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.
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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
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MethodGenome-wide association study of the five-factor model of personality in young Korean women
Kim, H., Roh, S.-J., Sung, Y. A., Chung, H. W., Lee, J., Cho, J., Shin, H., & Kim, H. (2013) · Journal of Human Genetics · doi:10.1038/jhg.2013.75 · Cited by 84
Locke, A. E., Dooley, K. J., Tinker, S. W., Cheong, S. Y., Feingold, E., Allen, E. G., Freeman, S. B., Torfs, C. P., Cua, C. L., Epstein, M. P., et al. (2010) · Genetic Epidemiology · doi:10.1002/gepi.20518 · Cited by 84
“To further identify and account for potential substructure in the combined study sample, we used a genomic control approach [Devlin and Roeder, 1999], by comparing allele frequencies of the case and control parents of both ethnic groups at 204 additional loci genotyped along with this study, yielding an inflation fact…”
MethodGenome-wide analysis of attention deficit hyperactivity disorder in Norway
Zayats, T., Athanasiu, L., Sonderby, I., Djurovic, S., Westlye, L. T., Tamnes, C. K., Fladby, T., Aase, H., Zeiner, P., Reichborn-Kjennerud, T., et al. (2015) · PLoS ONE · doi:10.1371/journal.pone.0122501 · Cited by 83
“Genomic control [40] was applied to check for possible population stratification.”
MethodLunetta, K. L. (2008) · Circulation · doi:10.1161/circulationaha.107.700401 · Cited by 84
Ahsan, H., Halpern, J., Kibriya, M. G., Pierce, B. L., Lin, T., Gamazon, E. R., McGuire, V. M., Felberg, A., Shi, J., Jasmine, F., et al. (2014) · Cancer Epidemiology Biomarkers & Prevention · doi:10.1158/1055-9965.epi-13-0340 · Cited by 85
“We checked for population stratificationusinggraphicalplotsof test statisticsand thelmeasure of overdispersion (19).”
Adams, M. J., Hill, W. D., Howard, D. M., Dashti, H. S., Davis, K. A. S., Campbell, A., Clarke, T., Deary, I. J., Hayward, C., Porteous, D. J., et al. (2019) · International Journal of Epidemiology · doi:10.1093/ije/dyz134 · Cited by 78
Reduced neonatal brain-derived neurotrophic factor is associated with autism spectrum disorders
Skogstrand, K., Hagen, C. M., Borbye‐Lorenzen, N., Christiansen, M., Bybjerg‐Grauholm, J., Bækvad‐Hansen, M., Werge, T. M., Børglum, A. D., Mors, O. N., Nordentoft, M., et al. (2019) · Translational Psychiatry · doi:10.1038/s41398-019-0587-2 · Cited by 84
Simcoe, M. J., Valdes, A. M., Liu, F., Furlotte, N. A., Evans, D. M., Hemani, G., Ring, S. M., Smith, G. D., Duffy, D. L., Zhu, G., et al. (2021) · Science Advances · doi:10.1126/sciadv.abd1239 · Cited by 92
“Both metaanalyses were performed using METAL (52) ap plying a weighted Zscore approach, given the differing phenotypic scales used across individual cohorts, with genomic control adjust ments (24) made for the VisiGen metaanalysis (see the Supplementary Methods).”
BackgroundMethodInfluentialGenome-wide screen for asthma in Puerto Ricans: evidence for association with 5q23 region
Choudhry, S., Taub, M. A., Mei, R., Rodríguez‐Santana, J., Rodríguez-Cintrón, W., Shriver, M. D., Ziv, E., RISCH, N. J., & Burchard, E. G. (2008) · Human Genetics · doi:10.1007/s00439-008-0495-7 · Cited by 83
“…downside to performing genetic association studies in recently admixed populations, such as Puerto Ricans, is the possibility for spurious associations (confounding) due to population stratiW- cation (Cardon and Palmer 2003; Devlin and Roeder 1999; Marchini et al. 2004; Ziv and Burchard 2003).”
BackgroundYu, J., Zhang, Z., Zhu, C., Tabanao, D. A. A., Pressoir, G., Tuinstra, M. R., Kresovich, S., Todhunter, R. J., & Buckler, E. S. (2009) · The Plant Genome · doi:10.3835/plantgenome2008.09.0009 · Cited by 83
“, 2003); genomic control (Devlin and Roeder, 1999; Devlin et al., 2001, 2004); mixed-model approach (Yu et al.”
Mead, S., Uphill, J. B., Beck, J., Poulter, M., Campbell, T., Lowe, J., Adamson, G., Hummerich, H., Klopp, N., Rückert, I., et al. (2011) · Human Molecular Genetics · doi:10.1093/hmg/ddr607 · Cited by 83
Nayeri, S., Sargolzaei, M., Abo-Ismail, M. K., Miller, S. P., Schenkel, F. S., Moore, S. S., & Stothard, P. (2016) · Journal of Dairy Science · doi:10.3168/jds.2016-11770 · Cited by 83
“Quantile-quantile ( Q-Q ) plots and inflation factor λ (Devlin and Roeder, 1999) were used to compare observed distributions of –log( P -value) to the expected distribution under the no association model for each trait.”
MethodThe distribution of common-variant effect sizes
O’Connor, L. J. (2021) · Nature Genetics · doi:10.1038/s41588-021-00901-3 · Cited by 81
Mansour, T. A., Lucot, K. L., Konopelski, S. E., Dickinson, P. J., Sturges, B. K., Vernau, K. L., Choi, S. S., Stern, J. A., Thomasy, S. M., Döring, S., et al. (2018) · PLoS Genetics · doi:10.1371/journal.pgen.1007850 · Cited by 88
“Genomic inflation increases this mean and to correct for this, all test statistics values are divided by the mean of the test statistics to restore the expected distribution [77].”
BackgroundGenome-wide association study of antibody response to smallpox vaccine
Ovsyannikova, I. G., Kennedy, R. B., O’Byrne, M. M., Jacobson, R. M., Pankratz, V. S., & Poland, G. A. (2012) · Vaccine · doi:10.1016/j.vaccine.2012.04.055 · Cited by 82
“These lambda values were then used to assess and correct for any inflation in the levels of significance, as described by Devlin and Roeder [17].”
Cappa, E. P., El-Kassaby, Y. A., García, M. N., Acuña, C. V., Borralho, N. M. G., Grattapaglia, D. G., & Poltri, S. N. M. (2013) · PLoS ONE · doi:10.1371/journal.pone.0081267 · Cited by 82
“To overcome such drawbacks, several methods have been developed and successfully implemented [8,9,10].”
MethodEVI5 is a risk gene for multiple sclerosis
Hoppenbrouwers, I. A., Aulchenko, Y. S., Ebers, G. C., Ramagopalan, S. V., Oostra, B. A., van Duijn, C. M., & Hintzen, R. Q. (2008) · Genes and Immunity · doi:10.1038/gene.2008.22 · Cited by 81
Genetic model selection in two-phase analysis for case-control association studies
Zheng, G., & Ng, H. K. T. (2007) · Biostatistics · doi:10.1093/biostatistics/kxm039 · Cited by 81
“It is known that case–control designs for genetic association may be affected by population stratifications and/or cryptic relatedness (Devlin and Roeder, 1999; Pritchard and Rosenberg, 1999; Satten and others, 2001; Zheng and others, 2005; Gorroochurn and others, 2006).”
BackgroundMetabolic and cardiovascular traits: an abundance of recently identified common genetic variants
Mohlke, K. L., Boehnke, M., & Abecasis, G. R. (2008) · Human Molecular Genetics · doi:10.1093/hmg/ddn275 · Cited by 82
“0 10(28) for fat mass) became weaker after correction for stratification using genomic control (43).”
BackgroundMicroarray Technology and Applications in the Arena of Genome-Wide Association
Grant, S. F. A., & Hakonarson, H. H. (2008) · Clinical Chemistry · doi:10.1373/clinchem.2008.105395 · Cited by 84
“... markers (AIMs),whicharechosenfrom3populationsandhave relatively common alleles, based on the HapMap project,canbeusedtoassessethnicity.Onecanfurther use the information generated on the SNP chips to more thoroughly evaluate evidence for population stratificationusingacombinationof3strategies:a)the structure approa…”
BackgroundBossé, 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
“These statistical tests were then adjusted for possible population stratiWcation using the genomic control method (Devlin and Roeder 1999).”
MethodGuo, Y., Huang, Y., Hou, L., Ma, J., Chen, C., Ai, H., Huang, L., & Ren, J. (2017) · Genetics Selection Evolution · doi:10.1186/s12711-017-0295-4 · Cited by 83
“The P value of the association test was adjusted by the genomic control method to correct for residual inflation [19, 20].”
MethodRzehak, P., Covic, M., Saffery, R., Reischl, E., Wahl, S., Grote, V., Weber, M., Xhonneux, A., Langhendries, J., Ferré, N., et al. (2017) · Scientific Reports · doi:10.1038/s41598-017-13099-4 · Cited by 82
Discovery and Fine-Mapping of Glycaemic and Obesity-Related Trait Loci Using High-Density Imputation
Horikoshi, M., Mägi, R., van de Bunt, M., Surakka, I. L., Sarin, A., Mahajan, A., Marullo, L., Þorleifsson, G., Hägg, S., Hottenga, J., et al. (2015) · PLoS Genetics · doi:10.1371/journal.pgen.1005230 · Cited by 81
“Summary statistics from association testing of variants passing quality control, separately in males and females, were corrected in each study for residual population structure through genomic control [56] where necessary (S2 and S3 Tables).”
Integrating epidemiology and genetic association: the challenge of gene–environment interaction
Kraft, P., & Hunter, D. (2005) · Philosophical Transactions of the Royal Society B Biological Sciences · doi:10.1098/rstb.2005.1692 · Cited by 81
“B (2005) although they require subjects be genotyped on a second panel of putatively anonymous markers (Devlin & Roeder 1999; Pritchard et al. 2000; Reich & Goldstein 2001; Tang et al. 2005)—preferably ‘ancestry informative markers,’ markers that are known to have different allele frequency in…”
BackgroundJestin, C., Lodé‐Taburel, M., Vallée, P., Domin, C., Falentin, C., Horvais, R., Coëdel, S., Manzanares-Dauleux, M. J., & Delourme, R. (2010) · Molecular Breeding · doi:10.1007/s11032-010-9429-x · Cited by 81
“Different statistical methods (Devlin and Roeder 1999; Price et al. 2006; Pritchard et al. 2000; Yu et al. 2006) that account for population structure and/or family relatedness can then be used to reduce the false positives and thus increase the power of AM (Zhao et al. 2007a).”
MethodReplication of celiac disease UK genome-wide association study results in a US population
Garner, C., Murray, J. A., Ding, Y. C., Tien, Z., van Heel, D. A., & Neuhausen, S. L. (2009) · Human Molecular Genetics · doi:10.1093/hmg/ddp364 · Cited by 82
“The genomic control parameter, lambda (13) was estimated from the x(2) association statistics computed for all 975 SNPs with the Cluster 1 sample to be 2.”
MethodInferences from Genomic Models in Stratified Populations
Janss, L., Campos, G. D. L., Sheehan, N. A., & Sørensen, D. (2012) · Genetics · doi:10.1534/genetics.112.141143 · Cited by 84
“…of literature has been devoted to methods to account for unobserved population substructure in the context of GWAS, including genomic control (Devlin and Roeder 1999), mixed models (Yu et al. 2006; Kang et al. 2008, 2010; Zhang et al. 2010), and principal components (Patterson et al. 2006;…”
MethodLerer, B., & Macciardi, F. M. (2002) · The International Journal of Neuropsychopharmacology · doi:10.1017/s1461145702002936 · Cited by 81
“Pritchard and Rosenberg (1999) have shown that microsatellite markers provide more power to detect stratification than do biallelic markers (Devlin and Roeder, 1999).”
BackgroundAn epigenome-wide association study meta-analysis of educational attainment
Linnér, R. K., Marioni, R. E., Rietveld, C. A., Simpkin, A. J., Davies, N. M., Watanabe, K., Armstrong, N. J., Auro, K. M., Baumbach, C., Bonder, M. J., et al. (2017) · Molecular Psychiatry · doi:10.1038/mp.2017.210 · Cited by 81
Young, A. I., Wauthier, F. L., & Donnelly, P. (2018) · Nature Genetics · doi:10.1038/s41588-018-0225-6 · Cited by 76
Analysis of 14 Candidate Genes for Diabetic Nephropathy on Chromosome 3q in European Populations
Vionnet, N., Trégouët, D., Kazeem, G., Gut, I. G., Groop, P., Tarnow, L., Parving, H., Hadjadj, S., Forsblom, C. M., Farrall, M., et al. (2006) · Diabetes · doi:10.2337/db06-0271 · Cited by 80
“We also examined 94 SNP genomic control markers in nongenic regions spaced throughout the genome to control for possible stratification within each population (23).”
Preliminary genome‐wide association study of bipolar disorder in the Japanese population
Hattori, E., Toyota, T., Ishitsuka, Y., Iwayama, Y., Yamada, K., Ujike, H., Morita, Y., Kodama, M., Nakata, K., Minabe, Y., et al. (2009) · American Journal of Medical Genetics Part B Neuropsychiatric Genetics · doi:10.1002/ajmg.b.30941 · Cited by 80
“The inflation factor (l) of genomic control [Devlin and Roeder, 1999] was also calculated by EIGENSTRAT.”
MethodTeh, C.-K., Ong, A. L., Kwong, Q.-B., Apparow, S., Chew, F. T., Mayes, S., Mohamed, M., Appleton, D. R., & Kulaveerasingam, H. (2016) · Scientific Reports · doi:10.1038/srep19075 · Cited by 82
Application of an African Ancestry Index as a Genomic Control Approach in a Brazilian Population
Zembrzuski, V., Callegari-Jacques, S., & Hutz, M. (2006) · Annals of Human Genetics · doi:10.1111/j.1469-1809.2006.00270.x · Cited by 77
“Several methods have been described to correct for population stratification (Devlin & Roeder, 1999; Pritchard & Rosenberg, 1999; Pritchard et al. 2000; Reich & Goldstein, 2001).”
MethodGenetics of Callous-Unemotional Behavior in Children
Viding, E. M., Price, T. S., Jaffee, S. R., Trzaskowski, M., Davis, O. S. P., Meaburn, E. L., Haworth, C. M. A., & Plomin, R. J. (2013) · PLoS ONE · doi:10.1371/journal.pone.0065789 · Cited by 85
“Probability values were adjusted by genomic control [64] separately for genotyped SNPs, SNPs that were genotyped in the WTCCC2 controls and imputed in the TEDS sample, and SNPs that were imputed in both WTCCC2 controls and the TEDS sample.”
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Li, X., Yan, W., Agrama, H. A., Jia, L., Shen, X., Jackson, A. K., Moldenhauer, K. A. K., Yeater, K. M., McClung, A. M., & Wu, D. (2011) · Planta · doi:10.1007/s00425-011-1405-0 · Cited by 79
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
“These values suggest that association studies in Quebec could yield inflated false-positive rates and should take into account population structure, especially since genomic inflation factors may be higher with the larger sample sizes used in case–control studies (Devlin and Roeder 1999).”
BackgroundMethodResultInfluentialRongve, A., Witoelar, A., Ruiz, A., Athanasiu, L., Ruiz, C. A., Clarimón, J., Heilmann‐Heimbach, S., Hernández, I., Moreno–Grau, S., de Rojas, I., et al. (2019) · Scientific Reports · doi:10.1038/s41598-019-43458-2 · Cited by 81
Mota, L. F. M., Lopes, F. B., Júnior, G. A. F., Rosa, G. J. M., Magalhães, A. F. B., Carvalheiro, R., & de Albuquerque, L. G. (2020) · Scientific Reports · doi:10.1038/s41598-020-63516-4 · Cited by 80
African Americans with Asthma: Genetic Insights
Barnes, K. C., Grant, A. V., Hansel, N. N., Gao, P., & Dunston, G. M. (2007) · Proceedings of the American Thoracic Society · doi:10.1513/pats.200607-146jg · Cited by 80
Epistasis between polymorphisms in COMT, ESR1, and GCH1 influences COMT enzyme activity and pain
Smith, S. B., Reenilä, I., Männistö, P. T., Slade, G. D., Maixner, W. D., Diatchenko, L. B., & Nackley, A. G. (2014) · Pain · doi:10.1016/j.pain.2014.09.009 · Cited by 78
“The potential for population stratification to influence association statistics was assessed by calculating the lambda statistic [18]; no evidence was found for inflation of test statistics (k < 1.”
MethodFamily-Based Genome-Wide Association Studies
Benyamin, B., Visscher, P. M., & McRae, A. F. (2009) · Pharmacogenomics · doi:10.2217/14622416.10.2.181 · Cited by 79
Meta-analysis of genome-wide association data identifies novel susceptibility loci for obesity
Pei, Y., Zhang, L., Liu, Y., Li, J. M., Shen, H., Liu, Y.-Z., Tian, Q., He, H., Wu, S., Ran, S., et al. (2013) · Human Molecular Genetics · doi:10.1093/hmg/ddt464 · Cited by 80
“To correct for potential population stratification, GC inflation factor (63) was estimated for each GWA study and study-specific summary statistics were corrected prior to the meta-analysis.”
Genetic variation and association mapping for 12 agronomic traits in indica rice
Lu, Q., Zhang, M., Niu, X., Shan, W., Xu, Q. J., Feng, Y., Wang, C., Deng, H., Yuan, X., Yu, H., et al. (2015) · BMC Genomics · doi:10.1186/s12864-015-2245-2 · Cited by 79
Family-based association studies
Zhao, H. (2000) · Statistical Methods in Medical Research · doi:10.1177/096228020000900604 · Cited by 79
Nonreplication in Genetic Association Studies of Obesity and Diabetes Research
Redden, D. T., & Allison, D. B. (2003) · Journal of Nutrition · doi:10.1093/jn/133.11.3323 · Cited by 76
Ganesh, S. K., Chasman, D. I., Larson, M. G., Guo, X., Verwoert, G., Bis, J. C., Gu, X., Smith, A. V., Yang, M.-L., Zhang, Y., et al. (2014) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2014.06.002 · Cited by 71
Wang, G. T., Peng, B., & Leal, S. M. (2014) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2014.04.004 · Cited by 80
“number of MDS components to be included in association analysis.(35,36) For analysis of different populations, e.”
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
“To take into account inflated test statistics caused by population stratification we corrected test statistics using the genomic control metric lmedian [20].”
MethodCunningham, S., Graham, C. A., Hutchinson, M., Droogan, A. G., O’Rourke, K., PATTERSON, C., McDonnell, G. V., Hawkins, S. A., & Vandenbroeck, K. (2005) · Clinical Pharmacology & Therapeutics · doi:10.1016/j.clpt.2005.08.018 · Cited by 77
“) Statistical analysis Differences in genotype frequencies and carriage rates between all MS patients and healthy control subjects and between stratified rIFN-β responders and rIFN-β nonresponders were assessed by chi-square analysis”
MethodEnabling Privacy-Preserving GWASs in Heterogeneous Human Populations
Simmons, S., Şahinalp, S. C., & Berger, B. (2016) · Cell Systems · doi:10.1016/j.cels.2016.04.013 · Cited by 77
“In order to avoid this common problem, known as population stratification, various methods have been employed (EIGENSTRAT [6], linear mixed models (LMMs) [13], genomic control (GC) [2], etc.”
Chen, G., Lee, S., Zhu, Z.-X., Benyamin, B., & Robinson, M. R. (2016) · Heredity · doi:10.1038/hdy.2016.25 · Cited by 78
“indicates underlying population structure (Devlin and Roeder, 1999).”
MethodInfluentialGenetics, Genomics, and Breeding of Grapes
(2011) · CRC Press eBooks · doi:10.1201/b10948 · Cited by 83
Wang, H., Burnett, T. S., Kono, S., Haiman, C. A., Iwasaki, M., Wilkens, L. R., Loo, L. W. M., Berg, D. V. D., Kolonel, L. N., Henderson, B. E., et al. (2014) · Nature Communications · doi:10.1038/ncomms5613 · Cited by 77
“In general, all genotyped samples were examined and excluded according to the following: (1) call rateso90%, 95% or 97% depending on the batches, (2) missing on basic covariates (age, sex or disease status), (3) gender mismatch, that is, the reported sex was different from that estimated based on X chromosome inbreedi…”
MethodShu, X., Long, J., Cai, Q., Kweon, S., Choi, J., Kubo, M., Park, S. K., Bolla, M. K., Dennis, J., Wang, Q., et al. (2020) · Nature Communications · doi:10.1038/s41467-020-15046-w · Cited by 78
AWclust: point-and-click software for non-parametric population structure analysis
Gao, X., & Starmer, J. (2008) · BMC Bioinformatics · doi:10.1186/1471-2105-9-77 · Cited by 80
“AWclust performs classification rather than test statistic adjustment as genomic control [32-34] and EigenStrat [35] do.”
The Growing Importance of CNVs: New Insights for Detection and Clinical Interpretation
Valsesia, A., Macé, A., Jacquemont, S., Beckmann, J. S., & Kutalik, Z. (2013) · Frontiers in Genetics · doi:10.3389/fgene.2013.00092 · Cited by 78
“Although genomic control methods (Devlin and Roeder, 1999) allow correcting for inflated p-values in most cases, critical assessment of the CNV pipeline remains necessary both for sensitivity and specificity.”
MethodThe novel atherosclerosis locus at 10q11 regulates plasma CXCL12 levels
Mehta, N. N., Li, M., William, D. A., Khera, A. V., DerOhannessian, S. L., Qu, L., Ferguson, J. F., McLaughlin, C., Shaikh, L. H., Shah, R., et al. (2011) · European Heart Journal · doi:10.1093/eurheartj/ehr091 · Cited by 77
Identification of Nine Novel Loci Associated with White Blood Cell Subtypes in a Japanese Population
Okada, Y., Hirota, T., Kamatani, Y., Takahashi, A., Ohmiya, H., Kumasaka, N., Higasa, K., Yamaguchi‐Kabata, Y., Hosono, N., Nalls, M. A., et al. (2011) · PLoS Genetics · doi:10.1371/journal.pgen.1002067 · Cited by 77
“Inflation factors of P-values, lGC [27], were as low as 1.”
BackgroundAinsworth, H. F., Unwin, J., Jamison, D. L., & Cordell, H. J. (2010) · Genetic Epidemiology · doi:10.1002/gepi.20547 · Cited by 76
“Recently, however, the case/control design has achieved greater popularity owing to the larger sample size (and thus greater power) that is achievable [WTCCC, 2007] and the development of alternative methods to deal with population stratification [Devlin and Roeder, 1999; Price et al., 2006; Pritchard et al., 2000].”
MethodLinkage Analysis of a Complex Disease through Use of Admixed Populations
Zhu, X., Cooper, R., & Elston, R. C. (2004) · The American Journal of Human Genetics · doi:10.1086/421329 · Cited by 75
“This procedure is similar to the genomic control method, in which a set of unlinked markers is used to control the false-positive rate due to the effect of population heterogeneity (Devlin and Roeder 1999).”
MethodGenome-wide Association Studies for Female Fertility Traits in Chinese and Nordic Holsteins
Liu, A., Wang, Y., Sahana, G., Zhang, Q., Liu, L., Lund, M. S., & Su, G. (2017) · Scientific Reports · doi:10.1038/s41598-017-09170-9 · Cited by 80
Zhou, G., & Zhao, H. (2021) · PLoS Genetics · doi:10.1371/journal.pgen.1009697 · Cited by 73
“Besides, double genomic control is applied to many summary statistics, which may lead to deflation of effect sizes [18, 19].”
Whole-genome association study for fatty acid composition of oleic acid in Japanese Black cattle
Uemoto, Y., Abe, T., Tameoka, N., HASEBE, H., Inoue, K., Nakajima, H., Shoji, N., Kobayashi, M., & Kobayashi, E. (2010) · Animal Genetics · doi:10.1111/j.1365-2052.2010.02088.x · Cited by 75
“Amin et al. (2007) also show that the genome-wide association analysis using both GRAMMAR and Genomic Control (GC) approaches (Devlin & Roeder 1999) is feasible and powerful in related populations.”
MethodGenome-Wide Association Study of Lp-PLA2 Activity and Mass in the Framingham Heart Study
Suchindran, S., Rivedal, D. D., Guyton, J. R., Milledge, T., Gao, X., Benjamin, A. M., Rowell, J. V., Ginsburg, G. S., & McCarthy, J. J. (2010) · PLoS Genetics · doi:10.1371/journal.pgen.1000928 · Cited by 75
“statistics by the expected median in the absence of stratification (0.456)”
BackgroundInfluentialFc receptor genes and the systemic lupus erythematosus diathesis
Brown, E. E., Edberg, J. C., & Kimberly, R. P. (2007) · Autoimmunity · doi:10.1080/08916930701763710 · Cited by 75
Central nervous system serotonergic responsivity and aggressive disposition in men
Manuck, S. B., Flory, J. D., Muldoon, M. F., & Ferrell, R. E. (2002) · Physiology & Behavior · doi:10.1016/s0031-9384(02)00922-8 · Cited by 75
Association of HPA axis genes with suicidal behaviour in schizophrenia
Luca, V. D., Tharmalingam, S., Zai, C. C. H., Potapova, N. V., Strauss, J., Vincent, J. B., & Kennedy, J. (2008) · Journal of Psychopharmacology · doi:10.1177/0269881108097817 · Cited by 75
“We used GC to separate causal factors from confounding factors (Devlin and Roeder, 1999).”
MethodNew genetic evidence for involvement of the dopamine system in migraine with aura
Todt, U., Netzer, C., Toliat, M. R., Heinze, A., Goebel, I., Nürnberg, P., Göbel, H., Freudenberg, J., & Kubisch, C. (2009) · Human Genetics · doi:10.1007/s00439-009-0623-z · Cited by 75
“To quantify the potential impact of a systematic bias, we next calculated the 2 inXation factor lambda-GC (Devlin and Roeder 1999) for the allelic comparison of our control sample and the WTCCC sample.”
MethodA powerful and efficient set test for genetic markers that handles confounders
Listgarten, J., Lippert, C., Kang, E. Y., Xiang, J., Kadie, C. M., & Heckerman, D. E. (2013) · Bioinformatics · doi:10.1093/bioinformatics/btt177 · Cited by 73
“, and LMM-corrected, univariate analysis on each data set, because this is a wellunderstood test that has been reported on before. On GAW14, the uncorrected analysis yielded a genomic control factor (Devlin and Roeder 1999), , while the LMM yielded . On WTCCC Crohn’s and hypertension, the uncorrected analysis yielded…”
MethodResultWen, W., Kato, N., Hwang, J., Guo, X., Tabara, Y., Li, H., Dorajoo, R., Yang, X., Tsai, F., Li, S., et al. (2016) · Scientific Reports · doi:10.1038/srep17958 · Cited by 76
Fast inference of individual admixture coefficients using geographic data
Caye, K., Jay, F., Michel, O., & François, O. (2018) · The Annals of Applied Statistics · doi:10.1214/17-aoas1106 · Cited by 75
Applications of Linkage Disequilibrium and Association Mapping in Maize
Ersoz, E. S., Yu, J., & Buckler, E. S. (2008) · Biotechnology in agriculture and forestry · doi:10.1007/978-3-540-68922-5_13 · Cited by 74
1,000 ancient genomes uncover 10,000 years of natural selection in EuropePreprint
Le, M. K., Smith, O. S., Akbari, A., Harpak, A., Reich, D., & Narasimhan, V. M. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.08.24.505188 · Cited by 75
Carty, C. L., Keene, K. L., Cheng, Y.-C., Meschia, J. F., Chen, W., Nalls, M. A., Bis, J. C., Kittner, S. J., Rich, S. S., Tajuddin, S. M., et al. (2015) · Stroke · doi:10.1161/strokeaha.115.009044 · Cited by 73
“of cerebral edema, and postischemic reuptake of glycerol and lactate.(27,28) Intergenic SNPs in this region also are associated with blood lipids in populations of diverse ancestry(29) and hypertension in African Americans.”
BackgroundVignal, C., Bansal, A. T., Balding, D. J., Binks, M. H., Dickson, M. C., Montgomery, D. S., & Wilson, A. G. (2008) · Arthritis & Rheumatism · doi:10.1002/art.24138 · Cited by 75
Wang, D., Sun, Y. H., Stang, P., Berlin, J. A., Wilcox, M., & Li, Q. S. (2009) · BMC Proceedings · doi:10.1186/1753-6561-3-s7-s109 · Cited by 78
“The genomic inflation factor [7] was calculated for each GWA analysis.”
Liu, Y.-Z., Wilson, S. G., Wang, L., Liu, X.-G., Guo, Y.-F., Li, J., Yan, H., Deloukas, P., Soranzo, N., Chinnapen-Horsley, U., et al. (2008) · PLoS ONE · doi:10.1371/journal.pone.0003160 · Cited by 74
“Calculated through the genomic control method [15], the measure for population stratification (l) for our GWAS sample, was 1.”
MethodInfluentialLi, Q., Zheng, G., Li, Z., & Yu, K. F. (2008) · Annals of Human Genetics · doi:10.1111/j.1469-1809.2008.00437.x · Cited by 74
“Various approaches (e.g., Devlin & Roeder, 1999; Price et al. 2006; Zheng et al. 2006b, and Li & Yu, 2008) have been proposed for the correction of population stratification.”
BackgroundComprehensive analysis of the role of DNA repair gene polymorphisms on risk of glioma
Bethke, L., Webb, E. L., Murray, A., Schoemaker, M. J., Johansen, C., Christensen, H. C., Muir, K. R., McKinney, P. A., Hepworth, S. J., Dimitropoulou, P., et al. (2007) · Human Molecular Genetics · doi:10.1093/hmg/ddm351 · Cited by 74
“To detect possible population stratification, we employed the genomic control approach (18) using all SNPs to estimate the stratification parameter and its associated 95% CI.”
MethodDauber, A. N., Yu, Y., Turchin, M. C., Chiang, C. W. K., Meng, Y., Demerath, E. W., Patel, S. R., Rich, S. S., Rotter, J. I., Schreiner, P. J., et al. (2011) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2011.10.014 · Cited by 73
Kittles, R. A., Baffoe-Bonnie, A. B., Moses, T. Y., Robbins, C. M., Ahaghotu, C., Huusko, P., Pettaway, C., Vijayakumar, S., Bennett, J., Hoke, G., et al. (2005) · Journal of Medical Genetics · doi:10.1136/jmg.2005.035790 · Cited by 74
Stanaway, I. B., Hall, T. O., Rosenthal, E. A., Palmer, M. R., Naranbhai, V., Knevel, R., Namjou‐Khales, B., Carroll, R. J., Kiryluk, K., Gordon, A. S., et al. (2019) · Europe PMC (PubMed Central) · doi:10.1002/gepi.22167 · Cited by 69
“…meet these association and quality parameters, we plotted the Manhattan and Quantile–Quantile plots using the GWASTools (Gogarten et al., 2012) R package and observed the genomic control lambda (λ; Devlin & Roeder, 1999). λ has an expected value close to one in a valid genome‐wide association.”
MethodA meta-analysis of gene expression quantitative trait loci in brain
Kim, Y., Xia, K., Tao, R., Giusti-Rodriguez, P., Vladimirov, V, van den Oord, E., & Sullivan, P. F. (2014) · Translational Psychiatry · doi:10.1038/tp.2014.96 · Cited by 73
Bongiorni, S., Mancini, G., Chillemi, G., Pariset, L., & Valentini, A. (2012) · PLoS ONE · doi:10.1371/journal.pone.0050137 · Cited by 73
“Genomic control was applied and the inflation factor l was calculated and used to correct significance levels [44].”
MethodZlojutro, M., Manz, N., Rangaswamy, M., Xuei, X., Wetherill, L. F., Koller, D. L., Bierut, L. J., Goate, A., HESSELBROCK, V. M., Samuel Kuperman, C., et al. (2010) · American Journal of Medical Genetics Part B Neuropsychiatric Genetics · doi:10.1002/ajmg.b.31136 · Cited by 73
“…confounding for case–control association studies, was corrected using twomethods: computation of genomic-control (GC) adjusted significance values [Devlin and Roeder, 1999], which accommodates over-dispersion of the chi-square statistic due to heterogeneity through the estimation of an inflation…”
MethodThe evolution and expression of virulence
Ebert, D., & Bull, J. J. (2007) · Oxford University Press eBooks · doi:10.1093/acprof:oso/9780199207466.003.0012 · Cited by 75
Power and Efficiency of the TDT and Case-Control Design for Association Scans
McGinnis, R. E., Shifman, S., & Darvasi, A. (2002) · Behavior Genetics · doi:10.1023/a:1015205924326 · Cited by 72
“Note that the costs for cases and controls (ca, cc) should not only factor in costs for recruitment but also any additional costs if researchers elect to apply “genomic control” ( Devlin and Roeder, 1999 ) or other methods (Pritchard and Rosenberg, 1999) aimed at detecting and/or correcting for population stratificati…”
BackgroundAn Exhaustive Epistatic SNP Association Analysis on Expanded Wellcome Trust Data
Lippert, C., Listgarten, J., Davidson, R. I., Baxter, J., Poon, H., Kadie, C. M., & Heckerman, D. E. (2013) · Scientific Reports · doi:10.1038/srep01099 · Cited by 73
Qin, H., Chen, M., Yi, X., Shu, B., Zhang, C., Youchang, Z., Lan, J., Meng, Y., Yuán, Y., & Jiao, C. (2015) · PLoS ONE · doi:10.1371/journal.pone.0118073 · Cited by 73
IL-1RN and IL-1B gene polymorphisms and cerebral hemorrhagic events after traumatic brain injury
Hadjigeorgiou, G. M., Paterakis, K. N., Dardiotis, E., Dardioti, M., Aggelakis, K., Τάσιου, Α., Xiromerisiou, G., Komnos, A., Zintzaras, E., Scarmeas, N., et al. (2005) · Neurology · doi:10.1212/01.wnl.0000178890.93795.0e · Cited by 73
Genome-wide association studies: implications for multiethnic samples
Cooper, R., Tayo, B. O., & Zhu, X. (2008) · Human Molecular Genetics · doi:10.1093/hmg/ddn263 · Cited by 74
“Further, the PCA approach is more powerful than both the genomic-control method (7) and meta-analysis that combines P-values from individual studies and is less computationally intensive than the Structure association method (6).”
MethodTrans-ethnic Fine Mapping Highlights Kidney-Function Genes Linked to Salt Sensitivity
Mahajan, A., Rodan, A. R., Le, T. H., Gaulton, K. J., Haessler, J., Stilp, A. M., Kamatani, Y., Zhu, G., Sofer, T., Puri, S., et al. (2016) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2016.07.012 · Cited by 71
Shen, H., Liu, Y., Liu, P., Recker, R. R., & Deng, H. (2005) · Journal of Bone and Mineral Research · doi:10.1359/jbmr.041129 · Cited by 73
“The Genomic Control method makes a quantitative estimate of , the degree of over dispersion of statistics generated by population stratification, and uses it to adjust the ordinary test statistic.”
MethodInfluentialA common biological basis of obesity and nicotine addiction
Thorgeirsson, T. E., Gudbjartsson, D. F., Sulem, P., Besenbacher, S., Styrkarsdottir, U., Thorleifsson, G., Walters, G. B., TAG Consortium, Oxford-GSK Consortium, ENGAGE consortium, et al. (2013) · Translational Psychiatry · doi:10.1038/tp.2013.81 · Cited by 71
A genome-wide meta-analysis of nodular sclerosing Hodgkin lymphoma identifies risk loci at 6p21.32
Cozen, W., Li, D., Best, T., Berg, D. J. V. D., Gourraud, P., Cortessis, V. K., Skol, A. D., Mack, T. M., Glaser, S. L., Weiss, L. M., et al. (2011) · Blood · doi:10.1182/blood-2011-03-343921 · Cited by 72
Multi-population GWA mapping via multi-task regularized regression
Puniyani, K., Kim, S. Y., & Xing, E. P. (2010) · Bioinformatics · doi:10.1093/bioinformatics/btq191 · Cited by 71
“While lactase activity typically disappears in childhood after weaning, some individuals have the ability to digest lactose during the adulthood.”
BackgroundMethodSha, Q., Wang, X., Wang, X., & Zhang, S. (2012) · Genetic Epidemiology · doi:10.1002/gepi.21649 · Cited by 72
“In association studies of common variants, several methods have been developed to control for population stratification by using a set of unlinked genetic markers genotyped in the same samples [Devlin and Roeder, 1999; Price et al., 2006; Pritchard et al., 2000; Zhang et al., 2003].”
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
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