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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“Recent attempts to correct association tests either for unknown population stratification and cryptic relatedness (Devlin and Roeder 1999) or for the sampling of related subjects in outbred populations (Slager and Schaid 2001) used the Armitage trend test (Armitage 1955), which is genotype based rather than allele bas…”
BackgroundMethodInfluentialGenome-Wide Association Scan of Trait Depression
Terracciano, A., Tanaka, T., Sutin, A. R., Sanna, S., Deiana, B., Lai, S., Uda, M., Schlessinger, D., Abecasis, G. R., Ferrucci, L., et al. (2010) · Biological Psychiatry · doi:10.1016/j.biopsych.2010.06.030 · Cited by 150
“In the SardiNIA sample, we checked the genomic control value for our genome-wide association analyses (44), and we did a principal component analysis of genome-wide SNP data in a subset of unrelated individuals (45).”
MethodA Genome-Wide Scan of Ashkenazi Jewish Crohn's Disease Suggests Novel Susceptibility Loci
Kenny, E. E., Pe’er, I., Karban, A. A., Ozelius, L. J., Mitchell, A. A., Ng, S. M. E., Erazo, M., D, H. O. M., Abraham, C., Abreu, M. T., et al. (2012) · PLoS Genetics · doi:10.1371/journal.pgen.1002559 · Cited by 163
“Any overinflation of the p-value distributions was adjusted by genomic control to approximate normality uniform p-value distribution [20].”
BackgroundMethodStorey, J. D. (2011) · International Encyclopedia of Statistical Science · doi:10.1007/978-3-642-04898-2_248 · Cited by 152
Arloth, J., Bogdan, R., Weber, P., Frishman, G., Menke, A., Wagner, K. V., Balsevich, G., Schmidt, M. V., Karbalai, N., Czamara, D., et al. (2015) · Neuron · doi:10.1016/j.neuron.2015.05.034 · Cited by 142
“The genomic control inflation factor ( l gc ; Devlin and Roeder, 1999) was calculated for every GR-response eQTL gene expression probe (n = 297) based on the genome-wide genotype data ( l gc ).”
Genetic predictors of medically refractory ulcerative colitis
Haritunians, T., Taylor, K. D., Targan, S. R., Dubinsky, M. C., Ippoliti, A., Kwon, S., Guo, X., MELMED, G. Y., Berel, D., Mengesha, E., et al. (2010) · Inflammatory Bowel Diseases · doi:10.1002/ibd.21293 · Cited by 150
“06 for MR-UC versus non-MR-UC, and MR-UC cases versus non-IBD controls analyses, respectively.(36)”
ResultPolygenic Overlap Between C-Reactive Protein, Plasma Lipids, and Alzheimer Disease
Desikan, R. S., Schork, A. J., Wang, Y., Thompson, W. K., Dehghan, A., Ridker, P. M., Chasman, D. I., McEvoy, L. K., Holland, D., Chen, C.-H., et al. (2015) · Circulation · doi:10.1161/circulationaha.115.015489 · Cited by 154
Multiple Loci within the Major Histocompatibility Complex Confer Risk of Psoriasis
Feng, B., Sun, L.-D., Soltani‐Arabshahi, R., Bowcock, A. M., Nair, R. P., Stuart, P. E., Elder, J. T., Schrodi, S. J., Begovich, A. B., Abecasis, G. R., et al. (2009) · PLoS Genetics · doi:10.1371/journal.pgen.1000606 · Cited by 154
“Moreover, the genomic control [37] parameter of our samples was 1.”
BackgroundAn evaluation of methods correcting for cell-type heterogeneity in DNA methylation studies
McGregor, K., Bernatsky, S., Colmegna, I., Hudson, M., Pastinen, T., Labbe, A., & Greenwood, C. M. T. (2016) · Genome biology · doi:10.1186/s13059-016-0935-y · Cited by 148
“One of these metrics is the genomic inflation factor (GIF) [28], which is the slope of the lines seen in Fig.”
BackgroundLarge-scale SNP analysis reveals clustered and continuous patterns of human genetic variation
Shriver, M. D., Mei, R., Parra, E. J., Sonpar, V. A., Halder, I., Tishkoff, S. A., Schurr, T. G., Zhadanov, S. I., Osipova, L. P., Brutsaert, T. D., et al. (2005) · Human Genomics · doi:10.1186/1479-7364-2-2-81 · Cited by 150
Winkler, T. W., Grassmann, F., Brandl, C., Kiel, C., Günther, F., Strunz, T., Weidner, L., Zimmermann, M. E., Korb, C. A., Poplawski, A., et al. (2020) · BMC Medical Genomics · doi:10.1186/s12920-020-00760-7 · Cited by 138
Genome-wide pharmacogenomic analysis of response to treatment with antipsychotics
McClay, J. L., Adkins, D. E., Åberg, K. A., Stroup, T. S., Perkins, D. O., Vladimirov, V. I., Lieberman, J. A., Sullivan, P. F., & van den Oord, E. J. C. G. (2009) · Molecular Psychiatry · doi:10.1038/mp.2009.89 · Cited by 150
Loci influencing blood pressure identified using a cardiovascular gene-centric array
Ganesh, S. K., Tragante, V., Guo, W., Guo, Y., Lanktree, M. B., Smith, E. N., Johnson, T., Castillo, B. A., Barnard, J., Baumert, J., et al. (2013) · Human Molecular Genetics · doi:10.1093/hmg/dds555 · Cited by 149
“Genomic control (41) was applied to each study result and then to the meta-analysis summary data to control effects possibly due to population stratification or cryptic relatedness.”
MethodModeration of antidepressant response by the serotonin transporter gene
Huezo-Diaz, P., Uher, R., Smith, R. G., Rietschel, M., Henigsberg, N., Marušiˇ, A., Mors, O. N., Maier, W., Hauser, J., Souery, D., et al. (2009) · The British Journal of Psychiatry · doi:10.1192/bjp.bp.108.062521 · Cited by 148
HLA class II sequence variants influence tuberculosis risk in populations of European ancestry
Sveinbjörnsson, G., Gudbjartsson, D. F., Halldórsson, B. V., Kristinsson, K. G., Gottfreðsson, M., Barrett, J. C., Gudmundsson, L. J., Blöndal, K., Gylfason, A., Gudjonsson, S. A., et al. (2016) · Nature Genetics · doi:10.1038/ng.3498 · Cited by 154
HLA Class II Locus and Susceptibility to Podoconiosis
Ayele, F. T., Adeyemo, A., Finan, C., Hailu, E., Sinnott, P. J., Burlinson, N. D., Aseffa, A., Rotimi, C. N., Newport, M. J., & Davey, G. (2012) · New England Journal of Medicine · doi:10.1056/nejmoa1108448 · Cited by 150
Utsunomiya, Y. T., do Carmo, A. S., Carvalheiro, R., Neves, H. H. D. R., Matos, M. C., Zavarez, L. B., O’Brien, A. M. P., Sölkner, J., McEwan, J. C., Cole, J. B., et al. (2013) · BMC Genetics · doi:10.1186/1471-2156-14-52 · Cited by 154
“1, the inflation was considered acceptable, and the Genomic Control (GC) correction was applied to adjust for that inflation [47].”
MethodLikelihood-Based Inference on Haplotype Effects in Genetic Association Studies
Lin, D., & Zeng, D. (2006) · Journal of the American Statistical Association · doi:10.1198/016214505000000808 · Cited by 146
Genome-wide association study identifies three novel loci in Fuchs endothelial corneal dystrophy
Afshari, N. A., Igo, R. P., Morris, N. J., Stambolian, D. E., Sharma, S., Pulagam, V. L., Dunn, S. P., Stamler, J. F., Truitt, B. J., Rimmler, J. B., et al. (2017) · Nature Communications · doi:10.1038/ncomms14898 · Cited by 147
Multistage genome-wide association meta-analyses identified two new loci for bone mineral density
Zhang, L., Choi, H. J., Estrada, K., Leo, P. J., Li, J., Pei, Y., Zhang, Y., Lin, Y., Shen, H., Liu, Y.-Z., et al. (2013) · Human Molecular Genetics · doi:10.1093/hmg/ddt575 · Cited by 148
“Genomic control inflation factor (33) was estimated for each individual GWAS.”
MethodMorris, A. P., Le, T. H., Wu, H., Akbarov, A., van der Most, P. J., Hemani, G., Smith, G. D., Mahajan, A., Gaulton, K. J., Nadkarni, G. N., et al. (2018) · Nature Communications · doi:10.1038/s41467-018-07867-7 · Cited by 141
Werling, D. M., Pochareddy, S., Choi, J., An, J., Sheppard, B. K., Peng, M., Li, Z., Dastmalchi, C., Santpere, G., Sousa, A. M. M., et al. (2020) · Cell Reports · doi:10.1016/j.celrep.2020.03.053 · Cited by 134
“…analyses were adequately adjusted for differences in sample ancestry, we calculated genomic control, or lambda, an estimate of inflation of genetic association signal (Devlin and Roeder, 1999), from the results of each of the three analyses (complete sample, prenatal-only, postnatal-only).”
Self-citationA Simple and Improved Correction for Population Stratification in Case-Control Studies
Epstein, M. P., Allen, A. S., & Satten, G. A. (2007) · The American Journal of Human Genetics · doi:10.1086/516842 · Cited by 143
SNP-Based Analysis of Genetic Substructure in the German Population
Steffens, M., Lamina, C., Illig, T., Bettecken, T., Vogler, R., Entz, P., Suk, E.-K., Toliat, M. R., Klopp, N., Caliebe, A., et al. (2006) · Human Heredity · doi:10.1159/000095850 · Cited by 144
“These GC SNPs were selected according to a set of rules envisaged by Devlin and Roeder (1999) and which were formalized by the Bonn group ( table 1 ).”
MethodSelf-citationA network of dopaminergic gene variations implicated as risk factors for schizophrenia.
Talkowski, M. E., Kirov, G., Bamne, M., Georgieva, L., Torres, G. E., Mansour, H. A., Chowdari, K., Milanova, V., Wood, J., McClain, L., et al. (2008) · Human Molecular Genetics · doi:10.1093/hmg/ddm347 · Cited by 154
“Differences in genotype distributions between cases and controls were evaluated with the Armitage trends test (SAS software) (58).”
BackgroundMethodSelf-citationGenetic Signatures of Exceptional Longevity in Humans
Sebastiani, P., Solovieff, N., Puca, A., Hartley, S. W., Melista, E., Andersen, S., Dworkis, D. A., Wilk, J. B., Myers, R. H., Steinberg, M. H., et al. (2010) · Science · doi:10.1126/science.1190532 · Cited by 141
“We estimated the genomic control factor as described in [88].”
MethodRetractedTakeuchi, F., Isono, M., Nabika, T., Katsuya, T., Sugiyama, T., Yamaguchi, S., Kobayashi, S., Ogihara, T., Yamori, Y., Fujioka, A., et al. (2011) · Circulation Journal · doi:10.1253/circj.cj-10-0774 · Cited by 146
Selection against variants in the genome associated with educational attainment
Kong, A., Frigge, M. L., Thorleifsson, G., Stefansson, H., Young, A. I., Zink, F., Jonsdottir, G. A., Okbay, A., Sulem, P., Masson, G., et al. (2017) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1612113114 · Cited by 168
“Devlin B, Roeder K (1999) Genomic control for association studies.”
MethodSequence variants at CYP1A1–CYP1A2 and AHR associate with coffee consumption
Sulem, P., Gudbjartsson, D. F., Geller, F., Prokopenko, I., Feenstra, B., Aben, K. K. H., Franke, B., den Heijer, M., Kovacs, P. L., Stümvoll, M., et al. (2011) · Human Molecular Genetics · doi:10.1093/hmg/ddr086 · Cited by 144
Osman, W. M., Low, S., Takahashi, A., Kubo, M., & Nakamura, Y. (2012) · Human Molecular Genetics · doi:10.1093/hmg/dds103 · Cited by 145
“30, we applied a logistic regression model incorporating age, gender and the first two eigenvectors as covariates for the analysis, in addition to apply the genomic control method (15) (lGC 1⁄4 1.”
MethodΕvangelou, Ε., Valdes, A. M., Kerkhof, H. J. M., Styrkársdóttir, U., Zhu, Y., Meulenbelt, I., Lories, R. J. U., Karassa, F. B., Tylżanowski, P., Bos, S. D., et al. (2010) · Annals of the Rheumatic Diseases · doi:10.1136/ard.2010.132787 · Cited by 145
“Each team performed an association test per gender for knee OA under a per-allele model. The λ inflation factor was calculated per gender-specific effect size using the genomic control method”
MethodA principal components regression approach to multilocus genetic association studies
Wang, K., & Abbott, D. (2007) · Genetic Epidemiology · doi:10.1002/gepi.20266 · Cited by 144
“If some unobserved latent stratification variables are of concern, one can implement a genomic control method to adjust for the inflation of the test statistic [Devlin and Roeder, 1999; Bacanu et al., 2002].”
MethodKawaguchi, T., Shima, T., Mizuno, M., Mitsumoto, Y., Umemura, A., Kanbara, Y., Tanaka, S., Sumida, Y., Yasui, K., Takahashi, M., et al. (2018) · PLoS ONE · doi:10.1371/journal.pone.0185490 · Cited by 142
Correction for hidden confounders in the genetic analysis of gene expression
Listgarten, J., Kadie, C. M., Schadt, E. E., & Heckerman, D. E. (2010) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1002425107 · Cited by 145
“The λ statistic, pervasive in GWAS studies and used to help judge inflation/ deflation of p-value distributions, is defined as the ratio of the median observed to median theoretical p-value, after conversion from p-value space to log-likelihood space by way of an inverse chi-square mapping (10, 18).”
BackgroundMethodInfluentialThe genetic dissection of quantitative traits in crops
Semagn, K., Bjørnstad, Å., & Xu, Y. (2010) · Electronic Journal of Biotechnology · doi:10.2225/vol13-issue5-fulltext-14 · Cited by 141
Population Stratification in the Candidate Gene Study: Fatal Threat or Red Herring?
Hutchison, K. E., Stallings, M. C., McGeary, J. E., & Bryan, A. D. (2004) · Psychological Bulletin · doi:10.1037/0033-2909.130.1.66 · Cited by 142
Yang, Q., Wu, H., Guo, C., & Fox, C. S. (2010) · Genetic Epidemiology · doi:10.1002/gepi.20497 · Cited by 142
“The genomic control parameter [Devlin and Roeder, 1999] that measures inflation due to population admixture or other confounders was 1.04, 1.02, for GWAS of UA and gout respectively, and 1 for all three combining statistics approaches.”
BackgroundInfluentialWang, M., Jiang, N., Jia, T., Leach, L. J., Cockram, J., Waugh, R., Ramsay, L., Thomas, B., & Luo, Z. (2011) · Theoretical and Applied Genetics · doi:10.1007/s00122-011-1697-2 · Cited by 151
“b̂ is the estimate of regression coefficient b and SE is the standard error) as a chi-square test statistic and hence the inflation factor k can be estimated from a number of ‘null’ markers using similar methodology to the case–control settings (Devlin and Roeder 1999).”
BackgroundMethodInfluentialGenome-wide association study of kidney function decline in individuals of European descent
Gorski, M., Tin, A., Garnaas, M., McMahon, G. M., Chu, A. Y., Tayo, B. O., Pattaro, C., Teumer, A., Chasman, D. I., Chalmers, J. P., et al. (2014) · Kidney International · doi:10.1038/ki.2014.361 · Cited by 140
“We performed genomic control correction if the inflation factor λ in the study files was greater than 1 (1st GC correction) or if it was greater than 1 in the metaanalysis result (2nd GC correction) [51].”
MethodParks, T., Mirabel, M., Kado, J. H., Auckland, K., Nowak, J., Rautanen, A., Mentzer, A. J., Marijon, É., Jouven, X., Perman, M. L., et al. (2017) · Nature Communications · doi:10.1038/ncomms14946 · Cited by 142
Sixteen new lung function signals identified through 1000 Genomes Project reference panel imputation
Artigas, M. S., Wain, L. V., Miller, S., Kheirallah, A. K., Huffman, J. E., Ντάλλα, Ι., Shrine, N. R. G., Obeidat, M., Trochet, H., McArdle, W. L., et al. (2015) · Nature Communications · doi:10.1038/ncomms9658 · Cited by 142
Genetic Association Studies in Stroke
Dichgans, M., & Markus, H. S. (2005) · Stroke · doi:10.1161/01.str.0000177498.21594.9e · Cited by 141
Hatzig, S., Frisch, M., Breuer, F., Nési, N., Ducournau, S., Wagner, M.-H., Leckband, G., Abbadi, A., & Snowdon, R. J. (2015) · Frontiers in Plant Science · doi:10.3389/fpls.2015.00221 · Cited by 140
Aston, K. I., & Carrell, D. T. (2009) · Journal of Andrology · doi:10.2164/jandrol.109.007971 · Cited by 143
“In addition, overall genomic control (GC) correction factors were calculated with each association test as another means of detecting any cryptic population stratification within the samples (Devlin and Roeder, 1999).”
MethodCommon and low-frequency variants associated with genome-wide recombination rate
Kong, A., Þorleifsson, G., Frigge, M. L., Másson, G., Gudbjartsson, D. F., Villemoes, R., Magnúsdóttir, E., Olafsdottir, S. B., Þorsteinsdóttir, U., & Stefánsson, K. (2013) · Nature Genetics · doi:10.1038/ng.2833 · Cited by 138
Inheritance Beyond Plain Heritability: Variance-Controlling Genes in Arabidopsis thaliana
Shen, X., Pettersson, M. E., Rönnegård, L., & Carlborg, Ö. (2012) · PLoS Genetics · doi:10.1371/journal.pgen.1002839 · Cited by 136
“The false positive rate (FPR) of the vGWAS is very low for any sample size and LAF, as shown by simulations (Figure A3 and A4 in Text S1), which supports the theoretical expectation of a low false positive rate for the Brown-Forsythe test in a vGWAS [16] and that GC is useful for filtering out false positive signals d…”
BackgroundResultFan, Q., Verhoeven, V. J. M., Wojciechowski, R., Barathi, V. A., Hysi, P. G., Guggenheim, J. A., Höhn, R., Vitart, V., Khawaja, A. P., Yamashiro, K., et al. (2016) · Nature Communications · doi:10.1038/ncomms11008 · Cited by 139
Molecular Genetic Studies of Gene Identification for Osteoporosis: A 2004 Update
Liu, Y., Shen, H., Xiao, P., Xiong, D.-H., Li, L.-H., Recker, R. R., & Deng, H. (2006) · Journal of Bone and Mineral Research · doi:10.1359/jbmr.051002 · Cited by 139
Unbiased methods for population‐based association studies
Devlin, B., Roeder, K., & Bacanu, S. (2001) · Genetic Epidemiology · doi:10.1002/gepi.1034 · Cited by 141
“To estimate two choices are natural: a robust estimator such as the median of the 2 test statistics, divided by 0.456 (Devlin and Roeder 1999), or the mean (Reich and Goldstein 2001).”
BackgroundMethodResultInfluentialSelf-citationZhang, L., Silva, T. C., Young, J. I., Gomez, L., Schmidt, M. A., Hamilton-Nelson, K. L., Kunkle, B. W., Chen, X., Martin, E. R., & Wang, L. (2020) · Nature Communications · doi:10.1038/s41467-020-19791-w · Cited by 139
Genome-wide association analysis identifies six new loci associated with forced vital capacity
Loth, D. W., Artigas, M. S., Gharib, S. A., Wain, L. V., Franceschini, N., Koch, B., Pottinger, T. D., Smith, A. V., Duan, Q., Oldmeadow, C. J., et al. (2014) · Nature Genetics · doi:10.1038/ng.3011 · Cited by 137
Using ancestry-informative markers to define populations and detect population stratification
Enoch, M., Shen, P.-H., Xu, K., Hodgkinson, C., & Goldman, D. (2006) · Journal of Psychopharmacology · doi:10.1177/1359786806066041 · Cited by 140
“Two recently derived statistical methods, Structured Association (Pritchard et al., 2000a, b) and Genomic Control (Devlin and Roeder, 1999; Devlin et al., 2001), are theoretically able to identify and correct population stratification in cases and controls through the analysis of a set of genomic…”
BackgroundMethodInfluentialNewman, A. B., Walter, S., Lunetta, K. L., Garcia, M. E., Slagboom, P. E., Christensen, K., Arnold, A. M., Aspelund, T., Aulchenko, Y. S., Benjamin, E. J., et al. (2010) · The Journals of Gerontology Series A · doi:10.1093/gerona/glq028 · Cited by 139
The SERPINE2 Gene is Associated with Chronic Obstructive Pulmonary Disease in Two Large Populations
Zhu, G., Warren, L. L., Aponte, J. L., Gulsvik, A., Bakke, P. S., Anderson, W. H., Lomas, D. A., Silverman, E. K., & Pillai, S. G. (2007) · American Journal of Respiratory and Critical Care Medicine · doi:10.1164/rccm.200611-1723oc · Cited by 136
Characterizing the genetic basis of methylome diversity in histologically normal human lung tissue
Shi, J., Marconett, C. N., Duan, J., Hyland, P. L., Li, P., Wang, Z., Wheeler, W., Zhou, B., Campan, M., Lee, D. S., et al. (2014) · Nature Communications · doi:10.1038/ncomms4365 · Cited by 137
Exome sequencing and complex disease: practical aspects of rare variant association studies
Do, R., Kathiresan, S., & Abecasis, G. R. (2012) · Human Molecular Genetics · doi:10.1093/hmg/dds387 · Cited by 143
Scalable privacy-preserving data sharing methodology for genome-wide association studies
Yu, F., Fienberg, S. E., Slavković, A., & Uhler, C. (2014) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2014.01.008 · Cited by 136
“Following the notation in [20], we can summarize the data for a single SNP in a case-control study with R cases and S controls using a 2 × 3 genotype contingency table shown in Table 1, or a 2 × 2 allelic contingency table shown in Table 2.”
MethodLi, Q., & Yu, K. F. (2007) · Genetic Epidemiology · doi:10.1002/gepi.20296 · Cited by 138
“…to evaluate the performance of the proposed method (called MDS) and to compare it with other existing methods, including the LRT based on the logistic regression model without the adjustment for PS, the LRT with GC adjustment [Devlin and Roeder, 1999] and the EIGENSTRAT [Price et al., 2006] method.”
BackgroundMethodInfluentialTimpson, N. J., Tobias, J. H., Richards, J. B., Soranzo, N., Duncan, E. L., Sims, A. M., Whittaker, P., Kumanduri, V., Zhai, G., Pourcain, B. S., et al. (2009) · Human Molecular Genetics · doi:10.1093/hmg/ddp052 · Cited by 136
“02), the genomic-control inflation factor (34), indicated only a small degree of population substructure in both samples.”
BackgroundTree and spline based association analysis of gene–gene interaction models for ischemic stroke
Cook, N. R., Zee, R. Y. L., & Ridker, P. M. (2004) · Statistics in Medicine · doi:10.1002/sim.1749 · Cited by 136
“In addition, genomic control was used to assess the potential impact of population strati cation [14], but these data were not found to exhibit such strati cation.”
MethodTzeng, J., Devlin, B., Wasserman, L., & Roeder, K. (2003) · The American Journal of Human Genetics · doi:10.1086/373881 · Cited by 136
“They also showed how the matching statistic could be adjusted for population substructure, by using the concept of “genomic control” introduced by Devlin and Roeder (1999). Still, Tzeng et al.”
InfluentialSelf-citationLiu, L., Sabo, A., Neale, B. M., Nagaswamy, U., Stevens, C., Lim, E., Bodea, C. A., Muzny, D., Reid, J. G., Banks, E., et al. (2013) · PLoS Genetics · doi:10.1371/journal.pgen.1003443 · Cited by 135
“We investigate the effects of population structure by calculating the genomic control inflation factor l [34] when the test is performed with and without including 10 eigen-vectors for ancestry obtained from genotypes of CV [29].”
MethodSelf-citationGenetic approaches to stature, pubertal timing, and other complex traits
Palmert, M. R., & Hirschhorn, J. N. (2003) · Molecular Genetics and Metabolism · doi:10.1016/s1096-7192(03)00107-0 · Cited by 135
Friendship and natural selection
Christakis, N. A., & Fowler, J. H. (2014) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1400825111 · Cited by 139
Yaeger, R., Avila-Bront, A., Abdul, K., Nolan, P. C., Grann, V., Birchette, M. G., Choudhry, S., Burchard, E., Beckman, K., Gorroochurn, P., et al. (2008) · Cancer Epidemiology, Biomarkers and Prevention · doi:10.1158/1055-9965.epi-07-2505 · Cited by 144
“and inconsistent, because they may potentially vary within the same individual over time (12, 13).”
BackgroundUsing biological networks to search for interacting loci in genome-wide association studies
Emily, M., Mailund, T., Hein, J., Schauser, L., & Schierup, M. H. (2009) · European Journal of Human Genetics · doi:10.1038/ejhg.2009.15 · Cited by 135
Pervjakova, N., Moen, G.-H., Borges, M. C., Ferreira, T. C., Cook, J. P., Allard, C., Beaumont, R. N., Canouil, M., Hatem, G., Heiskala, A., et al. (2022) · Human Molecular Genetics · doi:10.1093/hmg/ddac050 · Cited by 132
“Study-level association summary statistics (P-values and standard error of allelic effects) were corrected for residual structure by means of genomic control (54) if the inflation factor was > 1 (Supplementary Material, Table S3).”
MethodNonparametric Tests of Association of Multiple Genes with Human Disease
Schaid, D. J., McDonnell, S. K., Hebbring, S. J., Cunningham, J. M., & Thibodeau, S. N. (2005) · The American Journal of Human Genetics · doi:10.1086/429838 · Cited by 135
“For this type of scoring, reduces to Pear2 ZArm son’s x(2) statistic for the 2 # 2 table that compares allele counts between cases and controls when the genotypes are in Hardy-Weinberg proportions (Devlin and Roeder 1999), yet the statistic is robust to departures from ZArm Hardy-Weinberg proportions (Sasieni 1997).”
MethodNutrigenomics research for personalized nutrition and medicine
Kaput, J. (2008) · Current Opinion in Biotechnology · doi:10.1016/j.copbio.2008.02.005 · Cited by 138
Variants in the ATM-BRCA2-CHEK2 axis predispose to chronic lymphocytic leukemia
Rudd, M. F., Sellick, G. S., Webb, E. L., Catovsky, D., & Houlston, R. S. (2006) · Blood · doi:10.1182/blood-2005-12-5022 · Cited by 135
Common Variants in HSPB7 and FRMD4B Associated With Advanced Heart Failure
Cappola, T. P., Li, M., He, J., Ky, B., Gilmore, J. M., Qu, L., Keating, B. J., Reilly, M. P., Kim, C. E., Glessner, J., et al. (2010) · Circulation Cardiovascular Genetics · doi:10.1161/circgenetics.109.898395 · Cited by 135
Williams, F. M. K., Bansal, A. T., van Meurs, J. B. J., Bell, J. T., Meulenbelt, I., Suri, P., Rivadeneira, F., Sambrook, P. N., Albert Hofman, D., Bierma‐Zeinstra, S., et al. (2012) · Annals of the Rheumatic Diseases · doi:10.1136/annrheumdis-2012-201551 · Cited by 136
Genome-wide association study of toxic metals and trace elements reveals novel associations
Ng, E., Lind, P., Lindgren, C. M., Ingelsson, E., Mahajan, A., Morris, A. P., & Lind, L. (2015) · Human Molecular Genetics · doi:10.1093/hmg/ddv190 · Cited by 133
“The genomic control inflation factor (52,53) for eachmetalwas used to assess evidence of residual population structure.”
MethodLuca, D., Ringquist, S., Klei, L., Lee, A. B., Gieger, C., Wichmann, H.-E., Schreiber, S., Krawczak, M., Lu, Y., Styche, A., et al. (2008) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2007.11.003 · Cited by 128
Self-citationZhu, C., & Yu, J. (2009) · Genetics · doi:10.1534/genetics.108.098863 · Cited by 143
“Besides the earlier methods of genomic control (Devlin and Roeder 1999; Devlin et al. 2004) and structured association based on Bayesian clustering (Pritchard et al. 2000; Falush et al. 2003, 2007), principal component analysis (PCA) was recently suggested as a fast and effective way to diagnose…”
MethodHoffmann, T. J., Eeden, S. K. V. D., Sakoda, L. C., Jorgenson, E., Habel, L. A., Graff, R. E., Passarelli, M. N., Cario, C. L., Emami, N. C., Chao, C., et al. (2015) · Cancer Discovery · doi:10.1158/2159-8290.cd-15-0315 · Cited by 132
“The genomic inflation factor (50) was very modest for all GWAS analyses (all ≤1.”
BackgroundIdentification of new susceptibility loci for IgA nephropathy in Han Chinese
Li, M., Foo, J. N., Wang, J. Q., Low, H.-Q., Tang, X.-Q., Toh, K. Y., Yin, P.-R., Khor, C. C., Goh, Y.-F., Irwan, I. D., et al. (2015) · Nature Communications · doi:10.1038/ncomms8270 · Cited by 130
Association mapping, using a mixture model for complex traits
Zhu, X., Zhang, S., Zhao, H., & Cooper, R. (2002) · Genetic Epidemiology · doi:10.1002/gepi.210 · Cited by 132
“In fact, this assumption is the basis of all the methods using genomic markers to control the effect of population stratification [Pritchard et al., 2000a,b; Devlin and Roeder, 1999].”
MethodHuang, J., Ellinghaus, D., Franke, A., Howie, B., & Li, Y. (2012) · European Journal of Human Genetics · doi:10.1038/ejhg.2012.3 · Cited by 134
A Human Type 1 Diabetes Susceptibility Locus Maps to Chromosome 21q22.3
CONCANNON, P. J., Önengüt-Gümüşcü, S., Todd, J. A., Smyth, D. J., Pociot, F., Bergholdt, R., Akolkar, B., Erlich, H. A., Hilner, J. E., Julier, C., et al. (2008) · Diabetes · doi:10.2337/db08-0753 · Cited by 132
“02 obtained when the whole-genome scan results were examined (26).”
BackgroundGhosh, A., Murugesan, G., Chen, K., Zhang, L., Wang, Q. K., Febbraio, M., Anselmo, R. M., Marchant, K., Barnard, J., & Silverstein, R. L. (2011) · Blood · doi:10.1182/blood-2011-02-338582 · Cited by 130
Zhu, X., Li, S., Cooper, R., & Elston, R. C. (2008) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2007.10.009 · Cited by 132
Low, S., Takahashi, A., Cha, P.-C., Zembutsu, H., Kamatani, N., Kubo, M., & Nakamura, Y. (2012) · Human Molecular Genetics · doi:10.1093/hmg/dds020 · Cited by 130
“The P-values obtained from the discovery phase were subsequently corrected using the genomic control method (45), and the corrected P-values were used for further analysis.”
Factors affecting statistical power in the detection of genetic association
Gordon, D. (2005) · Journal of Clinical Investigation · doi:10.1172/jci24756 · Cited by 130
“Genomic control (25, 26) is one tool for dealing with this issue.”
MethodBurkhardt, R., Kenny, E. E., Lowe, J. K., Birkeland, A. C., Josowitz, R., Noel, M., Salit, J., Maller, J., Pe’er, I., Daly, M. J., et al. (2008) · Arteriosclerosis Thrombosis and Vascular Biology · doi:10.1161/atvbaha.108.172288 · Cited by 129
Common variants at 12q15 and 12q24 are associated with infant head circumference
Taal, H. R., Pourcain, B. S., Thiering, E., Das, S., Mook‐Kanamori, D. O., Warrington, N. M., Kaakinen, M., Kreiner‐Møller, E., Bradfield, J. P., Freathy, R. M., et al. (2012) · Nature Genetics · doi:10.1038/ng.2238 · Cited by 129
Orozco, L. D., Bennett, B. J., Farber, C. R., Ghazalpour, A., Pan, C., Che, N., Wen, P.-Z., Qi, H. X., Mutukulu, A., Siemers, N. O., et al. (2012) · Cell · doi:10.1016/j.cell.2012.08.043 · Cited by 131
Genome-wide association studies: assessing trait characteristics in model and crop plants
Alseekh, S., Kostova, D., Bulut, M., & Fernie, A. R. (2021) · Cellular and Molecular Life Sciences · doi:10.1007/s00018-021-03868-w · Cited by 143
“To combat this problem considerable effort has been made to statistically account for population structure [27, 28].”
BackgroundPriorities and standards in pharmacogenetic research
Need, A. C., Motulsky, A. G., & Goldstein, D. B. (2005) · Nature Genetics · doi:10.1038/ng1593 · Cited by 131
“One way to do this is to genotype unlinked genetic markers and look for systematic differences in allele frequency (genomic control”
BackgroundDemographic history mediates the effect of stratification on polygenic scores
Zaidi, A. A., & Mathieson, I. (2020) · eLife · doi:10.7554/elife.61548 · Cited by 122
“Approaches such as genomic control (GC) (Devlin and Roeder, 1999), principal component analysis (PCA) (Price et al.”
BackgroundMethodASsociation of gsk3β polymorphisms with brain structural changes in major depressive disorder
Inkster, B., Nichols, T. E., Saemann, P. G., Auer, D. P., Holsboer, F., Muglia, P., & Matthews, P. M. (2009) · Archives of General Psychiatry · doi:10.1001/archgenpsychiatry.2009.70 · Cited by 127
Rodriguez‐Fontenla, C., Calaza, M., Εvangelou, Ε., Valdes, A. M., Arden, N., Blanco, F. J., Carr, A. J., Chapman, K. E., Deloukas, P., Doherty, M., et al. (2013) · Arthritis & Rheumatology · doi:10.1002/art.38300 · Cited by 127
“The lambda inflation factor was calculated per sex-specific effect size using the genomic control method (37), and the SEs were corrected by the square root of the lambda inflation factor (SEcorrected SEobserved ).”
MethodFu, Y., Hallman, D. M., González, V. H., Klein, R., Klein, R., Hayes, M. G., Cox, N. J., Bell, G. I., & Hanis, C. L. (2010) · Journal of Ophthalmology · doi:10.1155/2010/861291 · Cited by 131
“A genomic inflation factor ( λ ) [31] and mean χ 2 statistics generated from all tested SNPs were also calculated to evaluate the e ff ect of population stratification.”
Noguchi, E., Sakamoto, H., Hirota, T., Ochiai, K., Imoto, Y., Sakashita, M., Kurosaka, F., Akasawa, A., Yoshihara, S., Kanno, N., et al. (2011) · PLoS Genetics · doi:10.1371/journal.pgen.1002170 · Cited by 129
“[37].”
Paşaniuc, B., Zaitlen, N., Lettre, G., Chen, G. K., Tandon, A., Kao, W. H. L., Ruczinski, I., Fornage, M., Siscovick, D. S., Zhu, X., et al. (2011) · PLoS Genetics · doi:10.1371/journal.pgen.1001371 · Cited by 124
“We also assessed all scores at null simulated data (R = 1) using the standard genomic control [26] statistic lGC which attained a value of 1.”
MethodDavies, R. W., Wells, G. A., Stewart, A. F. R., Erdmann, J., Shah, S. H., Ferguson, J. F., Hall, A. S., Anand, S. S., Burnett, M. S., Epstein, S. E., et al. (2012) · Circulation Cardiovascular Genetics · doi:10.1161/circgenetics.111.961243 · Cited by 129
“2) was employed, where the standard error for each cohort was multiplied by the square root of the lambda as estimated by the genotyped SNPs for that inheritance model for that cohort.(17) Only SNPs with data from at least 2 studies and with an I(2) less than 50% were considered.”
Liu, Z., Yang, N., Yan, Y., Li, G., Liu, A., Wu, G., & Sun, C. (2019) · BMC Genetics · doi:10.1186/s12863-019-0771-7 · Cited by 127
“Genomic inflation factor (GIF) was calculated using the “GenABEL” package in the R software to judge the extent of false positive signals [47].”
MethodCoalescent-Based Association Mapping and Fine Mapping of Complex Trait Loci
Zöllner, S. K., & Pritchard, J. K. (2004) · Genetics · doi:10.1534/genetics.104.031799 · Cited by 125
“When population structure is problematic, there are two types of methods that aim to correct for it: Genomic Control (Devlin and Roeder, 1999) and Structured Association (Pritchard et al.”
BackgroundHunninghake, G. M., Weiss, S. T., & Celedon, J. C. (2005) · American Journal of Respiratory and Critical Care Medicine · doi:10.1164/rccm.200508-1232so · Cited by 127
“The latter can be accomplished by using a familybased study design or methods to detect and adjust for population stratification (308, 309).”
MethodMORGAM (an international pooling of cardiovascular cohorts)
Evans, A. (2004) · International Journal of Epidemiology · doi:10.1093/ije/dyh327 · Cited by 126
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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