The DOI matches its Crossref record; 34 of the 34 references it cites were found in a registry or an index.
Genomic Control for Association Studies
Abstract
Summary. A dense set of single nucleotide polymorphisms (SNP) covering the genome and an efficient method to assess SNP genotypes are expected to be available in the near future. An outstanding question is how to use these technologies efficiently to identify genes affecting liability to complex disorders. To achieve this goal, we propose a statistical method that has several optimal properties: It can be used with case‐control data and yet, like family‐based designs, controls for population heterogeneity; it is insensitive to the usual violations of model assumptions, such as cases failing to be strictly independent; and, by using Bayesian outlier methods, it circumvents the need for Bonferroni correction for multiple tests, leading to better performance in many settings while still constraining risk for false positives. The performance of our genomic control method is quite good for plausible effects of liability genes, which bodes well for future genetic analyses of complex disorders.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
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?
In the citing paper
“the conventional genomic inflation factor (lambda or λ used interchangeably below) is dependent on the expected number of true associations”
From Sex-specific DNA methylation differences in Alzheimer’s disease pathology (2021) · cites this paper as [31]
In the citing paper
“Because in a typical epigenome-wide association study (EWAS), it is expected that small effects from many CpGs might be associated with the phenotype, the genomic inflation factor would overestimate actual test-statistic inflation”
From Sex-specific DNA methylation differences in Alzheimer’s disease pathology (2021) · cites this paper as [31]
In the citing paper
“The genomic control inflation factor (λ) 11 was 1.037, suggesting little evidence for residual stratification.”
From Genome-wide association study identifies variants at CLU and PICALM associated with Alzheimer's disease (2009) · cites this paper as [11]
In the citing paper
“The most popular are genomic control (GC)21,22, principal component analysis (PCA)23 and linear mixed models24.”
From Differential confounding of rare and common variants in spatially structured populations (2012) · cites this paper as [22]
In the citing paper
“The overall inflation of the results due to population stratification is negligible: a modified [7] genomic control factor [10] (see Text S1).”
From Integrated Model of De Novo and Inherited Genetic Variants Yields Greater Power to Identify Risk Genes (2013) · cites this paper as [10]
In the citing paper
“Prior to the gene-based analyses all individual SNP P-values were corrected for the genomic inflation factor (λ; to normalise for unaccounted variation, due to factors such as population stratification; Devlin and Roeder, 1999).”
From Genetic variability in response to amyloid beta deposition influences Alzheimer’s disease risk (2019) · cites this paper as Devlin and Roeder, 1999
In the citing paper
“Residual stratification was further corrected at the meta-analytic level with study-specific genomic controls56”
From Association studies of up to 1.2 million individuals yield new insights into the genetic etiology of tobacco and alcohol use (2019) · cites this paper as [56]
In the citing paper
“For the discovery, we applied two rounds of genomic control corrections to each individual GWAS and the combined meta results, respectively 51.”
From Seven new loci associated with age-related macular degeneration (2013) · cites this paper as [51]
In the citing paper
“Methods were developed to detect and adjust for such biases (67–69) as well as unexpected relatedness between subjects.”
From Genetic Mapping in Human Disease (2008) · cites this paper as [67]
Citations
Cites
Kass, R. E., & Raftery, A. E. (1995) · Journal of the American Statistical Association · doi:10.1080/01621459.1995.10476572 · Cited by 12,558
Statistical Decision Theory and Bayesian Analysis
Berger, J. O. (1985) · Springer Series in Statistics · doi:10.1007/978-1-4757-4286-2 · Cited by 7,722
The Future of Genetic Studies of Complex Human Diseases
Risch, N., & Merikangas, K. (1996) · Science · doi:10.1126/science.273.5281.1516 · Cited by 5,355
An introduction to population genetics theory
Crow, J. F., & Kimura, M. (1970) · Medical Entomology and Zoology · Cited by 4,223
Spielman, R. S., McGinnis, R. E., & Ewens, W. J. (1993) · PubMed · Cited by 3,679
The History and Geography of Human Genes
Cavalli-Sforza, L. L., Menozzi, P., & Piazza, A. (2018) · Princeton University Press eBooks · doi:10.2307/j.ctv301gjp · Cited by 3,175
BARNETT, V. D., Lewis, T., & Abeles, F. F. (1979) · Physics Today · doi:10.1063/1.2995737 · Cited by 2,834
Wang, D. G., Fan, J., Siao, C.-J., Berno, A. J., Young, P. R., Sapolsky, R., Ghandour, G., Perkins, N., Winchester, E., Spencer, J. B., et al. (1998) · Science · doi:10.1126/science.280.5366.1077 · Cited by 2,162
Bayes and Empirical Bayes Methods for Data Analysis
Carlin, B. P., & Louis, T. A. (2001) · Technometrics · doi:10.1198/tech.2001.s608 · Cited by 2,110
Tests for Linear Trends in Proportions and Frequencies
Armitage, P. (1955) · Biometrics · doi:10.2307/3001775 · Cited by 2,092
Cited by
Sorted by citations
Items 101–200 of 1,023
Assessing the impact of population stratification on genetic association studies
Freedman, M. L., Reich, D., Penney, K. L., McDonald, G. J., Mignault, A. A., Patterson, N. J., Gabriel, S., Topol, E. J., Smoller, J. W., Pato, C. N., et al. (2004) · Nature Genetics · doi:10.1038/ng1333 · Cited by 807
New loci associated with kidney function and chronic kidney disease
Köttgen, A., Pattaro, C., Böger, C. A., Fuchsberger, C., Olden, M., Glazer, N. L., Parsa, A., Gao, X., Yang, Q., Smith, A. V., et al. (2010) · Nature Genetics · doi:10.1038/ng.568 · Cited by 807
“Genomic control correction by calculating the lambda factor (λ) across all imputed SNP”
The trans-ancestral genomic architecture of glycemic traits
Chen, J., Spracklen, C. N., Marenne, G., Varshney, A., Corbin, L. J., Luan, J., Willems, S. M., Wu, Y., Zhang, X., Horikoshi, M., et al. (2021) · Nature Genetics · doi:10.1038/s41588-021-00852-9 · Cited by 776
“The analysis was performed in a subset of the cohorts included in the discovery GWAS (with representation from each ancestry) and in a smaller number of independent cohorts (European ancestry only).”
Seven new loci associated with age-related macular degeneration
The AMD Gene Consortium (2013) · Nature Genetics · doi:10.1038/ng.2578 · Cited by 788
“Biometrics 55, 997–1004 (1999). lars G Fritsche1,2,128, wei Chen2,3,128, Matthew schu4,128, Brian l Yaspan5,6,128, Yi Yu7,128, Gudmar Thorleifsson8, Donald J Zack9–12, satoshi Arakawa13, Valentina Cipriani14,15, stephan Ripke16,17, Robert P Igo Jr18, Gabriëlle H s Buitendijk19,20, Xueling sim2,21, Daniel e weeks22,23,…”
BackgroundBeall, C. M., Cavalleri, G. L., Deng, L., Elston, R. C., Gao, Y., Knight, J., Li, C., Li, J. C., Liang, Y., McCormack, M., et al. (2010) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1002443107 · Cited by 845
Stacey, S. N., Manolescu, A., Sulem, P., Rafnar, T., Gudmundsson, J., Gudjonsson, S. A., Masson, G., Jakobsdottir, M., Thorlacius, S., Helgason, A., et al. (2007) · Nature Genetics · doi:10.1038/ng2064 · Cited by 786
“We adjusted the results for relatedness among individuals and for potential population stratification using the method of genomic contro”
MethodVujkovic, M., Keaton, J. M., Lynch, J. A., Miller, D. R., Zhou, J., Tcheandjieu, C., Huffman, J. E., Assimes, T. L., Lorenz, K., Zhu, X., et al. (2020) · Nature Genetics · doi:10.1038/s41588-020-0637-y · Cited by 741
Variants in KCNQ1 are associated with susceptibility to type 2 diabetes mellitus
Yasuda, K., Miyake, K., Horikawa, Y., Hara, K., Osawa, H., Furuta, H., Hirota, Y., Mori, H., Jonsson, A., Sato, Y., et al. (2008) · Nature Genetics · doi:10.1038/ng.207 · Cited by 776
“We did not detect significant population stratification among individuals of the initial panels of the five disease groups by standard methods such as genomic contro”
MethodGenome-Wide Association Study of Retinopathy in Individuals without Diabetes
Jensen, R. A., Sim, X., Li, X., Cotch, M. F., Ikram, M. K., Holliday, E. G., Eiríksdóttir, G., Harris, T. B., Jónasson, F., Klein, R., et al. (2013) · PLoS ONE · doi:10.1371/journal.pone.0054232 · Cited by 763
“To account for possible residual population structure or other confounding factors, genomic control [36] was applied to each cohort before meta-analysis.”
MethodGenetic determinants of hair, eye and skin pigmentation in Europeans
Sulem, P., Gudbjartsson, D. F., Stacey, S. N., Helgason, A., Rafnar, T., Magnusson, K. P., Manolescu, A., Karason, A., Palsson, A., Thorleifsson, G., et al. (2007) · Nature Genetics · doi:10.1038/ng.2007.13 · Cited by 750
Genetics of 35 blood and urine biomarkers in the UK Biobank
Sinnott-Armstrong, N., Tanigawa, Y., Amar, D., Mars, N., Benner, C., Aguirre, M., Venkataraman, G. R., Wainberg, M., Ollila, H. M., Kiiskinen, T., et al. (2021) · Nature Genetics · doi:10.1038/s41588-020-00757-z · Cited by 744
An Arabidopsis Example of Association Mapping in Structured Samples
Zhao, K., Aranzana, M. J., Kim, S. H., Lister, C., Shindo, C., Tang, C., Toomajian, C., Zheng, H., Dean, C., Marjoram, P., et al. (2005) · PLoS Genetics · doi:10.1371/journal.pgen.0030004 · Cited by 776
“control’’ [15] and ‘‘structured association’’ [16], were not”
BackgroundGudmundsson, J., Sulem, P., Steinthorsdottir, V., Bergthorsson, J. T., Thorleifsson, G., Manolescu, A., Rafnar, T., Gudbjartsson, D., Agnarsson, B. A., Baker, A., et al. (2007) · Nature Genetics · doi:10.1038/ng2062 · Cited by 723
Mahajan, A., Spracklen, C. N., Zhang, W., Ng, M. C. Y., Petty, L. E., Kitajima, H., Yu, G. Z., Rüeger, S., Speidel, L., Kim, Y. J., et al. (2022) · Nature Genetics · doi:10.1038/s41588-022-01058-3 · Cited by 704
Rivadeneira, F., Estrada, K., Zillikens, M. C., van Meurs, J. B. J., Pols, H. A. P., Uitterlinden, A. G., Amin, N., Aulchenko, Y. S., Albert Hofman, D., van Duijn, C. M., et al. (2009) · Nature Genetics · doi:10.1038/ng.446 · Cited by 711
“Identification of BMD loci Association results (corrected by the genomic control metho”
Winkelmann, J., Schormair, B., Lichtner, P., Ripke, S., Xiong, L., Jalilzadeh, S., Fulda, S., Pütz, B., Eckstein, G., Hauk, S., et al. (2007) · Nature Genetics · doi:10.1038/ng2099 · Cited by 706
Baum, A. E., Akula, N., Cabanero, M., Cardona, I., Corona, W., Klemens, B., Schulze, T. G., Cichon, S., Rietschel, M., Nöthen, M. M., et al. (2008) · Molecular Psychiatry · doi:10.1038/sj.mp.4002012 · Cited by 700
Sequence variants at CHRNB3–CHRNA6 and CYP2A6 affect smoking behavior
The ENGAGE Consortium, Thorgeirsson, T. E., Gudbjartsson, D. F., Surakka, I., Vink, J. M., Amin, N., Geller, F., Sulem, P., Rafnar, T., Esko, T., et al. (2010) · Nature Genetics · doi:10.1038/ng.573 · Cited by 689
“We estimated an inflation factor for each GWA scan by calculating the average of the χ 2 statistics, which is a method of genomic contro”
MethodUda, M., Galanello, R., Sanna, S., Lettre, G., Sankaran, V. G., Chen, W., Usala, G., Busonero, F., Maschio, A., Albai, G., et al. (2008) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0711566105 · Cited by 672
Hunter, D. J., Peltonen, L., Guiducci, C., Crawford, G., Hirschhorn, J. N., Lyon, H. N., & Speliotes, E. K. (2009) · DSpace@MIT (Massachusetts Institute of Technology) · Cited by 687
Han, B., & Eskin, E. (2011) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2011.04.014 · Cited by 680
Common Sequence Variants in the LOXL1 Gene Confer Susceptibility to Exfoliation Glaucoma
Thorleifsson, G., Magnusson, K. P., Sulem, P., Walters, G. B., Gudbjartsson, D. F., Stefansson, H., Jonsson, T., Jonasdottir, A., Jonasdottir, A., Stefansdottir, G., et al. (2007) · Science · doi:10.1126/science.1146554 · Cited by 677
Newly identified genetic risk variants for celiac disease related to the immune response
Hunt, K. A., Zhernakova, A., Turner, G., Heap, G., Franke, L., Bruinenberg, M., Romanos, J., Dinesen, L. C., Ryan, A. W., Panesar, D., et al. (2008) · Nature Genetics · doi:10.1038/ng.102 · Cited by 685
“We assessed the median distribution of test statistics using genomic contro”
MethodGenome-wide association study of ankylosing spondylitis identifies non-MHC susceptibility loci
Reveille, J. D., Jin, R., Zhou, X., Diekman, L., Sims, A. M., Danoy, P., Leo, P., Bradbury, L. A., Doan, T., Dowling, A., et al. (2010) · Nature Genetics · doi:10.1038/ng.513 · Cited by 669
Zaykin, D. V., Westfall, P. H., Young, S. S., Karnoub, M. A., Wagner, M. J., & Ehm, M. G. (2002) · Human Heredity · doi:10.1159/000057986 · Cited by 655
Winkler, T. W., Justice, A. E., Graff, M., Barata, L., Feitosa, M. F., Chu, S. H., Czajkowski, J., Esko, T., Fall, T., Kilpeläinen, T. O., et al. (2015) · PLoS Genetics · doi:10.1371/journal.pgen.1005378 · Cited by 681
“Sex- and age-specific standard errors and P-values from each participating study were genomic-control (GC) corrected using study- and strata-specific lambda factors [74], whereas the lambdas were estimated from all genome-wide available SNPs for imputed GWAS and form a subset of 4,427 QT-interval SNPs for MetaboChip s…”
Genetic drivers of heterogeneity in type 2 diabetes pathophysiology
Suzuki, K., Hatzikotoulas, K., Southam, L., Taylor, H. J., Yin, X., Lorenz, K. M., Mandla, R., Huerta-Chagoya, A., Melloni, G. E. M., Kanoni, S., et al. (2024) · Nature · doi:10.1038/s41586-024-07019-6 · Cited by 606
“To assess the extent of residual structure between GWASs, we calculated the genomic control inflation factor 65 for the multi-ancestry meta-regression and the fixed-effects meta-analysis.”
MethodAssigning Significance to Peptides Identified by Tandem Mass Spectrometry Using Decoy Databases
Käll, L., Storey, J. D., MacCoss, M. J., & Noble, W. S. (2008) · Journal of Proteome Research · doi:10.1021/pr700600n · Cited by 607
Identification of common variants associated with human hippocampal and intracranial volumes
(ADNI), T. A. D. N. I., Stein, J. L., Murray, R. M., Medland, S. E., Vásquez, A. A., Hibar, D. P., Senstad, R. E., Winkler, A. M., Toro, R., Appel, K., et al. (2012) · Nature Genetics · doi:10.1038/ng.2250 · Cited by 634
Multiple Genetic Loci for Bone Mineral Density and Fractures
Styrkársdóttir, U., Halldórsson, B. V., Grétarsdóttir, S., Gudbjartsson, D. F., Walters, G. B., Ingvarsson, Þ., Jónsdóttir, Þ., Saemundsdottir, J., Nguyen, T. V., Bagger, Y. Z., et al. (2008) · New England Journal of Medicine · doi:10.1056/nejmoa0801197 · Cited by 633
Psaty, B. M., O'Donnell, C. J., Gudnason, V., Lunetta, K. L., Folsom, A. R., Rotter, J. I., Uitterlinden, A. G., Harris, T. B., Witteman, J. C. M., & Boerwinkle, E. (2009) · Circulation: Cardiovascular Genetics · doi:10.1161/circgenetics.108.829747 · Cited by 599
Asthma genetics 2006: the long and winding road to gene discovery
Ober, C., & Hoffjan, S. (2006) · Genes and Immunity · doi:10.1038/sj.gene.6364284 · Cited by 621
GWAMA: software for genome-wide association meta-analysis
Mägi, R., & Morris, A. P. (2010) · BMC Bioinformatics · doi:10.1186/1471-2105-11-288 · Cited by 600
“…software incorporates tools to align studies to the same reference strand, irrespective of the GWA genotyping product, where possible, and optionally performs genomic control [11] of sum-mary statistics to correct for population structure within each study, and potential variation between studies.”
MethodInfluentialMaller, J., George, S., Purcell, S., Fagerness, J., Altshuler, D., Daly, M. J., & Seddon, J. M. (2006) · Nature Genetics · doi:10.1038/ng1873 · Cited by 599
“The method of genomic control implemented in PLINK follows ref”
Methodthe IBSEN study group, Franke, A., Balschun, T. C., Karlsen, T. H., Skiecevičienė, J., Nikolaus, S., Gabriele Mayr, B., Domingues, F. S., Albrecht, M., Nothnagel, M., et al. (2008) · Nature Genetics · doi:10.1038/ng.221 · Cited by 590
“We found genetic heterogeneity to be low, with an estimated genomic inflation facto”
BackgroundCordell, H. J., & Clayton, D. G. (2005) · The Lancet · doi:10.1016/s0140-6736(05)67424-7 · Cited by 587
Circadian patterns of gene expression in the human brain and disruption in major depressive disorder
Li, J. Z., Bunney, B. G., Meng, F., Hagenauer, M. H., Walsh, D. M., Vawter, M. P., Evans, S. J., Choudary, P. V., Cartagena, P., Barchas, J. D., et al. (2013) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1305814110 · Cited by 589
“This artifact is analogous to the phenomenon of population stratification in genetic association studies; thus, we adopted a correction method similar to the genomic control method (17).”
BackgroundMethodTesting for an Unusual Distribution of Rare Variants
Neale, B. M., Rivas, M. A., Voight, B. F., Altshuler, D., Devlin, B., Orho‐Melander, M., Kathiresan, S., Purcell, S., Roeder, K., & Daly, M. J. (2011) · PLoS Genetics · doi:10.1371/journal.pgen.1001322 · Cited by 592
“If a large set of genotypes were available, such as from a genome-wide association (GWA) study, principal component analyses and related procedures can be used to match or control for ancestry [19–21].”
MethodSelf-citationFine-scale recombination rate differences between sexes, populations and individuals
Kong, A., Þorleifsson, G., Gudbjartsson, D. F., Másson, G., Sigurðsson, Á., Jónasdóttir, Á., Walters, G. B., Jónasdóttir, A., Gylfason, A., Kristinsson, K. T., et al. (2010) · Nature · doi:10.1038/nature09525 · Cited by 592
Genomic inflation factors under polygenic inheritance
Yang, J., Weedon, M. N., Purcell, S., Lettre, G., Estrada, K., Willer, C. J., Smith, A. V., Ingelsson, E., O’Connell, J. R., Mangino, M., et al. (2011) · European Journal of Human Genetics · doi:10.1038/ejhg.2011.39 · Cited by 571
“8 One standard quality-control measure for GWAS and meta-analysis is genomic control (GC)”
BackgroundGenome-wide association study identifies five loci associated with lung function
Repapi, E., The NSHD Respiratory Study Team, Sayers, I., Wain, L. V., Burton, P. R., Johnson, T., Obeidat, M., Zhao, J. H., Ramasamy, A., Zhai, G., et al. (2009) · Nature Genetics · doi:10.1038/ng.501 · Cited by 577
“All stage 1 study effect estimates were corrected using genomic contro”
Parental origin of sequence variants associated with complex diseases
DIAGRAM Consortium, Kong, A., Steinthorsdottir, V., Masson, G., Thorleifsson, G., Sulem, P., Besenbacher, S., Jonasdottir, A., Sigurdsson, A., Kristinsson, K. T., et al. (2009) · Nature · doi:10.1038/nature08625 · Cited by 553
Kato, N., Takeuchi, F., Tabara, Y., Kelly, T. N., Go, M. J., Sim, X., Tay, W. T., Chen, C.-H., Zhang, Y., Yamamoto, K., et al. (2011) · Nature Genetics · doi:10.1038/ng.834 · Cited by 571
DNA Pooling: a tool for large-scale association studies
Sham, P. C., Bader, J. S., Craig, I., O’Donovan, M. C., & Owen, M. J. (2002) · Nature Reviews Genetics · doi:10.1038/nrg930 · Cited by 549
“This factor is then used to adjust association test statistic”
MethodAssessment of cumulative evidence on genetic associations: interim guidelines
Ioannidis, J. P. A., Boffetta, P., Little, J., O'Brien, T. R., Uitterlinden, A. G., Vineis, P., Balding, D. J., Chokkalingam, A. P., Dolan, S. M., Flanders, W. D., et al. (2007) · International Journal of Epidemiology · doi:10.1093/ije/dym159 · Cited by 554
Two independent alleles at 6q23 associated with risk of rheumatoid arthritis
Plenge, R. M., Cotsapas, C. J., Davies, L. R. L., Price, A. L., de Bakker, P. I. W., Maller, J., Pe’er, I., Burtt, N. P., Blumenstiel, B. S., DeFelice, M., et al. (2007) · Nature Genetics · doi:10.1038/ng.2007.27 · Cited by 552
“In an initial analysis of unrelated case-control samples, we assessed the median distribution of test statistics with the genomic-control parameter λ GC”
MethodRevealing the architecture of gene regulation: the promise of eQTL studies
Gilad, Y., Rifkin, S. A., & Pritchard, J. K. (2008) · Trends in Genetics · doi:10.1016/j.tig.2008.06.001 · Cited by 552
“One plausible concern for association mapping is the possibility of false positives owing to population structure [65,66].”
BackgroundQuality control and conduct of genome-wide association meta-analyses
Winkler, T. W., Day, F. R., Croteau‐Chonka, D. C., Wood, A. R., Locke, A. E., Mägi, R., Ferreira, T., Fall, T., Graff, M., Justice, A. E., et al. (2014) · Nature Protocols · doi:10.1038/nprot.2014.071 · Cited by 517
Reilly, M. P., Li, M., He, J., Ferguson, J. F., Stylianou, I. M., Mehta, N. N., Burnett, M. S., Devaney, J. M., Knouff, C. W., Thompson, J. R., et al. (2011) · The Lancet · doi:10.1016/s0140-6736(10)61996-4 · Cited by 547
Kosoy, R., Nassir, R., Tian, C., White, P. A., Butler, L. M., SILVA, G. H. D. O., Kittles, R. A., Alarcón-Riquelme, M. E., Gregersen, P. K., Belmont, J. W., et al. (2008) · Human Mutation · doi:10.1002/humu.20822 · Cited by 539
“False discovery rate statistics [Devlin and Roeder, 1999] were determined using HelixTree 5.0.2 software (Golden Helix, Bozeman , MT).”
MethodInfluentialPractical aspects of imputation-driven meta-analysis of genome-wide association studies
de Bakker, P. I. W., Ferreira, M. A. R., Jia, X., Neale, B. M., Raychaudhuri, S., & Voight, B. F. (2008) · Human Molecular Genetics · doi:10.1093/hmg/ddn288 · Cited by 531
“The genomic inflation factor l is defined as the ratio of the median of the empirically observed distribution of the test statistic to the expected median, thus quantifying the extent of the bulk inflation and the excess false positive rate (32).”
BackgroundAnstee, Q. M., Darlay, R., Cockell, S., Meroni, M., Govaere, O., Tiniakos, D., Burt, A. D., Bedossa, P., Palmer, J., Liu, Y.-L., et al. (2020) · Journal of Hepatology · doi:10.1016/j.jhep.2020.04.003 · Cited by 499
“Examination of the resulting genome-wide QQ plots and genomic control in fl ation factors ( k ) 23 (see Results) indicated that this adjustment adequately corrected for any population differences.”
A QTL influencing F cell production maps to a gene encoding a zinc-finger protein on chromosome 2p15
Menzel, S., Garner, C., Gut, I., Matsuda, F., Yamaguchi, M., Heath, S., Foglio, M., Zelenika, D., Boland, A., Rooks, H., et al. (2007) · Nature Genetics · doi:10.1038/ng2108 · Cited by 529
The Bayesian revolution in genetics
Beaumont, M., & Rannala, B. H. (2004) · Nature Reviews Genetics · doi:10.1038/nrg1318 · Cited by 537
Clayton, D. G., Walker, N. M., Smyth, D. J., Pask, R., Cooper, J. D., Maier, L. M., Smink, L. J., Lam, A. C., Ovington, N. R., Stevens, H. E., et al. (2005) · Nature Genetics · doi:10.1038/ng1653 · Cited by 526
“To avoid excluding SNPs and losing valuable information, we extended the genomic control metho”
MethodRisk HLA-DQA1 and PLA 2 R1 Alleles in Idiopathic Membranous Nephropathy
Stanescu, H. C., Arcos‐Burgos, M., Medlar, A. J., Böckenhauer, D., Köttgen, A., Dragomirescu, L., Voinescu, C., Patel, N., Pearce, K., Hubank, M. J. F., et al. (2011) · New England Journal of Medicine · doi:10.1056/nejmoa1009742 · Cited by 520
Pattaro, C., Teumer, A., Gorski, M., Chu, A. Y., Li, M., Mijatovic, V., Garnaas, M., Tin, A., Sorice, R., Li, Y., et al. (2016) · Nature Communications · doi:10.1038/ncomms10023 · Cited by 514
Common Sequence Variants in the LOXL1 Gene Confer Susceptibility to Exfoliation Glaucoma
Myers, J. S. (2008) · Yearbook of Ophthalmology · doi:10.1016/s0084-392x(08)79151-2 · Cited by 517
Genomic Control, a New Approach to Genetic-Based Association Studies
Devlin, B., Roeder, K., & Wasserman, L. (2001) · Theoretical Population Biology · doi:10.1006/tpbi.2001.1542 · Cited by 511
“We reasoned it would be possible to account for the impact of substructure by using the distribution of markers in the sampled genomes { what we called Genomic Control or GC (Devlin and Roeder 1999).”
BackgroundMethodInfluentialSelf-citationChen, W., Stambolian, D., Edwards, A. O., Branham, K. E., Othman, M., Jakobsdottir, J., Tosakulwong, N., Pericak-Vance, M. A., Campochiaro, P. A., Klein, M. L., et al. (2010) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0912702107 · Cited by 506
“An initial comparison of allele frequencies between cases and controls resulted in a genomic control parameter (20) of 1.”
BackgroundMethodBasic statistical analysis in genetic case-control studies
Clarke, G. M., Anderson, C. A., Pettersson, F. H., Cardon, L. R., Morris, A. P., & Zondervan, K. T. (2011) · Nature Protocols · doi:10.1038/nprot.2010.182 · Cited by 531
“In addition, the technique of genomic control 26 can be used to detect and compensate for the presence of fine-scale or within-population stratification during association testing.”
MethodHigh-Resolution Whole-Genome Association Study of Parkinson Disease
Maraganore, D. M., de Andrade, M., Lesnick, T. G., Strain, K. J., Farrer, M. J., Rocca, W. A., Pant, P. V. K., Frazer, K. A., Cox, D., & Ballinger, D. G. (2005) · The American Journal of Human Genetics · doi:10.1086/496902 · Cited by 505
“We also checked for population structure, using the genomic-control method (Devlin and Roeder 1999; Bacanu et al. 2000; Devlin et al. 2004).”
MethodAndreassen, O. A., Djurovic, S., Thompson, W. K., Schork, A. J., Kendler, K. S., O’Donovan, M. C., Rujescu, D., Werge, T., van de Bunt, M., Morris, A. P., et al. (2013) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2013.01.001 · Cited by 506
A Bayesian measure of the probability of false discovery in genetic epidemiology studies.
Wakefield, J. (2007) · American Journal of Human Genetics · doi:10.1086/519024 · Cited by 518
Genome-wide associations for birth weight and correlations with adult disease
Horikoshi, M., Beaumont, R. N., Day, F. R., Warrington, N. M., Kooijman, M. N., Fernandez-Tajes, J. J., Feenstra, B., van Zuydam, N. R., Gaulton, K. J., Grarup, N., et al. (2016) · Nature · doi:10.1038/nature19806 · Cited by 508
Candidate single-nucleotide polymorphisms from a genomewide association study of Alzheimer disease
Li, H., Wetten, S., Li, L., St. Jean, P. L., Upmanyu, R., Surh, L., Hosford, D., Barnes, M. R., Briley, J. D., Borrie, M., et al. (2008) · Archives of Neurology · doi:10.1001/archneurol.2007.3 · Cited by 499
Control of confounding of genetic associations in stratified populations
Hoggart, C. J., Parra, E. J., Shriver, M. D., Bonilla, C., Kittles, R. A., Clayton, D. G., & McKeigue, P. M. (2003) · The American Journal of Human Genetics · doi:10.1086/375613 · Cited by 490
“Instead of modeling subpopulations, this approach models confounding as a random effect distributed over marker and candidate gene polymorphisms that inflates the variance of the test statistic (Devlin and Roeder 1999; Reich and Goldstein 2001).”
Methodthe BIOS Consortium, van Iterson, M., van Zwet, E. W., & Heijmans, B. T. (2017) · Genome biology · doi:10.1186/s13059-016-1131-9 · Cited by 421
“Although generally ignored, genomic control will overestimate the actual inflation unless it is estimated on the basis of genetic variants not associated with the outcome of interest [9, 19].”
BackgroundMethodInfluentialManuck, S. B., Flory, J. D., Ferrell, R. E., Mann, J. J., & Muldoon, M. F. (2000) · Psychiatry Research · doi:10.1016/s0165-1781(00)00162-1 · Cited by 486
Methods for linkage disequilibrium mapping in crops
Mackay, I., & Powell, W. (2007) · Trends in Plant Science · doi:10.1016/j.tplants.2006.12.001 · Cited by 496
Progress and promise of genome-wide association studies for human complex trait genetics
Stranger, B. E., Stahl, E. A., & Raj, T. (2011) · Genetics · doi:10.1534/genetics.110.120907 · Cited by 567
“Logistic regression was used to test for association with case-control status in each GWAS dataset; the results were genomic-control corrected (Devlin and Roeder 1999) and then combined via inverse variance-weighted meta-analysis (de Bakker et al. 2008).”
MethodQuality control and quality assurance in genotypic data for genome‐wide association studies
Laurie, C. C., Doheny, K. F., Mirel, D. B., Pugh, E., Bierut, L. J., Bhangale, T., Boehm, F. J., Caporaso, N. E., Cornelis, M. C., Edenberg, H. J., et al. (2010) · Genetic Epidemiology · doi:10.1002/gepi.20516 · Cited by 489
“Genomic inflation factor [Devlin and Roeder, 1999] is the ratio of the median of the observed statistic for a set of genome-wide tests to the expected median of that statistic under the null hypothesis.”
BackgroundWeb-Based, Participant-Driven Studies Yield Novel Genetic Associations for Common Traits
Eriksson, N., Macpherson, J. M., Tung, J. Y., Hon, L., Naughton, B., Saxonov, S., Avey, L., Wojcicki, A., Pe’er, I., & Mountain, J. L. (2010) · PLoS Genetics · doi:10.1371/journal.pgen.1000993 · Cited by 483
“For each phenotype, we also computed genomic control inflation factors ( l ) [59].”
MethodMethods for High-Density Admixture Mapping of Disease Genes
Patterson, N. J., Hattangadi, N., Lane, B., Lohmueller, K. E., Hafler, D. A., Oksenberg, J. R., Hauser, S. L., Smith, M. W., O’Brien, S. J., Altshuler, D., et al. (2004) · The American Journal of Human Genetics · doi:10.1086/420871 · Cited by 475
“of allele frequencies with a suitable beta distribution has also been used before (see, e.g., Balding and Nichols 1995; Devlin and Roeder 1999; Falush et al. 2003).”
MethodStatus and prospects of genome‐wide association studies in plants
Tibbs‐Cortes, L. E., Zhang, Z., & Yu, J. (2021) · The Plant Genome · doi:10.1002/tpg2.20077 · Cited by 520
“This information was used to adjust the final p value for each marker, reducing false positives (Devlin & Roeder, 1999).”
MethodMeta-Analysis of Genome-Wide Association Studies of Attention-Deficit/Hyperactivity Disorder
Neale, B. M., Medland, S. E., Ripke, S., Asherson, P., Franke, B., Lesch, K.-P., Faraone, S. V., Nguyen, T. T., Schäfer, H., Holmans, P., et al. (2010) · Journal of the American Academy of Child & Adolescent Psychiatry · doi:10.1016/j.jaac.2010.06.008 · Cited by 450
Genetic association studies: Design, analysis and interpretation
Lewis, C. M. (2002) · Briefings in Bioinformatics · doi:10.1093/bib/3.2.146 · Cited by 467
Susceptibility to leprosy is associated with PARK2 and PACRG
Mira, M. T., Alcaïs, A., Thuc, N. V., Moraes, M. O., Flumeri, C. D., Thai, V. H., Phuong, M. C., Hương, N. T., Ba, N. N., Khoa, P. X., et al. (2004) · Nature · doi:10.1038/nature02326 · Cited by 467
“To account for possible cryptic population stratification, we also used the genomic control metho”
MethodVoight, B. F., Kang, H. M., Ding, J., Palmer, C. D., Sidore, C., Chines, P. S., Burtt, N. P., Fuchsberger, C., Li, Y., Erdmann, J., et al. (2012) · PLoS Genetics · doi:10.1371/journal.pgen.1002793 · Cited by 475
“Since Metabochip SNPs were selected to be associated with our 23 traits of interest, performing genomic control correction [37] requires some care.”
BackgroundGenetic signatures of exceptional longevity in humans
Sebastiani, P., Solovieff, N., DeWan, A. T., Walsh, K. M., Puca, A., Hartley, S. W., Melista, E., Andersen, S., Dworkis, D. A., Wilk, J. B., et al. (2012) · PLoS ONE · doi:10.1371/journal.pone.0029848 · Cited by 464
“We estimated the genomic control factor as described in [88].”
A genome-wide association study of alcohol dependence
Bierut, L. J., Agrawal, A., Bucholz, K. K., Doheny, K. F., Laurie, C., Pugh, E., Fisher, S., Fox, L., Howells, W., Bertelsen, S., et al. (2010) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0911109107 · Cited by 457
Association studies for finding cancer-susceptibility genetic variants
Pharoah, P. D. P., Dunning, A. M., Ponder, B. A. J., & Easton, D. F. (2004) · Nature reviews. Cancer · doi:10.1038/nrc1476 · Cited by 460
Population Structure and Cryptic Relatedness in Genetic Association Studies
Astle, W. J., & Balding, D. J. (2009) · Statistical Science · doi:10.1214/09-sts307 · Cited by 477
“which generalizes the result of Devlin and Roeder (1999). In practice, it is unclear how λ should scale with n in well designed GWAS studies of homogeneous populations.”
BackgroundMethodInfluentialGenome-wide association study identifies three loci associated with melanoma risk
Bishop, D. T., Démenais, F., Iles, M. M., Harland, M., Taylor, J., Corda, E., Randerson‐Moor, J. A., Aitken, J. F., Avril, M., Azizi, E., et al. (2009) · Nature Genetics · doi:10.1038/ng.411 · Cited by 465
Aranzana, M. J., Kim, S., Zhao, K., Bakker, E. G., Horton, M., Jakob, K., Lister, C., Molitor, J., Shindo, C., Tang, C., et al. (2005) · PLoS Genetics · doi:10.1371/journal.pgen.0010060 · Cited by 448
“Genomic control [22] is an alternative approach in which genome-wide markers are used to estimate the effect of population structure on association statistics and correct these statistics to achieve valid significance levels.”
BackgroundWheeler, E., Leong, A., Liu, C.-T., Hivert, M.-F., Strawbridge, R. J., Podmore, C., Li, M., Yao, J., Sim, X., Hong, J., et al. (2017) · PLOS Medicine · doi:10.1371/journal.pmed.1002383 · Cited by 408
“using the genomic control inflation factor, λGC [17,19].”
MethodDemonstrating stratification in a European American population
Campbell, C. D., Ogburn, E. L., Lunetta, K. L., Lyon, H. N., Freedman, M. L., Groop, L. C., Altshuler, D., Ardlie, K. G., & Hirschhorn, J. N. (2005) · Nature Genetics · doi:10.1038/ng1607 · Cited by 444
“Genotyping 178 SNPs and applying standard analytical method”
MethodSoranzo, N., Sanna, S., Wheeler, E., Gieger, C., Radke, D., Dupuis, J., Bouatia‐Naji, N., Langenberg, C., Prokopenko, I., Stolerman, E., et al. (2010) · Diabetes · doi:10.2337/db10-0502 · Cited by 448
Lo, M., Hinds, D. A., Tung, J. Y., Franz, C. E., Fan, C.-C., Wang, Y., Smeland, O. B., Schork, A. J., Holland, D., Kauppi, K., et al. (2016) · Nature Genetics · doi:10.1038/ng.3736 · Cited by 462
Identification of type 2 diabetes loci in 433,540 East Asian individuals
Spracklen, C. N., Horikoshi, M., Kim, Y. J., Lin, K., Bragg, F., Moon, S., Ken, S., Tam, C. H. T., Tabara, Y., Kwak, S., et al. (2020) · Nature · doi:10.1038/s41586-020-2263-3 · Cited by 446
Differential confounding of rare and common variants in spatially structured populations
Mathieson, I., & McVean, G. (2012) · Nature Genetics · doi:10.1038/ng.1074 · Cited by 385
“, and testing and correcting for structure is now standard practice in GWAS through methods such as genomic control (GC”
BackgroundConomos, M. P., Miller, M. B., & Thornton, T. A. (2015) · Genetic Epidemiology · doi:10.1002/gepi.21896 · Cited by 430
“The genomic control inflation factor [Devlin and Roeder, 1999] λG C was used to evaluate confounding due to unaccounted for sample structure, where λG C ≈ 1 indicates appropriate correction for population and family structure, while λG C > 1 indicates elevated type-I error rate.”
MethodGenome-wide association study of PR interval
Pfeufer, A., van Noord, C., Marciante, K. D., Arking, D. E., Larson, M. G., Smith, A. V., Tarasov, K. V., Müller‐Nurasyid, M., Sotoodehnia, N., Sinner, M. F., et al. (2010) · Nature Genetics · doi:10.1038/ng.517 · Cited by 434
“076 and report overall analysis results unadjusted for this λ value (25).”
BackgroundMahajan, 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
“Association summary statistics for each analysis were corrected for residual inflation by means of genomic control 41 , calculated after excluding variants mapping to established T2D susceptibility loci.”
InfluentialGenome-wide Association Studies in Maize: Praise and Stargaze
Xiao, Y., Liu, H., Wu, L., Warburton, M. L., & Yan, J. (2016) · Molecular Plant · doi:10.1016/j.molp.2016.12.008 · Cited by 439
Estimation and Tests of Haplotype-Environment Interaction when Linkage Phase Is Ambiguous
Lake, S. L., Lyon, H. N., Tantisira, K. G., Silverman, E. K., Weiss, S. T., Laird, N. M., & Schaid, D. J. (2003) · Human Heredity · doi:10.1159/000071811 · Cited by 426
A genome-wide association meta-analysis identifies new childhood obesity loci
Bradfield, J. P., Abou‐Sleiman, P. M., Hakonarson, H. H., Grant, S. F. A., Taal, H. R., Mook‐Kanamori, D. O., Albert Hofman, D., van der Valk, R. J. P., de Jongste, J. C., Jaddoe, V. W. V., et al. (2012) · Nature Genetics · doi:10.1038/ng.2247 · Cited by 428
Study, L. C., Wain, L. V., CardioGram, Verwoert, G. C., O’Reilly, P. F., Shi, G., Johnson, T., Johnson, A. D., Bochud, M., Rice, K. M., et al. (2011) · Nature Genetics · doi:10.1038/ng.922 · Cited by 434
Genetic Structure of Europeans: A View from the North–East
Nelis, M., Esko, T., Mägi, R., Zimprich, F., Zimprich, A. A., Toncheva, D. I., Karachanak-Yankova, S., Piskackova, T., Balaščák, I., Peltonen, L., et al. (2009) · PLoS ONE · doi:10.1371/journal.pone.0005472 · Cited by 432
“The inflation factor l was calculated with the method of the Genomic Control [19].”
BackgroundMethodInfluentialFTO genotype is associated with phenotypic variability of body mass index
Yang, J., Loos, R. J. F., Powell, J. E., Medland, S. E., Speliotes, E. K., Chasman, D. I., Rose, L. M., Þorleifsson, G., Steinthórsdóttir, V., Mägi, R., et al. (2012) · Nature · doi:10.1038/nature11401 · Cited by 418
Metadata
- Authors
- Devlin, B., & Roeder, K.
- Affiliations
- University of Pittsburgh (US)
- Carnegie Mellon University (US)
- Corresponding author
- Devlin, B.
- Roeder, Kathryn
- Venue
- Biometrics
- Publisher
- Oxford University Press (OUP)
- Published
- 1999-12
- Volume
- 55
- Issue
- 4
- Pages
- 997-1004
- ISSN
- 0006-341X (ISSN-L)
- 1541-0420
- OpenAlex
- W2008047653
- Cited by
- 3,162
- References
- 34
- Citations by year
- 2026: 86 · 2025: 79 · 2024: 87 · 2023: 84 · 2022: 115 · 2021: 102 · 2020: 94 · 2019: 118 · 2018: 128 · 2017: 124 · 2016: 137 · 2015: 170 · 2014: 143 · 2013: 175 · 2012: 172
- FWCI
- 14.43
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Biometrics (publishedVersion)
- PubMed (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Funders
- University of Pittsburgh
- National Institutes of Health
- National Institute of Mental Health (NIMH 57881, P01MH056193, R01MH057881, NIMH 56193)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Mapping and Diversity in Plants and Animals
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic diversity and population structure
- Keywords
- genomic control, association studies, single nucleotide polymorphisms, case-control data, population heterogeneity, multiple testing correction, false positives, complex diseases, model assumption violation
- MeSH terms
- Bayes Theorem, Biometry, Genetic Techniques, Humans, Models, Genetic, Models, Statistical, Genome, Human, Case-Control Studies
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
