Efficient Control of Population Structure in Model Organism Association Mapping

By Hyun Min Kang, Noah A. Zaitlen, Claire M. Wade, Andrew W. Kirby, David E. Heckerman, Mark J. Daly, Eleazar Eskin. Genetics, 2008

1,796 citations recorded by the source corpus.

Subfields: Genetics, Plant Science

View Paper: https://www.semanticscholar.org/paper/d0d3598f6c8ceda3e0a14cb6228d1489b5212e0f

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Citations in the corpus

Population Structure and Cryptic Relatedness in Genetic Association Studies (2009, methodology): “Kang et al. (2008) have developed the software package EMMA for fast inference in linear MMs using a likelihood ratio test.”
Genome-wide association mapping: a case study in bread wheat (Triticum aestivum L.) (2010, methodology): “The EMMA method (Kang et al. 2008) was chosen and the MLM parameters were left at the default settings from TASSEL.”
Variance component model to account for sample structure in genome-wide association studies (2010, neutral): “Similar variance component approaches have been used successfully in animal model”
A Multiparent Advanced Generation Inter-Cross to Fine-Map Quantitative Traits in Arabidopsis thaliana (2009, background): “The main challenge for association studies at the moment is population sub-structure (due to demographic causes), which requires more sophisticated analyses such as linear mixed models [13,24] to control for false positives.”
A resource-efficient tool for mixed model association analysis of large-scale data (2019, methodology): “Therefore, 𝛽 $%& can be estimated using the generalised least squares approach: where the parameters used to compute 𝑽 are unknown but can be replicated by the estimates from sparse REML under the null that 𝛽 $%& = 0 as in most existing methods 27,29-31, 37 , 39,”
Accuracy and Training Population Design for Genomic Selection on Quantitative Traits in Elite North American Oats (2011, methodology): “Th is method was implemented in the computer soft ware R (R Development Core Team, 2009) using the emma package (Kang et al., 2008) and matrix algebra functions, in which the emma.”
Improving power and accuracy of genome-wide association studies via a multi-locus mixed linear model methodology (2016, neutral): “Kang et al. 3 used a matrix transformation prior to the genome-wide scanning stage and treated the scanned SNP effect as fixed.”
Evaluation of Genomic Prediction Methods for Fusarium Head Blight Resistance in Wheat (2012, methodology): “Th e association analysis stage was conducted using the package emma (Kang et al., 2008) implemented in R (R Development Core Team, 2010) to fi t a mixed eff ects model testing each marker’s association with the trait while correcting for multiple levels of relatedness (Yu et al.”
Marker-Assisted Plant Breeding: Principles and Practices (2015, background): “This kinship matrix is determined from genome-wide markers and corrects for population structure (Kang et al. 2008).”