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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Items 401–500 of 1,023
Dalmasso, C., Carpentier, W., Meyer, L., Rouzioux, C., Goujard, C., Chaix, M., Lambotte, O., Avettand-Fènoël, V., Clerc, S. L., de Senneville, L. D., et al. (2008) · PLoS ONE · doi:10.1371/journal.pone.0003907 · Cited by 206
“In the present study, we estimated the q-values using the procedure introduced by Dalmasso et al.[45] and considering a stratified approach (by chromosome) as proposed by Sun et al [46].”
MethodConditions Under Which Genome-Wide Association Studies Will be Positively Misleading
Platt, A., Vilhjálmsson, B. J., & Nordborg, M. (2010) · Genetics · doi:10.1534/genetics.110.121665 · Cited by 203
“…recognized that population structure can cause these kinds of spurious, nonrandom associations (Li 1969; Lander and Schork 1994), and considerable effort has been devoted to addressing this problem statistically (Devlin and Roeder 1999; Pritchard et al. 2000; Price et al. 2006; Yu et al. 2006).”
BackgroundMethodological challenges of genome-wide association analysis in Africa
Teo, Y., Small, K. S., & Kwiatkowski, D. P. (2010) · Nature Reviews Genetics · doi:10.1038/nrg2731 · Cited by 202
“At the first stage of a GWA study, it is possible to correct for population structure using statistical approaches, such as genomic control and principal components analysis”
MethodDries, D. L., Victor, R. G., Rame, J. E., Cooper, R., Wu, X., Zhu, X., Leonard, D. S., Ho, S. I., Wu, Q., Post, W. S., et al. (2005) · Circulation · doi:10.1161/circulationaha.105.568881 · Cited by 195
Wen, W., Zheng, W., Okada, Y., Takeuchi, F., Tabara, Y., Hwang, J., Dorajoo, R., Li, H., Tsai, F., Yang, X., et al. (2014) · Human Molecular Genetics · doi:10.1093/hmg/ddu248 · Cited by 198
“To correct each study for residual population stratification or cryptic relatedness, the meta-analyses were performed with genomic control correction (64) by adjusting for the studyspecific inflation factor (l), which ranged from 1.”
MethodEllinghaus, D., Folseraas, T., Holm, K., Ellinghaus, E., Melum, E., Balschun, T. C., Laerdahl, J. K., Shiryaev, A., Gotthardt, D. N., Weismüller, T. J., et al. (2012) · Hepatology · doi:10.1002/hep.25977 · Cited by 199
“098, respectively (Supporting Table 1).(17) Quantile-quantile (Q-Q) plots of GWAS test statistics showed an excess of significant associations in the tail of the distribution (Supporting Fig.”
Application of t-SNE to human genetic data
Li, W., Cerise, J. E., Yang, Y., & Han, H. (2017) · Journal of Bioinformatics and Computational Biology · doi:10.1142/s0219720017500172 · Cited by 205
A genome-wide association study on African-ancestry populations for asthma
Mathias, R. A., Grant, A. V., Rafaels, N. M., Hand, T. A., Gao, L., Vergara, C., Tsai, Y. J., Yang, M., Campbell, M., Foster, C., et al. (2009) · Journal of Allergy and Clinical Immunology · doi:10.1016/j.jaci.2009.08.031 · Cited by 192
Genome-Wide Association and Functional Follow-Up Reveals New Loci for Kidney Function
Pattaro, C., Köttgen, A., Teumer, A., Garnaas, M., Böger, C. A., Fuchsberger, C., Olden, M., Chen, M., Tin, A., Taliun, D., et al. (2012) · PLoS Genetics · doi:10.1371/journal.pgen.1002584 · Cited by 199
Winkelmann, J., Czamara, D., Schormair, B., Knauf, F., Schulte, E. C., Trenkwalder, C., Dauvilliers, Y. A., Polo, O. J., Högl, B., Berger, K., et al. (2011) · PLoS Genetics · doi:10.1371/journal.pgen.1002171 · Cited by 196
“Using the Genomic Control approach [22], we obtained an inflation factor l of 1.”
MethodAttempted Replication of Reported Chronic Obstructive Pulmonary Disease Candidate Gene Associations
Hersh, C. P., DeMeo, D. L., Lange, C., Litonjua, A. A., Reilly, J. J., Kwiatkowski, D. J., Laird, N. M., Sylvia, J. S., Sparrow, D., Speizer, F. E., et al. (2005) · American Journal of Respiratory Cell and Molecular Biology · doi:10.1165/rcmb.2005-0073oc · Cited by 191
“Several statistical methods, based on genotype data from additional unlinked markers elsewhere in the genome, are available to test for stratification and control for its effects if present (21, 31, 32).”
MethodFast and accurate imputation of summary statistics enhances evidence of functional enrichment
Paşaniuc, B., Zaitlen, N., Shi, H., Bhatia, G., Gusev, A., Pickrell, J. K., Hirschhorn, J. N., Strachan, D. P., Patterson, N. J., & Price, A. L. (2014) · Bioinformatics · doi:10.1093/bioinformatics/btu416 · Cited by 189
“This could hamper efforts to assess confounding due to population stratification or cryptic relatedness via genomic control [39].”
BackgroundEvidence for genetic heterogeneity between clinical subtypes of bipolar disorder
Charney, A. W., Ruderfer, D. M., Stahl, E. A., Moran, J. L., Chambert, K., Belliveau, R., Forty, L., Gordon‐Smith, K., Florio, A. D., Lee, P. H., et al. (2017) · Translational Psychiatry · doi:10.1038/tp.2016.242 · Cited by 195
Aguilar, I., Legarra, A., Cardoso, F. F., Masuda, Y., Lourenco, D. A. L., & Misztal, I. (2019) · Genetics Selection Evolution · doi:10.1186/s12711-019-0469-3 · Cited by 192
Johnson, A. D., Newton‐Cheh, C., Chasman, D. I., Ehret, G., Johnson, T., Rose, L. M., Rice, K. M., Verwoert, G. C., Launer, L. J., Gudnason, V. G., et al. (2011) · Hypertension · doi:10.1161/hypertensionaha.110.158667 · Cited by 191
Genetic variants at 2q24 are associated with susceptibility to type 2 diabetes
Qi, L., Cornelis, M. C., Kraft, P. L., Stanya, K. J., Kao, W. H. L., Pankow, J. S., Dupuis, J., Florez, J. C., Fox, C. S., Paré, G., et al. (2010) · Human Molecular Genetics · doi:10.1093/hmg/ddq156 · Cited by 197
“Individual studies were corrected for residual inflation of the test statistic using genomic control methods (32) and the heterogeneity in effect size across studies was tested using the Cochran’s Q-test (33).”
MethodVariant ASGR1 Associated with a Reduced Risk of Coronary Artery Disease
Nioi, P., Sigurdsson, A., Thorleifsson, G., Helgason, H., Agustsdottir, A. B., Norddahl, G. L., Helgadottir, A., Magnusdottir, A., Jonasdottir, A., Gretarsdottir, S., et al. (2016) · New England Journal of Medicine · doi:10.1056/nejmoa1508419 · Cited by 189
Use of unphased multilocus genotype data in indirect association studies
Clayton, D., Chapman, J., & Cooper, J. (2004) · Genetic Epidemiology · doi:10.1002/gepi.20032 · Cited by 186
“This is recommended because it does not assume Hardy-Weinberg equilibrium in the study population [Devlin and Roeder, 1999].”
BackgroundA sequence variant at 4p16.3 confers susceptibility to urinary bladder cancer
Kiemeney, L. A. L. M., Sulem, P., Besenbacher, S., Vermeulen, S. H. H. M., Sigurðsson, Á., Þorleifsson, G., Gudbjartsson, D. F., Stacey, S., Guðmundsson, J., Zanon, C., et al. (2010) · Nature Genetics · doi:10.1038/ng.558 · Cited by 190
“To adjust for possible population stratification and relatedness among individuals, we divided the χ 2 test statistics from the individual scans using the method of genomic contro”
MethodYang, X., Yan, J., Shah, T. M., Warburton, M. L., Li, Q., Li, L., Gao, Y., Chai, Y., Fu, Z., Zhou, Y., et al. (2010) · Theoretical and Applied Genetics · doi:10.1007/s00122-010-1320-y · Cited by 188
“To account for population structure in association analysis, two major statistical methods, genome control (Devlin and Roeder 1999; Zheng et al. 2005) and structure association (SA) (Pritchard et al.”
MethodOrg, E., Eyheramendy, S., Juhanson, P., Gieger, C., Lichtner, P., Klopp, N., Veldre, G., Döring, A., Viigimaa, M., Sõber, S., et al. (2009) · Human Molecular Genetics · doi:10.1093/hmg/ddp135 · Cited by 192
“The genomic control analysis (24) led to an inflation factor (l) of 1.”
BackgroundUsing association mapping to dissect the genetic basis of complex traits in plants
Hall, D., Tegström, C., & Ingvarsson, P. K. (2010) · Briefings in Functional Genomics · doi:10.1093/bfgp/elp048 · Cited by 192
“One of the first methods proposed was the method of 'genomic control' (GC) developed by Devlin and Roeder [38].”
MethodBlood lipids influence DNA methylation in circulating cells
Dekkers, K. F., van Iterson, M., Slieker, R. C., Moed, M. H., Bonder, M. J., van Galen, M., Mei, H., Zhernakova, D. V., van den Berg, L. H., Deelen, J., et al. (2016) · Genome biology · doi:10.1186/s13059-016-1000-6 · Cited by 190
“To minimize possible inflation in the test statistic, the genomic control procedure [59] was applied to achieve an inflation factor λ of 1.”
MethodGenetic architecture of plant stress resistance: Multi-trait genome-wide association mapping
Thoen, M. P. M., Davila Olivas, N. H., Kloth, K. J., Coolen, S., Huang, P., Aarts, M. G. M., Bac‐Molenaar, J. A., Bakker, J., Bouwmeester, H. J., Broekgaarden, C., et al. (2017) · New Phytologist · doi:10.1111/nph.14220 · Cited by 188
“The Wald test is known to suffer from some inflation (Zhou & Stephens, 2014), which we correct for using genomic control (Devlin & Roeder, 1999; Devlin et al. , 2001), which divides the observed test statistics T 1 , . . . , T p by the genomic inflation factor.”
Prospects for Admixture Mapping of Complex Traits
McKeigue, P. (2004) · The American Journal of Human Genetics · doi:10.1086/426949 · Cited by 181
Kung, A. W. C., Xiao, S., Cherny, S. S., Li, G. H., Gao, Y., Tso, G. H. W., Lau, K. S., Luk, K. D. K., Liu, J., Cui, B., et al. (2010) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2009.12.014 · Cited by 182
McMahon, F. J., Akula, N., Schulze, T. G., Detera‐Wadleigh, S. D., Steele, C. J. M., Wendland, J. R., Breuer, R., Strohmaier, J., Rietschel, M., Muglia, P., et al. (2010) · Nature Genetics · doi:10.1038/ng.523 · Cited by 180
“Modified files were loaded into Metal (July 2008 version), then processed using the GENOMICCONTROL option, which applies a genomic contro”
MethodWang, K., Baldassano, R. N., Zhang, H., Qu, H., Imielinski, M. B., Kugathasan, S., Annese, V., Dubinsky, M. C., Rotter, J. I., Russell, R. K., et al. (2010) · Human Molecular Genetics · doi:10.1093/hmg/ddq078 · Cited by 183
“The genomic control inflation factors (l) (52) were 1.”
BackgroundA Central Role for GRB10 in Regulation of Islet Function in Man
Prokopenko, I., Poon, W., Mägi, R., Prasad, R. B., Salehi, A. A., Almgren, P., Osmark, P., Bouatia‐Naji, N., Wierup, N., Fall, T., et al. (2014) · PLoS Genetics · doi:10.1371/journal.pgen.1004235 · Cited by 176
“Discovery (stage 1) GWAS analyses were carried out using a statistical tool that was able to account for genotype uncertainty, SNPTEST [29], or by using allele dosages in the linear regression model in MACH2QTL [30,31], probABEL [32], corrected for residual inflation of the test statistics using the genomic control me…”
Human 5-HT1A receptor C(−1019)G polymorphism and psychopathology
Huang, Y., Battistuzzi, C., Oquendo, M. A., Harkavy‐Friedman, J., Greenhill, L. L., Zalsman, G., Brodsky, B. S., Arango, V., Brent, D. A., & Mann, J. J. (2004) · The International Journal of Neuropsychopharmacology · doi:10.1017/s1461145704004663 · Cited by 182
“We used instead Armitage’s trend test (Armitage, 1955) that corresponds to the additive genetic model adopted in the genomic control method (Devlin and Roeder, 1999) to assess a trend in genetic relative risks and reduce type I error (Schaid and Jacobsen, 1999).”
MethodGrey wolf genomic history reveals a dual ancestry of dogs
Bergström, A., Stanton, D. W. G., Taron, U. H., Frantz, L., Sinding, M. S., Ersmark, E., Pfrengle, S., Cassatt‐Johnstone, M., Lebrasseur, O., Girdland-Flink, L., et al. (2022) · Nature · doi:10.1038/s41586-022-04824-9 · Cited by 203
Joehanes, R., Zhang, X., Huan, T., Yao, C., Ying, S., Nguyen, Q. T., Demirkale, C. Y., Feolo, M., Sharopova, N., Sturcke, A., et al. (2017) · Genome biology · doi:10.1186/s13059-016-1142-6 · Cited by 178
“We computed the genomic control factor λ as defined by Devlin and Roeder [12].”
BackgroundMethodInfluentialLoss-of-function variants in ATM confer risk of gastric cancer
Helgason, H., Rafnar, Þ., Ólafsdóttir, H. S., Jonasson, J. G., Sigurðsson, Á., Stacey, S., Jónasdóttir, A., Tryggvadóttír, L., Alexiusdottir, K. K., Haraldsson, Á., et al. (2015) · Nature Genetics · doi:10.1038/ng.3342 · Cited by 180
Genome-wide association study of ancestry-specific TB risk in the South African Coloured population
Chimusa, E. R., Zaitlen, N., Daya, M., Möller, M., van Helden, P. D., Mulder, N., Price, A. L., & Hoal, E. G. (2013) · Human Molecular Genetics · doi:10.1093/hmg/ddt462 · Cited by 182
Beaumont, R. N., Warrington, N. M., Cavadino, A., Tyrrell, J., Nodzenski, M., Horikoshi, M., Geller, F., Myhre, R., Richmond, R. C., Paternoster, L., et al. (2018) · Human Molecular Genetics · doi:10.1093/hmg/ddx429 · Cited by 176
Shields, A. E., Fortun, M., Hammonds, E. M., King, P. A., Lerman, C. E., Rapp, R., & Sullivan, P. F. (2005) · American Psychologist · doi:10.1037/0003-066x.60.1.77 · Cited by 177
Pharmacogenetics of antidepressant response
Porcelli, S., Drago, A., Fabbri, C., Gibiino, S., Calati, R., & Serretti, A. (2011) · Journal of Psychiatry and Neuroscience · doi:10.1503/jpn.100059 · Cited by 183
Shen, X., de Jonge, J., Forsberg, S. K. G., Pettersson, M. E., Sheng, Z., Hennig, L., & Carlborg, Ö. (2014) · PLoS Genetics · doi:10.1371/journal.pgen.1004842 · Cited by 173
“Subsequent genomic control (GC) [37] of the genome-wide association results was performed under the null hypothesis that no SNP has an effect on the climate phenotype.”
Variations in the G6PC2/ABCB11 genomic region are associated with fasting glucose levels
Chen, W., Erdos, M. R., Jackson, A., Saxena, R., Sanna, S., Silver, K. D., Timpson, N. J., Hansen, T. F., Orrù, M., Piras, M. G., et al. (2008) · Journal of Clinical Investigation · doi:10.1172/jci34566 · Cited by 179
“The estimated genomic control (40) values for FUSION stage 1 and SardiNIA were both 1.”
BackgroundMethodHettema, J. M., An, S., Neale, M. C., Bukszár, J., van den Oord, E. J. C. G., Kendler, K. S., & Chen, X. (2006) · Molecular Psychiatry · doi:10.1038/sj.mp.4001845 · Cited by 177
Han, B., Kang, H. M., & Eskin, E. (2009) · PLoS Genetics · doi:10.1371/journal.pgen.1000456 · Cited by 171
“Theoretically, this is due to the fact that the allelic and genotypic test statistics differ only by their variance [44].”
Guo, M. H., Plummer, L., Chan, Y.-M., Hirschhorn, J. N., & Lippincott, M. F. (2018) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2018.08.016 · Cited by 180
Swaroop, A., Branham, K. E., Chen, W., & Abecasis, G. (2007) · Human Molecular Genetics · doi:10.1093/hmg/ddm212 · Cited by 173
“Nevertheless, clear differences in disease prevalence between ethnic groups emphasize the importance of design of genetic studies (37,38).”
BackgroundCommon and rare variants associated with kidney stones and biochemical traits
Oddsson, Á., Sulem, P., Helgason, H., Edvardsson, V. O., Þorleifsson, G., Sveinbjörnsson, G., Haraldsdottir, E., Eyjolfsson, G. I., Sigurðardóttir, Ó., Ólafsson, Í., et al. (2015) · Nature Communications · doi:10.1038/ncomms8975 · Cited by 173
A practical introduction to Random Forest for genetic association studies in ecology and evolution
Brieuc, M. S. O., Waters, C. D., Drinan, D. P., & Naish, K. A. (2018) · Molecular Ecology Resources · doi:10.1111/1755-0998.12773 · Cited by 179
“…to account for correlations between individuals (e.g., population structure and relatedness) and reduce false positive results in association studies have been developed (Devlin & Roeder, 1999; Price et al., 2006; Stephan et al., 2015; Yu et al., 2006; Zhang et al., 2010; Zhao et al., 2012).”
BackgroundGenomic screening and replication using the same data set in family-based association testing
Steen, K. V., McQueen, M. B., Herbert, A. G., Raby, B. A., Lyon, H. N., DeMeo, D. L., Murphy, A., Lasky-Su, J. A., Datta, S., Rosenow, C., et al. (2005) · Nature Genetics · doi:10.1038/ng1582 · Cited by 172
Ennis, S., Jomary, C., Mullins, R., Cree, A., Chen, X., MacLeod, A., Jones, S., Collins, A., Stone, E., & Lotery, A. (2008) · The Lancet · doi:10.1016/s0140-6736(08)61348-3 · Cited by 171
Tobi, E. W., Slieker, R. C., Stein, A. D., Suchiman, H. E. D., Slagboom, P. E., van Zwet, E. W., Heijmans, B. T., & Lumey, L. H. (2015) · International Journal of Epidemiology · doi:10.1093/ije/dyv043 · Cited by 173
Common variants at the MHC locus and at chromosome 16q24.1 predispose to Barrett's esophagus
Su, Z., Gay, L. J., Strange, A., Palles, C., Band, G., Whiteman, D. C., Lescai, F., Langford, C., Nanji, M. S., Edkins, S., et al. (2012) · Nature Genetics · doi:10.1038/ng.2408 · Cited by 172
Nayeri, S., Sargolzaei, M., Abo-Ismail, M. K., May, N., Miller, S. P., Schenkel, F. S., Moore, S. S., & Stothard, P. (2016) · BMC Genetics · doi:10.1186/s12863-016-0386-1 · Cited by 170
“The inflation factor λ [69] and quantile-quantile (Q-Q) plots were calculated to compare observed distributions of –log (P-value) to the expected distribution under the no association model for each trait.”
MethodIdentification of 12 genetic loci associated with human healthspan
Zenin, A., Tsepilov, Y., Sharapov, S., Getmantsev, E., Menshikov, L. I., Fedichev, P. O., & Aulchenko, Y. (2019) · Communications Biology · doi:10.1038/s42003-019-0290-0 · Cited by 170
Lindgren, C. M., Heid, I. M., Randall, J. C., Lamina, C., Steinthórsdóttir, V., Qi, L., Speliotes, E. K., Þorleifsson, G., Willer, C. J., Herrera, B. M., et al. (2009) · PLoS Genetics · doi:10.1371/journal.pgen.1000508 · Cited by 712
Johnston, S. E., Bérénos, C., Slate, J., & Pemberton, J. M. (2016) · Genetics · doi:10.1534/genetics.115.185553 · Cited by 171
Arking, D., Junttila, M. J., Goyette, P., Huertas-Vázquez, A., Eijgelsheim, M., Blom, M., Newton-Cheh, C., Reinier, K., Teodorescu, C. A., Uy-Evanado, A., et al. (2011) · PLoS Genetics · doi:10.1371/journal.pgen.1002158 · Cited by 150
“A genomic control correction factor (l), calculated from all imputed SNPs, was applied on a per-study basis to account for cryptic population sub-structure and other potential biases [37].”
MethodGenome-Wide Association Studies Identify CHRNA5/3 and HTR4 in the Development of Airflow Obstruction
Wilk, J. B., Shrine, N. R. G., Loehr, L. R., Zhao, J. H., Manichaikul, A. W., Lopez, L. M., Smith, A. V., Heckbert, S. R., Smolonska, J., Tang, W., et al. (2012) · American Journal of Respiratory and Critical Care Medicine · doi:10.1164/rccm.201202-0366oc · Cited by 180
“Genome-wide and regional meta-analyses were performed using METAL software (22) with inverse variance weighting to combine effect size estimates after applying a genomic control correction (23).”
Polygenic architecture of rare coding variation across 394,783 exomes
Weiner, D. J., Nadig, A., Jagadeesh, K. A., Dey, K. K., Neale, B. M., Robinson, E., Karczewski, K. J., & O’Connor, L. J. (2023) · Nature · doi:10.1038/s41586-022-05684-z · Cited by 168
Genome-Wide Association Studies and Beyond
Witte, J. S. (2010) · Annual Review of Public Health · doi:10.1146/annurev.publhealth.012809.103723 · Cited by 185
“In addition, if such controls result in population stratification bias—confounding of associations due to case-control differences in genetic ancestry (67)—this can be addressed analytically with genomic information (8, 50, 51).”
BackgroundHaplotype analysis in population genetics and association studies
Zhao, H., Pfeiffer, R. M., & Gail, M. H. (2003) · Pharmacogenomics · doi:10.1517/phgs.4.2.171.22636 · Cited by 168
“Many methods [55-57] have been developed to use a large number of markers either to identify the underlying popay provide critical information on human nd the identification of genetic variants underlying hrough linkage disequilibrium (LD), or allelic ns in different regions and different populations fer population hi…”
MethodBest, T., Li, D., Skol, A. D., Kirchhoff, T., Jackson, S. A., Yasui, Y., Bhatia, R., Strong, L. C., Domchek, S. M., Nathanson, K. L., et al. (2011) · Nature Medicine · doi:10.1038/nm.2407 · Cited by 170
Genetic epidemiologic studies of preterm birth: guidelines for research
Pennell, C. E., Jacobsson, B., Williams, S. M., Buus, R. M., Muglia, L. J., Dolan, S. M., Morken, N., Özçelik, H., Lye, S. J., & Relton, C. L. (2007) · American Journal of Obstetrics and Gynecology · doi:10.1016/j.ajog.2006.03.109 · Cited by 163
“One method, genomic control, proposes the collection of genetic information at several loci that are unrelated to the phenotype to test for underlying population structure and to correct for it if it occurs.(101) The second method, known as structured association, tests for underlying population structure explicitly,…”
MethodMeasuring European Population Stratification with Microarray Genotype Data
Bauchet, M., McEvoy, B., Pearson, L. N., Quillen, E. E., Sarkisian, T., Hovhannesyan, K., Deka, R., Bradley, D. G., & Shriver, M. D. (2007) · The American Journal of Human Genetics · doi:10.1086/513477 · Cited by 165
“, how much more likely false-positive results are to arise).(27) A simple estimator for this inflation factor l is the mean allele-frequency correlation between cases and controls (x(2)) across null loci (i.”
BackgroundCordell, H. J., Bentham, J., Töpf, A., Zélénika, D., Heath, S. C., Mamasoula, C., Cosgrove, C., Blue, G. M., Granados-Riveron, J. T., Setchfield, K., et al. (2013) · Nature Genetics · doi:10.1038/ng.2637 · Cited by 165
OSCA: a tool for omic-data-based complex trait analysis
Zhang, F., Chen, W., Zhu, Z., Zhang, Q., Nabais, M. F., Qi, T., Deary, I. J., Wray, N. R., Visscher, P. M., McRae, A. F., et al. (2019) · Genome biology · doi:10.1186/s13059-019-1718-z · Cited by 147
Bonilla, C., Parra, E. J., Pfaff, C., Dios, S., Marshall, J. A., Hamman, R. F., Ferrell, R. E., Hoggart, C., McKeigue, P., & Shriver, M. (2004) · Annals of Human Genetics · doi:10.1046/j.1529-8817.2003.00084.x · Cited by 164
“As a result, several methods have been devised that account for the presence of population structure (Ewens & Spielman, 1995; Devlin & Roeder, 1999; Pritchard & Rosenberg, 1999; McKeigue et al. 2000; Pritchard et al. 2000; Reich & Goldstein, 2001; Satten et al. 2001; Pfaff et al. 2002; Hoggart et…”
MethodApplications of Linkage Disequilibrium and Association Mapping in Crop Plants
Ersoz, E. S., Yu, J., & Buckler, E. S. (2007) · Springer eBooks · doi:10.1007/978-1-4020-6295-7_5 · Cited by 171
Common variants associated with general and MMR vaccine–related febrile seizures
Feenstra, B., Pasternak, B., Geller, F., Carstensen, L., Wang, T., Huang, F., Eitson, J. L., Hollegaard, M. V., Svanström, H., Vestergaard, M., et al. (2014) · Nature Genetics · doi:10.1038/ng.3129 · Cited by 152
Slager, S. L., & Schaid, D. J. (2001) · Human Heredity · doi:10.1159/000053370 · Cited by 163
Genome-wide association study of coronary artery disease in the Japanese
Takeuchi, F., Yokota, M., Yamamoto, K., Nakashima, E., Katsuya, T., Asano, H., Isono, M., Nabika, T., Sugiyama, T., Fujioka, A., et al. (2011) · European Journal of Human Genetics · doi:10.1038/ejhg.2011.184 · Cited by 163
Genome-Wide Association of Body Fat Distribution in African Ancestry Populations Suggests New Loci
Liu, C.-T., Monda, K. L., Taylor, K. C., Lange, L. A., Demerath, E. W., Palmas, W., Wojczynski, M. K., Ellis, J., Vitolins, M. Z., Liu, S., et al. (2013) · PLoS Genetics · doi:10.1371/journal.pgen.1003681 · Cited by 166
“variants across the genome are conventionally used to scale the test statistic [27].”
BackgroundSung, Y. J., Winkler, T. W., Fuentes, L. D. L., Bentley, A. R., Brown, M. R., Kraja, A. T., Schwander, K., Ντάλλα, Ι., Guo, X., Franceschini, N., et al. (2018) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2018.01.015 · Cited by 163
Sex-dimorphic genetic effects and novel loci for fasting glucose and insulin variability
Lagou, V., Mägi, R., Hottenga, J., Grallert, H., Perry, J. R. B., Bouatia‐Naji, N., Marullo, L., Rybin, D. V., Jansen, R., Min, J. L., et al. (2021) · Nature Communications · doi:10.1038/s41467-020-19366-9 · Cited by 157
The Molecular Genetic Architecture of Self-Employment
van der Loos, M. J. H. M., Rietveld, C. A., Eklund, N., Koellinger, P., Rivadeneira, F., Abecasis, G. R., Ankra-Badu, G. A., Baumeister, S. E., Benjamin, D. J., Biffar, R., et al. (2013) · PLoS ONE · doi:10.1371/journal.pone.0060542 · Cited by 167
“Genomic control [69] was applied in samples with inflation factors that were greater than one by adjusting the test statistics.”
MethodWang, X., Liu, W., Sun, C., Armenian, S. H., Hakonarson, H. H., Hageman, L., Ding, Y. P., Landier, W., Blanco, J. G., Chen, L., et al. (2014) · Journal of Clinical Oncology · doi:10.1200/jco.2013.50.3557 · Cited by 161
Saad, M., Lesage, S., Saint-Pierre, A., Corvol, J., Zélénika, D., Lambert, J., Vidailhet, M., Mellick, G. D., Lohmann, E., Durif, F., et al. (2010) · Human Molecular Genetics · doi:10.1093/hmg/ddq497 · Cited by 162
“As for our primary analyses, we applied the genomic inflation correction method (23); the median of the GC-corrected x(2) value was 0.”
MethodMetabolic GWAS ‐based dissection of genetic bases underlying the diversity of plant metabolism
Fang, C., & Luo, J. (2018) · The Plant Journal · doi:10.1111/tpj.14097 · Cited by 162
The advent of genome-wide association studies for bacteria
Chen, P. E., & Shapiro, B. J. (2015) · Current Opinion in Microbiology · doi:10.1016/j.mib.2015.03.002 · Cited by 154
Within family Mendelian randomization studies
Davies, N. M., Howe, L. J., Brumpton, B., Havdahl, A., Evans, D. M., & Davey Smith, G. (2019) · Human Molecular Genetics · doi:10.1093/hmg/ddz204 · Cited by 158
Mansour, H. A., Talkowski, M. E., Wood, J., Chowdari, K. V., McClain, L., Prasad, K., Montrose, D., Fagiolini, A., Friedman, E. S., Allen, M. H., et al. (2009) · Bipolar Disorders · doi:10.1111/j.1399-5618.2009.00756.x · Cited by 161
Self-citationA genome-wide association study in 574 schizophrenia trios using DNA pooling
Kirov, G., Zaharieva, I. T., Georgieva, L., Moskvina, V., Nikolov, I., Cichon, S., Hillmer, A. M., Toncheva, D. I., Owen, M. J., & O’Donovan, M. C. (2008) · Molecular Psychiatry · doi:10.1038/mp.2008.33 · Cited by 161
The Genome-wide Patterns of Variation Expose Significant Substructure in a Founder Population
Jakkula, E., Rehnström, K., Varilo, T., Pietiläinen, O. P. H., Paunio, T., Pedersen, N. L., DeFaire, U., Järvelin, M., Saharinen, J., Freimer, N. B., et al. (2008) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2008.11.005 · Cited by 162
Thornton, T. A., & McPeek, M. S. (2010) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2010.01.001 · Cited by 161
Expanding the range of ZNF804A variants conferring risk of psychosis
Steinberg, S., Mors, O. N., Børglum, A. D., Gústafsson, Ó., Werge, T. M., Mortensen, P. B., Andreassen, O. A., Sigurðsson, E., Thorgeirsson, T. E., Böttcher, Y., et al. (2010) · Molecular Psychiatry · doi:10.1038/mp.2009.149 · Cited by 163
Genome-wide Association Studies Identify Genetic Loci Associated With Albuminuria in Diabetes
Teumer, A., Tin, A., Sorice, R., Gorski, M., Yeo, N. C., Chu, A. Y., Li, M., Li, Y., Mijatovic, V., Ko, Y.-A., et al. (2015) · Diabetes · doi:10.2337/db15-1313 · Cited by 162
“Genomic-control (GC) (15) correction was applied when the GC factor was .”
MethodA PAX1 enhancer locus is associated with susceptibility to idiopathic scoliosis in females
Sharma, S., Londoño, D., Eckalbar, W. L., Gao, X., Zhang, D., Mauldin, K., Kou, I., Takahashi, A., Matsumoto, M., Kamiya, N., et al. (2015) · Nature Communications · doi:10.1038/ncomms7452 · Cited by 158
“Additionally, we checked for population stratification confounder effects by applying the genomic control (GC) method 62 .”
Heath, S. C., Gut, I. G., Brennan, P., McKay, J., Bencko, V., Fabiánová, E., Foretová, L., Georges, M., Janout, V., Kabesch, M., et al. (2008) · European Journal of Human Genetics · doi:10.1038/ejhg.2008.210 · Cited by 161
Genetic associations with schizophrenia: Meta-analyses of 12 candidate genes
Shi, J., Gershon, E. S., & Liu, C. (2008) · Schizophrenia Research · doi:10.1016/j.schres.2008.06.016 · Cited by 159
“Second, most case-control studies we analyzed did not address population stratification using genomic control (Devlin and Roeder, 1999; Reich and Goldstein, 2001), structured association (Pritchard and Rosenberg, 1999; Pritchard et al.”
BackgroundMethodAlves, A. C., Silva, N. M. G. D., Karhunen, V., Sovio, U., Das, S., Taal, H. R., Warrington, N. M., Lewin, A., Kaakinen, M., Cousminer, D. L., et al. (2019) · Science Advances · doi:10.1126/sciadv.aaw3095 · Cited by 158
Lerer, B., Macciardi, F. M., Segman, R. H., Adolfsson, R., Blackwood, D., Blairy, S., Del‐Favero, J., Dikeos, D. G., Kaneva, R. P., Lilli, R., et al. (2001) · Molecular Psychiatry · doi:10.1038/sj.mp.4000883 · Cited by 160
Kittles, R. A., Chen, W., Panguluri, R. K., Ahaghotu, C. A., Jackson, A., Adebamowo, C., Griffin, R., Williams, T., Ukoli, F. A. M., Adams-Campbell, L. L., et al. (2002) · Human Genetics · doi:10.1007/s00439-002-0731-5 · Cited by 161
“Recently, it has been proposed that unlinked genetic markers should be typed in order to detect, quantify, and correct for stratification in the case-control study (Pritchard and Rosenberg 1999; Pritchard et al. 2000; Devlin and Roeder 1999; Schork et al. 2001; Reich and Goldstein 2001).”
Biostatistical Aspects of Genome‐Wide Association Studies
Ziegler, A., König, I. R., & Thompson, J. R. (2008) · Biometrical Journal · doi:10.1002/bimj.200710398 · Cited by 165
Zhu, X., & Stephens, M. (2017) · The Annals of Applied Statistics · doi:10.1214/17-aoas1046 · Cited by 151
A genome-wide association analysis of serum iron concentrations
Tanaka, T., Roy, C. N., Yao, W., Matteini, A. M., Semba, R. D., Arking, D. E., Walston, J. D., Fried, L. P., Singleton, A., Guralnik, J. M., et al. (2009) · Blood · doi:10.1182/blood-2009-07-232496 · Cited by 162
Genomic Control to the extreme
Devlin, B., Bacanu, S.-A., & Roeder, K. (2004) · Nature Genetics · doi:10.1038/ng1104-1129 · Cited by 157
Self-citationNakanishi, H., Yamada, R., Gotoh, N., Hayashi, H., Yamashiro, K., Shimada, N., Ohno‐Matsui, K., Mochizuki, M., Saito, M., Iida, T., et al. (2009) · PLoS Genetics · doi:10.1371/journal.pgen.1000660 · Cited by 157
“Genomic Control (GC) method [37] revealed only a slight inflation of the test statistics (GC parameter l= 1.”
MethodStyrkársdóttir, U., Þorleifsson, G., Helgadottir, H. T., Bömer, N., Metrustry, S., Bierma‐Zeinstra, S., Strijbosch, A. M., Εvangelou, Ε., Hart, D. J., Beekman, M., et al. (2014) · Nature Genetics · doi:10.1038/ng.2957 · Cited by 158
The FOXE1 locus is a major genetic determinant for radiation-related thyroid carcinoma in Chernobyl
Takahashi, M., Saenko, V., Rogounovitch, T., Kawaguchi, T., Drozd, V. M., Takigawa-Imamura, H., Akulevich, N. M., Ratanajaraya, C., Mitsutake, N., Takamura, N., et al. (2010) · Human Molecular Genetics · doi:10.1093/hmg/ddq123 · Cited by 160
“Population stratification was assessed by the genomic control method (28).”
MethodAssociation Mapping in Crop Plants
Gupta, P. K., Kulwal, P. L., & Jaiswal, V. (2014) · Advances in genetics · doi:10.1016/b978-0-12-800271-1.00002-0 · Cited by 162
Genetic loci associated with heart rate variability and their effects on cardiac disease risk
Nolte, I. M., Muñoz, M. L., Tragante, V., Amare, A. T., Jansen, R., Vaez, A., von der Heyde, B., Avery, C. L., Bis, J. C., Dierckx, B., et al. (2017) · Nature Communications · doi:10.1038/ncomms15805 · Cited by 157
Sinnott-Armstrong, N., Naqvi, S., Rivas, M. A., & Pritchard, J. K. (2021) · eLife · doi:10.7554/elife.58615 · Cited by 152
Genetics of Venous Thrombosis: Insights from a New Genome Wide Association Study
Germain, M., Saut, N., Greliche, N., Dina, C., Lambert, J., Perret, C., Cohen, W., Oudot‐Mellakh, T., Antoni, G., Alessi, M., et al. (2011) · PLoS ONE · doi:10.1371/journal.pone.0025581 · Cited by 159
“The genomic control (GC) inflation factor was also computed according to the median test statistic [39].”
Method
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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