Advantages and pitfalls in the application of mixed-model association methods
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P. Visscher | A. Price | M. Goddard | Jian Yang | N. Zaitlen | A. Price
[1] D. Falconer. The inheritance of liability to diseases with variable age of onset, with particular reference to diabetes mellitus , 1967, Annals of human genetics.
[2] K. Abromeit. Music Received , 2023, Notes.
[3] C. R. Henderson,et al. Best linear unbiased estimation and prediction under a selection model. , 1975, Biometrics.
[4] K. Roeder,et al. Genomic Control for Association Studies , 1999, Biometrics.
[5] M. Goddard,et al. Prediction of total genetic value using genome-wide dense marker maps. , 2001, Genetics.
[6] D. Reich,et al. Principal components analysis corrects for stratification in genome-wide association studies , 2006, Nature Genetics.
[7] M. McMullen,et al. A unified mixed-model method for association mapping that accounts for multiple levels of relatedness , 2006, Nature Genetics.
[8] Keyan Zhao,et al. An Arabidopsis Example of Association Mapping in Structured Samples , 2006, PLoS genetics.
[9] G. Abecasis,et al. Family-based association tests for genomewide association scans. , 2007, American journal of human genetics.
[10] D. Heckerman,et al. Efficient Control of Population Structure in Model Organism Association Mapping , 2008, Genetics.
[11] Alkes L. Price,et al. New approaches to population stratification in genome-wide association studies , 2010, Nature Reviews Genetics.
[12] Ayellet V. Segrè,et al. Hundreds of variants clustered in genomic loci and biological pathways affect human height , 2010, Nature.
[13] H. Kang,et al. Variance component model to account for sample structure in genome-wide association studies , 2010, Nature Genetics.
[14] P. Visscher,et al. Common SNPs explain a large proportion of heritability for human height , 2011 .
[15] Zhiwu Zhang,et al. Mixed linear model approach adapted for genome-wide association studies , 2010, Nature Genetics.
[16] Daniel Gianola,et al. Predicting genetic predisposition in humans: the promise of whole-genome markers , 2010, Nature Reviews Genetics.
[17] W. G. Hill,et al. Genome partitioning of genetic variation for complex traits using common SNPs , 2011, Nature Genetics.
[18] Simon C. Potter,et al. Genetic risk and a primary role for cell-mediated immune mechanisms in multiple sclerosis , 2011, Nature.
[19] P. Visscher,et al. GCTA: a tool for genome-wide complex trait analysis. , 2011, American journal of human genetics.
[20] Ying Liu,et al. FaST linear mixed models for genome-wide association studies , 2011, Nature Methods.
[21] P. Visscher,et al. Estimating missing heritability for disease from genome-wide association studies. , 2011, American journal of human genetics.
[22] Mark I McCarthy,et al. Genomic inflation factors under polygenic inheritance , 2011, European Journal of Human Genetics.
[23] M. Stephens,et al. Genome-wide Efficient Mixed Model Analysis for Association Studies , 2012, Nature Genetics.
[24] D. Altshuler,et al. Informed Conditioning on Clinical Covariates Increases Power in Case-Control Association Studies , 2012, PLoS genetics.
[25] M. Pirinen,et al. Including known covariates can reduce power to detect genetic effects in case-control studies , 2012, Nature Genetics.
[26] G. McVean,et al. Differential confounding of rare and common variants in spatially structured populations , 2011, Nature Genetics.
[27] Peter Kraft,et al. Analysis of case-control association studies with known risk variants , 2012, Bioinform..
[28] M Erbe,et al. Improving accuracy of genomic predictions within and between dairy cattle breeds with imputed high-density single nucleotide polymorphism panels. , 2012, Journal of dairy science.
[29] Bjarni J. Vilhjálmsson,et al. A mixed-model approach for genome-wide association studies of correlated traits in structured populations , 2012, Nature Genetics.
[30] Tatiana I Axenovich,et al. Rapid variance components–based method for whole-genome association analysis , 2012, Nature Genetics.
[31] J. Mefford,et al. The Covariate's Dilemma , 2012, PLoS genetics.
[32] Bjarni J. Vilhjálmsson,et al. An efficient multi-locus mixed model approach for genome-wide association studies in structured populations , 2012, Nature Genetics.
[33] Peter Kraft,et al. Heritability in the genome-wide association era , 2012, Human Genetics.
[34] David C. Wilson,et al. Host-microbe interactions have shaped the genetic architecture of inflammatory bowel disease , 2012, Nature.
[35] Eleazar Eskin,et al. Improved linear mixed models for genome-wide association studies , 2012, Nature Methods.
[36] D. Clayton,et al. Link Functions in Multi-Locus Genetic Models: Implications for Testing, Prediction, and Interpretation , 2012, Genetic epidemiology.
[37] Xiang Zhou,et al. Polygenic Modeling with Bayesian Sparse Linear Mixed Models , 2012, PLoS genetics.
[38] Eleazar Eskin,et al. Mixed models can correct for population structure for genomic regions under selection , 2013, Nature Reviews Genetics.
[39] Kai Wang,et al. An Analytical Comparison of the Principal Component Method and the Mixed Effects Model for Association Studies in the Presence of Cryptic Relatedness and Population Stratification , 2013, Human Heredity.
[40] David Heckerman,et al. FaST-LMM-Select for addressing confounding from spatial structure and rare variants , 2013, Nature Genetics.
[41] Naomi R. Wray,et al. Estimation and partitioning of polygenic variation captured by common SNPs for Alzheimer's disease, multiple sclerosis and endometriosis , 2012, Human molecular genetics.
[42] David Heckerman,et al. The benefits of selecting phenotype-specific variants for applications of mixed models in genomics , 2013, Scientific Reports.
[43] Alkes L. Price,et al. Response to Sul and Eskin , 2013, Nature Reviews Genetics.