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
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
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Self-citationStacey, S., Gudbjartsson, D. F., Sulem, P., Bergþorsson, J. Þ., Kumar, R., Þorleifsson, G., Sigurðsson, Á., Jakobsdottir, M., Sigurgeirsson, B., Benediktsdóttir, K. R., et al. (2008) · Nature Genetics · doi:10.1038/ng.234 · Cited by 124
“We adjusted the results for familial relatedness between individuals and for potential population stratification using the method of genomic contro”
MethodInterethnic analyses of blood pressure loci in populations of East Asian and European descent
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Pausch, H., Flisikowski, K., Jung, S., Emmerling, R., Edel, C., Götz, K., & Fries, R. (2010) · Genetics · doi:10.1534/genetics.110.124057 · Cited by 128
“The genome-wide inflation factor was computed according to Devlin and Roeder (1999).”
BackgroundMethodInfluentialMbarek, H., Steinberg, S., Nyholt, D. R., Gordon, S. D., Miller, M., McRae, A. F., Hottenga, J., Day, F. R., Willemsen, G. A. H. M., de Geus, E. J. C., et al. (2016) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2016.03.008 · Cited by 120
“Relatedness was controlled for by using genomic control in all Icelandic association analyses.(43) The combined p value of the meta-analysis and the replication study was calculated by Fisher’s combined probability test.”
MethodEu‐ahsunthornwattana, J., Miller, E. N., Fakiola, M., Jerônimo, S. M. B., Blackwell, J. M., & Cordell, H. J. (2014) · PLoS Genetics · doi:10.1371/journal.pgen.1004445 · Cited by 128
“Regardless of which kinship coefficients are used, GRAMMAR was found to be conservative and to result in biased regression coefficients representing the SNP effects of interest [12], and so it was suggested that the final x(2) test statistics should be ‘re-inflated’ by multiplying by an appropriate estimated correctio…”
InfluentialStark, K. J., Reinhard, W., Grassl, M., Erdmann, J., Schunkert, H., Illig, T., & Hengstenberg, C. (2009) · PLoS ONE · doi:10.1371/journal.pone.0007729 · Cited by 123
“Recent GWA analyses [11,12] using a part of the current study sample (n = 1,021) revealed no population stratification effects within unrelated individuals form the German MI Family Study using the genomic control method [13].”
MethodPeters, M., Broer, L., Willemen, H., Eiriksdottir, G., Hocking, L., Holliday, K., Horan, M., Meulenbelt, I., Neogi, T., Popham, M., et al. (2012) · Annals of the Rheumatic Diseases · doi:10.1136/annrheumdis-2012-201742 · Cited by 115
A Genome-Wide Association Study (GWAS) for Bronchopulmonary Dysplasia
Wang, H., Julien, K. R. S., Stevenson, D. K., Hoffmann, T. J., Witte, J. S., Lazzeroni, L. C., Krasnow, M. A., Quaintance, C. C., Oehlert, J. W., Jelliffe‐Pawlowski, L. L., et al. (2013) · PEDIATRICS · doi:10.1542/peds.2013-0533 · Cited by 121
Genetic Case-Control Association Studies in Neuropsychiatry
Sullivan, P. F. (2001) · Archives of General Psychiatry · doi:10.1001/archpsyc.58.11.1015 · Cited by 121
“First, it can be argued that differences in genotype frequency and/or disease frequency must be fairly gross for stratification to produce an artifactually significant result(35) and that simply controlling for reported ancestry will greatly reduce the risk.(35,36) Consider a case-control association study of major de…”
BackgroundLogistic regression protects against population structure in genetic association studiesPreprint
Setakis, E., Stirnadel, H., & Balding, D. J. (2005) · Genome Research · doi:10.1101/gr.4346306 · Cited by 120
“Moreover, Devlin and Roeder (1999) argue that the deviation from 1 2 can adequately be encapsulated in an over-dispersion factor, , which takes value 1 in the absence of population structure.”
BackgroundMethodInfluentialA novel common variant in DCST2 is associated with length in early life and height in adulthood
van der Valk, R. J. P., Kreiner‐Møller, E., Kooijman, M. N., Guxens, M., Stergiakouli, E., Sääf, A. M., Bradfield, J. P., Geller, F., Hayes, M. G., Cousminer, D. L., et al. (2014) · Human Molecular Genetics · doi:10.1093/hmg/ddu510 · Cited by 121
“Genomic control (GC) (33) was applied to adjust the statistics generated within each cohort (see Supplementary Material, Table S1 for individual studylvalues).”
Association studies for quantitative traits in structured populations
Bacanu, S., Devlin, B., & Roeder, K. (2001) · Genetic Epidemiology · doi:10.1002/gepi.1045 · Cited by 120
Self-citationZhang, L., Guo, Y.-F., Liu, Y.-Z., Liu, Y.-J., Xiong, D.-H., Liu, X.-G., Wang, L., Yang, T.-L., Lei, S.-F., Guo, Y., et al. (2010) · Journal of Bone and Mineral Research · doi:10.1002/jbmr.36 · Cited by 119
“0 software, which uses both principalcomponent analysis and a genomic control approach to correct possible statistical bias caused by ancestral differences in wholegenome association studies.((18,19))”
MethodHarnessing genomics and genome biology to understand malaria biology
Volkman, S. K., Neafsey, D. E., Schaffner, S. F., Park, D. J., & Wirth, D. F. (2012) · Nature Reviews Genetics · doi:10.1038/nrg3187 · Cited by 119
Genome Scans for Detecting Footprints of Local Adaptation Using a Bayesian Factor Model
Duforet-Frebourg, N., Bazin, É., & Blum, M. G. B. (2014) · Molecular Biology and Evolution · doi:10.1093/molbev/msu182 · Cited by 127
“We consider the model of population divergence depicted in Figure 1.”
MethodA frameshift deletion in the sarcomere gene MYL4 causes early-onset familial atrial fibrillation
Gudbjartsson, D. F., Hólm, H., Sulem, P., Másson, G., Oddsson, Á., Magnússon, Ó. Þ., Saemundsdottir, J., Helgadottir, H. T., Helgason, H., Johannsdottir, H., et al. (2016) · European Heart Journal · doi:10.1093/eurheartj/ehw379 · Cited by 116
easyGWAS: A Cloud-Based Platform for Comparing the Results of Genome-Wide Association Studies
Grimm, D. G., Roqueiro, D., Salomé, P. A., Kleeberger, S., Tzovaras, B. G., Zhu, W., Liu, C., Lippert, C., Stegle, O., Schölkopf, B., et al. (2016) · The Plant Cell · doi:10.1105/tpc.16.00551 · Cited by 117
“The second tab, “ QQ-Plots, ” renders quantile-quantile plots and provides information about the genomic control factor (Devlin and Roeder, 1999) (Supplemental Text 5).”
BackgroundHuman population structure and genetic association studies.
Ziv, E., & Burchard, E. (2003) · Pharmacogenomics (London) · doi:10.1517/phgs.4.4.431.22758 · Cited by 127
Slager, S. L., & Schaid, D. J. (2001) · The American Journal of Human Genetics · doi:10.1086/320608 · Cited by 119
“If, however, one has reason to suspect that a given sample is subject to population stratification, then one can use the genomic control method as a possible correction (Devlin and Roeder 1999).”
MethodGenetic variability in response to amyloid beta deposition influences Alzheimer’s disease risk
Salih, D. A., Bayram, S., Guelfi, S., Reynolds, R. H., Shoai, M., Ryten, M., Brenton, J. W., Zhang, D., Matarin, M., Botia, J. A., et al. (2019) · Brain Communications · doi:10.1093/braincomms/fcz022 · Cited by 110
“Prior to the gene-based analyses all individual SNP P-values were corrected for the genomic inflation factor (k; to normalise for unaccounted variation, due to factors such as population stratification; Devlin and Roeder, 1999).”
Genome-Wide Association Study Identifies ALDH7A1 as a Novel Susceptibility Gene for Osteoporosis
Guo, Y., Tan, L., Lei, S., Yang, T., Chen, X., Zhang, F., Chen, Y., Pan, F., Yan, H., Liu, X., et al. (2010) · PLoS Genetics · doi:10.1371/journal.pgen.1000806 · Cited by 118
“To correct for potential population stratification that may lead to spurious association results, we estimated the inflation factor (l) for the GWAS sample using a method of genomic control [28].”
MethodOkada, Y., Kamatani, Y., Takahashi, A., Matsuda, K., Hosono, N., Ohmiya, H., Daigo, Y., Yamamoto, K., Kubo, M., Nakamura, Y., et al. (2010) · Human Molecular Genetics · doi:10.1093/hmg/ddq091 · Cited by 118
Common body mass index-associated variants confer risk of extreme obesity
Cotsapas, C. J., Speliotes, E. K., Hatoum, I. J., Greenawalt, D. M., Dobrin, R., Lum, P. Y., Suver, C., Chudin, E., Kemp, D. M., Reitman, M. L., et al. (2009) · Human Molecular Genetics · doi:10.1093/hmg/ddp292 · Cited by 121
Yang, J., Jiang, H., Yeh, C., Yu, J., Jeddeloh, J. A., Nettleton, D. S., & Schnable, P. S. (2015) · The Plant Journal · doi:10.1111/tpj.13029 · Cited by 118
“To attenuate the effects of population structure, a genomic control method (Devlin and Roeder, 1999) was implemented to adjust the v(2) test statistic (Experimental procedures).”
MethodInfluentialInvolvement of SMARCA2/BRM in the SWI/SNF chromatin-remodeling complex in schizophrenia
Koga, M., Ishiguro, H., Yazaki, S., Horiuchi, Y., Arai, M., Niizato, K., Iritani, S., Itokawa, M., Inada, T., Iwata, N., et al. (2009) · Human Molecular Genetics · doi:10.1093/hmg/ddp166 · Cited by 112
“The potential impact of population structure on this association study was evaluated by using the genomewide x(2) inflation factor, l, as a genomic control (38,39).”
MethodAllelic Analysis of Sheath Blight Resistance with Association Mapping in Rice
Jia, L., Yan, W., Zhu, C., Agrama, H. A., Jackson, A. K., Yeater, K. M., Li, X., Huang, B., Hu, B., McClung, A. M., et al. (2012) · PLoS ONE · doi:10.1371/journal.pone.0032703 · Cited by 117
“In order to control false positive rates, the genomic control (GC) method [72] was further used for correcting population structure.”
MethodCommon variants spanning PLK4 are associated with mitotic-origin aneuploidy in human embryos
McCoy, R. C., Demko, Z., Ryan, A., Banjevic, M., Hill, M., Sigurjonsson, S., Rabinowitz, M., Fraser, H. B., & Petrov, D. A. (2015) · Science · doi:10.1126/science.aaa3337 · Cited by 114
He, J., Meng, S., Zhao, T., Xing, G., Yang, S., Li, Y., Guan, R., Lu, J., Wang, Y., Xia, Q., et al. (2017) · Theoretical and Applied Genetics · doi:10.1007/s00122-017-2962-9 · Cited by 120
“The population structure bias may be caused by the admixture of heterogeneous populations or the inbreeding-caused relatedness among the materials, or mainly a mixture of them (Devlin and Roeder 1999; Campbell et al.”
BackgroundFunctional SNPs in CD244 increase the risk of rheumatoid arthritis in a Japanese population
Suzuki, A., Yamada, R., Kochi, Y., Sawada, T., Okada, Y., Matsuda, K., Kamatani, Y., Mori, M., Shimane, K., Hirabayashi, Y., et al. (2008) · Nature Genetics · doi:10.1038/ng.205 · Cited by 117
“We evaluated the first cohort for variable inflation with 83,567 SNPs in autosomal chromosomes using the genomic control metho”
MethodVariants in theGH-IGFaxis confer susceptibilityto lung cancerPreprint
Rudd, M. F., Webb, E. L., Matakidou, A., Sellick, G. S., Williams, R. D., Bridle, H. L., Eisen, T. G., & Houlston, R. S. (2006) · Genome Research · doi:10.1101/gr.5120106 · Cited by 120
“To detect and control for possible population stratification, we used the genomic control approach (Devlin and Roeder 1999), using all SNPs to estimate the stratification parameter ̂ and its associated 95% confidence interval (CI).”
MethodGenetic aspects of pathological gambling: a complex disorder with shared genetic vulnerabilities
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The complex genetics of multiple sclerosis: pitfalls and prospects
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“However, having completed a GWAS it is straightforward to identify ancestry and compensate for any stratification (Devlin and Roeder, 1999; Bacanu et al., 2000; Devlin et al., 2004).”
BackgroundDetecting Rare Variant Associations by Identity-by-Descent Mapping in Case-Control Studies
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“This assumption is wrong (Devlin and Roeder, 1999; Voight and Pritchard, 2005), but for a complex disease will not be too far off, provided the samples really do come from the same population.”
Backgroundgap : Genetic Analysis Package
Zhao, J. H. (2007) · Journal of Statistical Software · doi:10.18637/jss.v023.i08 · Cited by 117
“Notably, the following functions need further work: bt , kin.morgan , twinan90 (Williams et al. 1992), gcontrol (Devlin and Roeder 1999), mtdt (Sham 1997), s2k (Hirotsu et al. 2001).”
Background1000 Genomes-based meta-analysis identifies 10 novel loci for kidney function
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“Recent reports propose that population stratificationmay be addressed by genotyping for a large series of random markers throughout the genome, along with statistical adjustment for ethnic admixture [Devlin and Roeder, 1999; Pritchard and Rosenberg, 1999].”
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“To correct each study for residual population stratification or cryptic relatedness, themeta-analyseswere performedwith genomic control correction (40) by adjusting for the study-specific inflation factor (λ), which ranged from 1.”
Correcting for Population Structure and Kinship Using the Linear Mixed Model: Theory and Extensions
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“Since it is well established that ignoring this covariance in a test of association produces deflated p-values that do not follow a uniform distribution under the null [13], it is common to apply a LMM or include principal components as fixed effects in order to model the dependence structure [1].”
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“The genomic control parameter l was calculated for each analysis to assess test statistic inflation due to residual population stratification [34].”
Genome-wide association study of Stevens-Johnson Syndrome and Toxic Epidermal Necrolysis in Europe
Génin, E., Schumacher, M. C., Roujeau, J., Naldi, L., Liß, Y., Kazma, R., Sekula, P., Hovnanian, A., & Mockenhaupt, M. (2011) · Orphanet Journal of Rare Diseases · doi:10.1186/1750-1172-6-52 · Cited by 113
“A sensitivity analysis was performed to determine the number of PCs that should be accounted for and we decided to adjust only on the first two PCs (the genomic control coefficient lambda [26] was 1.”
Liu, X.-G., Tan, L.-J., Lei, S., Liu, Y., Shen, H., Wang, L., Yan, H., Guo, Y.-F., Xiong, D.-H., Chen, X., et al. (2009) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2009.02.004 · Cited by 113
Population admixture associated with disease prevalence in the Boston Puerto Rican health study
Lai, C., Tucker, K. L., Choudhry, S., Parnell, L. D., Mattei, J., García‐Bailo, B., Beckman, K. B., Burchard, E. G., & Ordovás, J. M. (2008) · Human Genetics · doi:10.1007/s00439-008-0612-7 · Cited by 111
“To overcome the problem associated with population substructure, genomic control (Devlin and Roeder 1999), ancestry index (Pritchard et al. 2000,Falush et al. 2003) and principal component analysis (PCA, Price et al. 2006;Patterson et al. 2006;Paschou et al. 2007) have been developed and applied to…”
Goddard, K. A. B., Tromp, G., Romero, R. J., Olson, J. M., Lu, Q. L., Xu, Z., Parimi, N., Nien, J. K., Gómez, R., Behnke, E., et al. (2006) · Human Heredity · doi:10.1159/000097926 · Cited by 113
Genome-wide association studies in cancer--current and future directions
Chung, C. C., Magalhães, W. C. S., Bosquet, J. G., & Chanock, S. J. (2009) · Carcinogenesis · doi:10.1093/carcin/bgp273 · Cited by 110
Geller, F., Feenstra, B., Carstensen, L., Pers, T. H., van Rooij, I. A. L. M., Körberg, I. B., Choudhry, S., Karjalainen, J. M., Schnack, T. H., Hollegaard, M. V., et al. (2014) · Nature Genetics · doi:10.1038/ng.3063 · Cited by 113
Genetic epidemiology of type 1 diabetes
Hirschhorn, J. N. (2003) · Pediatric Diabetes · doi:10.1034/j.1399-5448.2001.00013.x · Cited by 112
Association of TRPV4 gene polymorphisms with chronic obstructive pulmonary disease
Zhu, G., ICGN Investigators, Gulsvik, A., Bakke, P. S., Ghatta, S., Anderson, W. H., Lomas, D. A., Silverman, E. K., & Pillai, S. G. (2009) · Human Molecular Genetics · doi:10.1093/hmg/ddp111 · Cited by 111
“In the case--control data, we had previously genotyped a panel of 221 unlinked SNPs to detect population stratification by estimating an inflation factor l for genomic control (43,44), which did not show significant evidence of population stratification (inflation factor was 1.”
MethodGenome-Wide Association Studies of the PR Interval in African Americans
Smith, J. G., Magnani, J. W., Palmer, C. D., Meng, Y., Soliman, E. Z., Musani, S. K., Kerr, K. F., Schnabel, R. B., Lubitz, S. A., Sotoodehnia, N., et al. (2011) · PLoS Genetics · doi:10.1371/journal.pgen.1001304 · Cited by 111
“Genomic inflation factors were evaluated in each cohort prior to meta-analysis and in the combined results [32].”
Susceptibility loci revealed for bovine respiratory disease complex in pre-weaned holstein calves
Neibergs, H. L., Seabury, C. M., Wojtowicz, A. J., Wang, Z., Scraggs, E., Kiser, J. N., Neupane, M., Womack, J. E., Eenennaam, A. L. V., Hagevoort, G., et al. (2014) · BMC Genomics · doi:10.1186/1471-2164-15-1164 · Cited by 111
“…identify a reasonable number of principal components for correction of the input data, we first estimated the Genomic Inflation Factor Lambda ( λ ) [77] across increasing numbers of principal components for each Holstein population, with 9 (NM), 53 (CA) and 91 (CA + NM) principal components…”
Teo, Y. Y. (2008) · Current Opinion in Lipidology · doi:10.1097/mol.0b013e3282f5dd77 · Cited by 110
The impact of HLA-DRB1genes on extra-articular disease manifestations in rheumatoid arthritis
Turesson, C., Schaid, D. J., Weyand, C. M., Jacobsson, L., Goronzy, J. J., Petersson, I. F., Sturfelt, G. K., Nyhäll-Wåhlin, B.-M., Truedsson, L., Dechant, S. A., et al. (2005) · Arthritis Research & Therapy · doi:10.1186/ar1837 · Cited by 111
“This approach reduces to the usual Pearson χ2 statistic for comparing allele frequencies when genotype proportions match Hardy-Weinberg proportions [30], and is the preferred way to compare allele frequencies [31].”
MethodYang, B., Zhao, H., Kranzler, H. R., & Gelernter, J. E. (2005) · Genetic Epidemiology · doi:10.1002/gepi.20070 · Cited by 111
“In recent years, several methods have been proposed to allow valid analysis of genetic association in case-control samples by detecting and accounting for population structure [Devlin and Roeder, 1999; Pritchard et al., 2000a,b; Reich and Goldstein, 2001; Ripatti et al., 2001; Satten et al., 2001; Sillanpaa et al., 20…”
Li, M., Boehnke, M., & Abecasis, G. R. (2006) · The American Journal of Human Genetics · doi:10.1086/503711 · Cited by 112
Genetic association mapping at the crossroads: Which test and why? Overview and practical guidelines
Schulze, T. G., & McMahon, F. J. (2001) · American Journal of Medical Genetics · doi:10.1002/ajmg.10042 · Cited by 110
“The genomic control (GC) method [Devlin and Roeder, 1999; Bacanu et al., 2000] is based on genome screen data of biallelic markers.”
MethodA guide to genome‐wide association analysis and post‐analytic interrogation
Reed, E. R., Núñez, S., Kulp, D., Qian, J., Reilly, M. P., & Foulkes, A. S. (2015) · Statistics in Medicine · doi:10.1002/sim.6605 · Cited by 122
“The degree of deviation from this line is measured by the 𝜆 -statistic [35, 36], a value close to 1 suggests appropriate adjustment for potential substructure.”
BackgroundA genome-wide meta-analysis of association studies of Cloninger's Temperament Scales
Service, S. K., Verweij, K. J. H., Lahti, J. M. T., Congdon, E. L., Ekelund, J., Hintsanen, M., Räikkönen, K., Lehtimäki, T. J., Kähönen, M. A. P., Widén, E., et al. (2012) · Translational Psychiatry · doi:10.1038/tp.2012.37 · Cited by 108
Genome-wide association study and meta-analysis of intraocular pressure
Ozel, A. B., Moroi, S. E., Reed, D. M., Nika, M., Schmidt, C. M., Akbari, S., Scott, K., Rozsa, F. W., Pawar, H. S., Musch, D. C., et al. (2013) · Human Genetics · doi:10.1007/s00439-013-1349-5 · Cited by 111
“After single-SNP association tests, residual population stratification was assessed by using the genomic control factor (Devlin and Roeder 1999).”
Methodvan Setten, J., Išgum, I., Smolonska, J., Ripke, S., de Jong, P. A., Oudkerk, M., de Koning, H. J., Lammers, J. J., Zanen, P., Groen, H. J. M., et al. (2013) · Atherosclerosis · doi:10.1016/j.atherosclerosis.2013.02.039 · Cited by 110
“Genomic inflation (lGC) [18] was low before and after imputation (l 1.”
Backgroundde Villemereuil, P., Mouterde, M., Gaggiotti, O., & Till-Bottraud, I. (2018) · Journal of Ecology · doi:10.1111/1365-2745.12955 · Cited by 90
“A genomic inflation factor (GIF, a scaling factor used to correct for deviations of p-values from a uniform distribution, Devlin & Roeder, 1999) was computed using the resulting z-values, which were then transformed into corrected p-values when GIF was higher than 1.”
MethodFreidin, M. B., Tsepilov, Y. A., Palmer, M. R., Karssen, L. C., CHARGE Musculoskeletal Working Group, Suri, P., Aulchenko, Y. S., & Williams, F. M. K. (2019) · Pain · doi:10.1097/j.pain.0000000000001514 · Cited by 108
Zawistowski, M., Fritsche, L. G., Pandit, A., Vanderwerff, B. R., Patil, S. B., Schmidt, E. M., VandeHaar, P., Willer, C. J., Brummett, C. M., Kheterpal, S., et al. (2023) · Cell Genomics · doi:10.1016/j.xgen.2023.100257 · Cited by 110
Manuck, S. B., Flory, J. D., Ferrell, R. E., & Muldoon, M. F. (2003) · Psychoneuroendocrinology · doi:10.1016/s0306-4530(03)00094-5 · Cited by 109
“... but not with socio-economic status or serotonergic responsivity per se. Nonetheless, confi rmatory studies are clearly warranted, particularly by more defi nitive genetic methodologies, such as family-based association designs (e.g., transmissiondisequilibrium analysis) (Ewens and Spielman, 1995; Thomson, 1995; Al…”
BackgroundMethodInfluentialComparison of SSRs and SNPs in assessment of genetic relatedness in maize
Yang, X., Xu, Y., Shah, T. M., Li, H., Han, Z., Li, J., & Yan, J. (2011) · Genetica · doi:10.1007/s10709-011-9606-9 · Cited by 109
“structure, assuming that such a population structure has similar effects at all loci (Zheng et al. 2005; Devlin and Roeder 1999).”
BackgroundStrauss, J., Barr, C. L., George, C. J., King, N. A., Shaikh, S. A., Devlin, B., Kovács, M., & Kennedy, J. L. (2004) · American Journal of Medical Genetics Part B Neuropsychiatric Genetics · doi:10.1002/ajmg.b.30041 · Cited by 109
“GC analysis [Devlin and Roeder, 1999] revealed a robust correction factor of 0.”
BackgroundMethodInfluentialSelf-citationA genome wide association study of pulmonary tuberculosis susceptibility in Indonesians
Png, E., Alisjahbana, B., Sahiratmadja, E., Marzuki, S., Nelwan, R. H. H., Balabanova, Y., Nikolayevskyy, V., Drobniewski, F. A., Nejentsev, S., Adnan, I. A., et al. (2012) · BMC Medical Genetics · doi:10.1186/1471-2350-13-5 · Cited by 108
“As population stratification can confound case-control association studies [19-21], we performed a principal components (PC) analysis as implemented in EIGENSTRAT to identify and exclude 4 population outliers within PC1 and 2, from the Indonesian stage 1 dataset, see Additional file 1, Supplementary Figure S1 [21].”
BackgroundMethodInfluentialClerc, S. L., Limou, S., Coulonges, C., Carpentier, W., Dina, C., Taing, L., Delaneau, O., Labib, T., Sladek, R., Deveau, C., et al. (2009) · Journal of Infectious Diseases · doi:10.1086/605892 · Cited by 27
“We also computed the genomic inflation factor l [17].”
MethodAn update on the genetics of Gilles de la Tourette syndrome
Pauls, D. L. (2003) · Journal of Psychosomatic Research · doi:10.1016/s0022-3999(02)00586-x · Cited by 108
“One of the more promising approaches has been suggested by Devlin and Roeder [15].”
MethodSinner, M. F., Pfeufer, A., Akyol, M., Beckmann, B.-M., Hinterseer, M., Wacker, A., Perz, S., Sauter, W., Illig, T., Näbauer, M., et al. (2008) · European Heart Journal · doi:10.1093/eurheartj/ehm619 · Cited by 107
“Population stratification has been investigated across Germany according to the Genomic controls method.(37) The upper limit of the 95%”
MethodHysi, P. G., Valdes, A. M., Liu, F., Furlotte, N. A., Evans, D. M., Bataille, V. A., Visconti, A., Hemani, G., McMahon, G., Ring, S. M., et al. (2018) · Nature Genetics · doi:10.1038/s41588-018-0100-5 · Cited by 107
Dumitrescu, L. C., Ritchie, M. D., Brown-Gentry, K. D., Pulley, J. M., Basford, M., Denny, J. C., Oksenberg, J. R., Roden, D. M., Haines, J. L., & Crawford, D. C. (2010) · Genetics in Medicine · doi:10.1097/gim.0b013e3181efe2df · Cited by 106
Behavior of QQ-Plots and Genomic Control in Studies of Gene-Environment Interaction
Voorman, A., Lumley, T., McKnight, B., & Rice, K. M. (2011) · PLoS ONE · doi:10.1371/journal.pone.0019416 · Cited by 108
“Citation: Voorman A, Lumley T, McKnight B, Rice K (2011) Behavior of QQ-Plots and Genomic Control in Studies of Gene-Environment Interaction.”
InfluentialHu, Z., Zhang, H., Kan, G., Ma, D., Zhang, D., Shi, G., Hong, D., Zhang, G., & Yu, D. (2013) · Genetica · doi:10.1007/s10709-013-9723-8 · Cited by 106
“To obtain deeper insight into the relationships between the six traits, PCA was performed to identify the major sources of the variation in seed morphology.”
InfluentialCross-Ancestry Investigation of Venous Thromboembolism Genomic Predictors
Thibord, F., Klarin, D. M., Brody, J. A., Chen, M., Levin, M. G., Chasman, D. I., Goode, E. L., Hveem, K., Teder‐Laving, M., Martínez-Pérez, Á., et al. (2022) · Circulation · doi:10.1161/circulationaha.122.059675 · Cited by 105
COL4A1 Is Associated With Arterial Stiffness by Genome-Wide Association Scan
Tarasov, K. V., Sanna, S., Scuteri, A., Strait, J. B., Orrù, M., Parsa, A., Lin, P.-I., Maschio, A., Lai, S., Piras, M. G., et al. (2009) · Circulation: Cardiovascular Genetics · doi:10.1161/circgenetics.108.823245 · Cited by 104
Statistical analysis for genome-wide association study
Ping, Z., Zhao, Y., Cheng, Q., Li-wei, Z., Zhang, R., Jianwei, G., Jin, L., Liya, L., & Feng, C. (2015) · Journal of Biomedical Research · doi:10.7555/jbr.29.20140007 · Cited by 110
“In association analysis, population structure can cause spurious findings if not accounted for, and it is one of the most often cited reasons for non-replication of previously confirmed variants [33-34] .”
BackgroundOrr, N., Lemnrau, A., Cooke, R., Fletcher, O., Tomczyk, K., Jones, M. E., Johnson, N., Lord, C. J., Mitsopoulos, C., Zvelebil, M., et al. (2012) · Nature Genetics · doi:10.1038/ng.2417 · Cited by 105
Hoffmann, T. J., Keats, B. J. B., Yoshikawa, N., Schaefer, C. A., RISCH, N. J., & Lustig, L. R. (2016) · PLoS Genetics · doi:10.1371/journal.pgen.1006371 · Cited by 101
Tsai, H., Choudhry, S., Naqvi, M., Rodríguez-Cintrón, W., Burchard, E. G., & Ziv, E. (2005) · Human Genetics · doi:10.1007/s00439-005-0067-z · Cited by 102
“In general, the methods of correction for population stratification can be categorized into three classes (1) genomic control (2) ‘‘structured association’’ and (3) a semi-parametric method based on principal components analysis (Bacanu et al. 2000; Chakraborty et al. 1986; Devlin and Roeder 1999; Falush et al. 2003;…”
MethodGenetics, Transcriptomics, and Proteomics of Alzheimers Disease
Papassotiropoulos, A., Fountoulakis, M., Dunckley, T. L., Stephan, D. A., & Reiman, E. M. (2006) · The Journal of Clinical Psychiatry · doi:10.4088/jcp.v67n0418 · Cited by 105
Hettema, J. M., An, S., Bukszár, J., van den Oord, E. J. C. G., Neale, M. C., Kendler, K. S., & Chen, X. (2008) · Biological Psychiatry · doi:10.1016/j.biopsych.2008.03.014 · Cited by 106
Zhai, G., Teumer, A., Stolk, L., Perry, J. R. B., Vandenput, L., Coviello, A. D., Koster, A., Bell, J. T., Bhasin, S., Eriksson, J., et al. (2011) · PLoS Genetics · doi:10.1371/journal.pgen.1002025 · Cited by 107
“Further, we corrected for population stratification by applying the genomic control method [27]; the lGC in the meta-analysis is 1.”
BackgroundMethodGenome-Wide Association Studies of Skeletal Phenotypes: What We Have Learned and Where We Are Headed
Hsu, Y., & Kiel, D. P. (2012) · The Journal of Clinical Endocrinology & Metabolism · doi:10.1210/jc.2012-1890 · Cited by 109
Yang, S. Y., Castellani, C. A., Longchamps, R. J., Pillalamarri, V., O'Rourke, B. P., Güallar, E., & Arking, D. E. (2021) · Genome Research · doi:10.1101/gr.269381.120 · Cited by 103
“71) [26].”
MethodCommon genetic variants in pre-microRNAs and risk of gallbladder cancer in North Indian population
Srivastava, K., Srivastava, A., & Mittal, B. (2010) · Journal of Human Genetics · doi:10.1038/jhg.2010.54 · Cited by 103
“Sobin, L.H., Wittekind, C.h.), pp 170–173 (Wiley-Liss, New York, 1997).”
InfluentialThe Impact of Divergence Time on the Nature of Population Structure: An Example from Iceland
Price, A. L., Helgason, A., Pálsson, S., Stefánsson, H., Clair, D. S., Andreassen, O. A., Reich, D., Kong, A., & Stefánsson, K. (2009) · PLoS Genetics · doi:10.1371/journal.pgen.1000505 · Cited by 99
“) This means that when the method of genomic control [40] is applied, the inflation factor l is equal to 1+NFST, and that dividing association statistics by l results in a x(2) (1 d.”
MethodGenome-wide association study identifies loci on 12q24 and 13q32 associated with Tetralogy of Fallot
Cordell, H. J., Töpf, A., Mamasoula, C., Postma, A. V., Bentham, J., Zélénika, D., Heath, S. C., Blue, G. M., Cosgrove, C., Granados-Riveron, J. T., et al. (2013) · Human Molecular Genetics · doi:10.1093/hmg/dds552 · Cited by 101
“076) (9), possibly due to unmodelled population substructure.”
BackgroundLee, S. H., Choi, B., Lim, D., Gondro, C., Cho, Y. M., Dang, C., Sharma, A., Jang, G. W., Lee, K., Yoon, D., et al. (2013) · PLoS ONE · doi:10.1371/journal.pone.0074677 · Cited by 103
“An important prerequisite for unbiased QTL mapping is homogeneity of the mapping population [12].”
BackgroundMitochondrial DNA Haplogroup D4a Is a Marker for Extreme Longevity in Japan
Bilal, E., Rabadán, R., Alexe, G., Fuku, N., Ueno, H., Nishigaki, Y., Fujita, Y., Ito, M., Arai, Y., Hirose, N., et al. (2008) · PLoS ONE · doi:10.1371/journal.pone.0002421 · Cited by 103
“Several methods [18–21] have been proposed to factor out associations due to population structure and identify real functional polymorphisms.”
Germain, M., Eyries, M., Montani, D., Poirier, O., Girerd, B., Dorfmüller, P., Coulet, F., Nadaud, S., Maugenre, S., Guignabert, C., et al. (2013) · Nature Genetics · doi:10.1038/ng.2581 · Cited by 103
Tidball, J. G., & Wehling‐Henricks, M. (2005) · Current Opinion in Rheumatology · doi:10.1097/01.bor.0000179948.65895.1a · Cited by 105
Matching Strategies for Genetic Association Studies in Structured Populations
Hinds, D. A., Stokowski, R. P., Patil, N., Konvicka, K., Kershenobich, D., Cox, D., & Ballinger, D. G. (2004) · The American Journal of Human Genetics · doi:10.1086/381716 · Cited by 100
“Genomic control (Devlin and Roeder 1999) provides another approach to estimating the magnitude of the effect of population structure in an association study.”
Fine mapping in 94 inbred mouse strains using a high-density haplotype resource
Kirby, A., Kang, H. M., Wade, C. M., Cotsapas, C., Kostem, E., Han, B., Furlotte, N., Kang, E. Y., Rivas, M., Bogue, M. A., et al. (2010) · Genetics · doi:10.1534/genetics.110.115014 · Cited by 102
“The genomic control inflation factor was computed by taking the median P-value and computing the corresponding x2 statistic divided by 0.455 (Devlin and Roeder 1999).”
MethodInfluentialKanai, M., Tanaka, T., & Okada, Y. (2016) · Journal of Human Genetics · doi:10.1038/jhg.2016.72 · Cited by 98
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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