ArticleBiometrics2011
Control of population stratification by correlation-selected principal components.
Article in Biometrics, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 3 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
21 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Pooled it
- Genetic regulation of gene expression in the epileptic human hippocampus.Human molecular genetics · 2017Pooled it
- A large-scale genome-wide association and meta-analysis identified four novel susceptibility loci for leprosy.Nature communications · 2016Pooled it
- GWAS-based polygenic risk scoring for predicting cerebral artery dissection in the Chinese population.BMC neurology · 2024Article
- Genome-wide meta-analysis and fine-mapping prioritize potential causal variants and genes related to leprosy.MedComm · 2023Article
- Population stratification correction using Bayesian shrinkage priors for genetic association studies.Annals of human genetics · 2023Article
- Genome-wide superior alleles, haplotypes and candidate genes associated with tolerance on sodic-dispersive soils in wheat (Triticum aestivum L.).TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2022Article
- Polygenic risk prediction based on singular value decomposition with applications to alcohol use disorder.BMC bioinformatics · 2022Article
- Rare Coding Variants Associated with Breast Cancer.Advances in experimental medicine and biology · 2021Article
- Pleiotropy of polygenic factors associated with focal and generalized epilepsy in the general population.PloS one · 2020Article
- Maternal and Offspring Genetic Risk of Type 2 Diabetes and Offspring Birthweight Among African Ancestry Populations.The Journal of clinical endocrinology and metabolism · 2019Article
- Genome-wide gene by lead exposure interaction analysis identifies UNC5D as a candidate gene for neurodevelopment.Environmental health : a global access science source · 2017Article
- Set-Based Tests for the Gene-Environment Interaction in Longitudinal Studies.Journal of the American Statistical Association · 2017Article
- Single- and Bayesian Multi-Marker Genome-Wide Association for Haematological Parameters in Pigs.PloS one · 2016Article
- Further improvements to linear mixed models for genome-wide association studies.Scientific reports · 2014Article
- Rare-variant association analysis: study designs and statistical tests.American journal of human genetics · 2014Review
- Discovery of candidate genes for muscle traits based on GWAS supported by eQTL-analysis.International journal of biological sciences · 2014Article
- Using Mendelian randomisation to infer causality in depression and anxiety research.Depression and anxiety · 2013Review
- Empirical pathway analysis, without permutation.Biostatistics (Oxford, England) · 2013Article
- Correcting for population structure and kinship using the linear mixed model: theory and extensions.PloS one · 2013Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
In genome-wide association studies, population stratification is recognized as producing inflated type I error due to the inflation of test statistics. Principal component-based methods applied to genotypes provide information about population structure, and have been widely used to control for stratification. Here we explore the precise relationship between genotype principal components and inflation of association test statistics, thereby drawing a connection between principal component-based stratification control and the alternative approach of genomic control. Our results provide an inherent justification for the use of principal components, but call into question the popular practice of selecting principal components based on significance of eigenvalues alone. We propose a new approach, called EigenCorr, which selects principal components based on both their eigenvalues and their correlation with the (disease) phenotype. Our approach tends to select fewer principal components for stratification control than does testing of eigenvalues alone, providing substantial computational savings and improvements in power. Analyses of simulated and real data demonstrate the usefulness of the proposed approach.
Indexed as
Identifiers
What Socratic holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.