Principal components analysis corrects for stratification in genome-wide association studies

By Alkes L Price, Nick Patterson, Robert M. Plenge, Michael E. Weinblatt, Nancy A. Shadick, David Reich. 2006

10,117 citations recorded by the source corpus.

Subfields: Genetics, Computational Biology & Bioinformatics

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In Computational Biology & Bioinformatics

Citations in the corpus

Underspecification Presents Challenges for Credibility in Modern Machine Learning (2020, methodology): “We measured the “British-ness” of an individual by the distance from the coordinate-wise median of the self-reported British individuals, in the 10-dimensional vector space of the top 10 principal components (PCs) of genetic variation Price et al. (2006).”
Multi-population GWA mapping via multi-task regularized regression (2010, methodology): “…problem in the literature, existing methods either completely ignore population structure, or focus on reducing spurious associations that are linked to the population structure rather than to the phenotype (Devlin et al., 2004; Hoggart et al., 2003; Price et al., 2006; Zhu et al., 2002).”
Web-Based, Participant-Driven Studies Yield Novel Genetic Associations for Common Traits (2010, background): “This multilevel model is similar to the model in EIGENSTRAT [50].”
The neuropsychology of consumer behavior and marketing (2018, methodology): “Standard control variables, such as age, sex, the interaction of age and sex, and population stratification principle components created by conducting a genome-wide principal components analysis, are also included in the regressions (Benjamin et al., 2012; Price et al., 2006).”
rMVP: A Memory-efficient, Visualization-enhanced, and Parallel-accelerated Tool for Genome-wide Association Study (2020, neutral): “Principal components (PCs) are widely used to represent sub-populations and to enable the incorporation of population structure into GWAS [5].”
Identification of a urate transporter, ABCG2, with a common functional polymorphism causing gout (2009, methodology): “Individual samples were filtered to ensure genotyping quality, and 734 out of 8,861 samples were removed in data-cleaning steps for sex mismatch, discordance with previously genotyped markers, first-degree relative of an included individual, and genetic outlier based on allele sharing and principal ”
Genome-wide association scan in women with systemic lupus erythematosus identifies susceptibility variants in ITGAM, PXK, KIAA1542 and other loci (2008, methodology): “To account for potential confounding substructure or admixture in these samples, we computed PCAs using all SNP”
An efficient multi-locus mixed model approach for genome-wide association studies in structured populations (2012, neutral): “Several methods have been proposed to deal with this issue, including genomic control 3 , structured association 4 , principal components analysis 5 , and mixed linear models 6 .”