoS ONE · doi:10.1371/journal.pone.0045086 · Cited by 86
Self-citationEfficient pathway enrichment and network analysis of GWAS summary data using GSA-SNP2
Yoon, S., Nguyen, H. C. T., Yoo, Y. J., Kim, J., Baik, B., Kim, S., Kim, J., Kim, S., & Nam, D. (2018) · Nucleic Acids Research · doi:10.1093/nar/gky175 · Cited by 81
Chromosome contacts in activated T cells identify autoimmune disease candidate genes
Burren, O. S., Rubio García, A., Javierre, B.-M., Rainbow, D. B., Cairns, J., Cooper, N. J., Lambourne, J. J., Schofield, E., Castro Dopico, X., Ferreira, R. C., et al. (2017) · Genome Biology · doi:10.1186/s13059-017-1285-0 · Cited by 80
Shared genetic contribution to ischemic stroke and Alzheimer's disease
Traylor, M., Adib‐Samii, P., Harold, D., the Alzheimer's Disease Neuroimaging Initiative, T. I. S. G. C. (., Dichgans, M., Williams, J., Lewis, C. M., Markus, H. S., & and the METASTROKE and International Genomics of Alzheimer's Project (IGAP) investigators (2016) · Annals of Neurology · doi:10.1002/ana.24621 · Cited by 71
PLXNA4 is associated with Alzheimer disease and modulates tau phosphorylation
Jun, G., Asai, H., Zeldich, E., Drapeau, E., Chen, C., Chung, J., Park, J., Kim, S., Haroutunian, V., Foroud, T., et al. (2014) · Annals of Neurology · doi:10.1002/ana.24219 · Cited by 67
“encoded protein using the VEGAS (Versatile Gene-Based Association Study) program, which calculates probability values based on 100,000 permutations.(26)”
MethodPedroso, I., Lourdusamy, A., Rietschel, M., Nöthen, M. M., Cichon, S., McGuffin, P., Al-Chalabi, A., Barnes, M. R., & Breen, G. (2012) · Biological Psychiatry · doi:10.1016/j.biopsych.2011.12.031 · Cited by 59
Moskvina, V., O'Dushlaine, C., Purcell, S., Craddock, N., Holmans, P., & O'Donovan, M. C. (2011) · Genetic Epidemiology · doi:10.1002/gepi.20636 · Cited by 49
Vélez, J. I., Chandrasekharappa, S. C., Henao, E., Martinez, A. F., Harper, U., Jones, M., Solomon, B. D., Lopez, L., Garcia, G., Aguirre-Acevedo, D. C., et al. (2013) · Molecular Psychiatry · doi:10.1038/mp.2012.81 · Cited by 44
A genome-wide investigation of food addiction
Cornelis, M. C., Flint, A., Field, A. E., Kraft, P., Han, J., Rimm, E. B., & van Dam, R. M. (2016) · Obesity · doi:10.1002/oby.21476 · Cited by 44
Mukherjee, S., Russell, J. C., Carr, D. T., Burgess, J. D., Allen, M., Serie, D. J., Boehme, K. L., Kauwe, J. S. K., Naj, A. C., Fardo, D. W., et al. (2017) · Alzheimer's & Dementia · doi:10.1016/j.jalz.2017.01.016 · Cited by 39
miR155 regulation of behavior, neuropathology, and cortical transcriptomics in Alzheimer's disease
Readhead, B., Haure-Mirande, J.-V., Mastroeni, D., Audrain, M., Fanutza, T., Kim, S. H., Blitzer, R. D., Gandy, S., Dudley, J. T., & Ehrlich, M. E. (2020) · Acta Neuropathologica · doi:10.1007/s00401-020-02185-z · Cited by 37
Wojcik, G. L., Kao, W. L., & Duggal, P. (2015) · BMC Genetics · doi:10.1186/s12863-015-0191-2 · Cited by 33
Novel loci affecting iron homeostasis and their effects in individuals at risk for hemochromatosis
Benyamin, B., Esko, T., Ried, J. S., Radhakrishnan, A., Vermeulen, S. H., Traglia, M., Gögele, M., Anderson, D., Broer, L., Podmore, C., et al. (2014) · Nature Communications · doi:10.1038/ncomms5926 · Cited by 30
“We performed gene-based analysis on SNP association p-values from the meta-analysis of discovery samples using VEGAS (http://gump.qimr.edu.au/VEGAS/, accessed 2014-03-27) 69 .”
Self-citationRadwan, Z. H., Wang, X., Waqar, F., Pirim, D., Niemsiri, V., Hokanson, J. E., Hamman, R. F., Bunker, C. H., Barmada, M. M., Demirci, F. Y., et al. (2014) · PLoS ONE · doi:10.1371/journal.pone.0114618 · Cited by 27
Genome‐wide association study of body mass index in subjects with alcohol dependence
Polimanti, R., Zhang, H., Smith, A. H., Zhao, H., Farrer, L. A., Kranzler, H. R., & Gelernter, J. (2017) · Addiction Biology · doi:10.1111/adb.12317 · Cited by 22
“Considering the results of GWAS in AAs and EAs, we performed a genebased association analysis in each ancestry group using VEGAS software (Liu et al. 2010).”
MethodH‐MAGMA, inheriting a shaky statistical foundation, yields excess false positives
Yurko, R., Roeder, K., Devlin, B., & G'Sell, M. (2021) · Annals of Human Genetics · doi:10.1111/ahg.12412 · Cited by 23
Pemberton, T. J., Verdu, P., Becker, N. S., Willer, C. J., Hewlett, B. S., Le Bomin, S., Froment, A., Rosenberg, N. A., & Heyer, E. (2018) · Human Genetics · doi:10.1007/s00439-018-1902-3 · Cited by 18
Genetic and expression analysis of COPI genes and Alzheimer’s disease susceptibility
Yang, Y., Wang, X., Ju, W., Sun, L., & Zhang, H. (2019) · Frontiers in Genetics · doi:10.3389/fgene.2019.00866 · Cited by 6
Metadata
- Authors
- Liu, J. Z., Mcrae, A. F., Nyholt, D. R., Medland, S. E., Wray, N. R., Brown, K. M., Hayward, N. K., Montgomery, G. W., Visscher, P. M., Martin, N. G., & Macgregor, S.
- Venue
- The American Journal of Human Genetics
- Publisher
- Elsevier BV
- Published
- 2010-07
- Volume
- 87
- Issue
- 1
- Pages
- 139-145
- ISSN
- 0002-9297 (ISSN-L)
- OpenAlex
- W2003283154
- Cited by
- 791
- References
- 4
- FWCI
- 29.34
- Type
- journal article
- Language
- en
- Open access
- bronze
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