ArticleStatistical applications in genetics and molecular biology2018
A practical approach to adjusting for population stratification in genome-wide association studies: principal components and propensity scores (PCAPS).
Article in Statistical applications in genetics and molecular biology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers, 1 of them a synthesis that pooled it.
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Who cites it
26 citing papers in PubMed, 1 synthesis or guideline pooled it, 51 citations in OpenAlex.
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- GWAS advancements to investigate disease associations and biological mechanisms.Clinical and translational discovery · 2024Article
- Oryza CLIMtools: A genome-environment association resource reveals adaptive roles for heterotrimeric G proteins in the regulation of rice agronomic traits.Plant communications · 2024Article
- A statistical method for image-mediated association studies discovers genes and pathways associated with four brain disorders.American journal of human genetics · 2024Article
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- Oryza CLIMtools: A Genome-Environment Association Resource Reveals Adaptive Roles for Heterotrimeric G Proteins in the Regulation of Rice Agronomic Traits.bioRxiv : the preprint server for biology · 2023Article
- GWAS reveals genomic associations with swine inflammation and necrosis syndrome.Mammalian genome : official journal of the International Mammalian Genome Society · 2023Article
- Population stratification correction using Bayesian shrinkage priors for genetic association studies.Annals of human genetics · 2023Article
- Robust Bioinformatics Approaches Result in the First Polygenic Risk Score for BMI in Greek Adults.Journal of personalized medicine · 2023Article
- Analytical Approaches to Uncover Genetic Associations for Rare Outcomes: Lessons from West Nile Neuroinvasive Disease.Methods in molecular biology (Clifton, N.J.) · 2023Article
- X chromosome-wide association study of quantitative biomarkers from the Alzheimer's Disease Neuroimaging Initiative study.Frontiers in aging neuroscience · 2023Article
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Authors and funding
5 authors at 4 institutions in 1 country.
Funding
Abstract
Genome-wide association studies (GWAS) are susceptible to bias due to population stratification (PS). The most widely used method to correct bias due to PS is principal components (PCs) analysis (PCA), but there is no objective method to guide which PCs to include as covariates. Often, the ten PCs with the highest eigenvalues are included to adjust for PS. This selection is arbitrary, and patterns of local linkage disequilibrium may affect PCA corrections. To address these limitations, we estimate genomic propensity scores based on all statistically significant PCs selected by the Tracy-Widom (TW) statistic. We compare a principal components and propensity scores (PCAPS) approach to PCA and EMMAX using simulated GWAS data under no, moderate, and severe PS. PCAPS reduced spurious genetic associations regardless of the degree of PS, resulting in odds ratio (OR) estimates closer to the true OR. We illustrate our PCAPS method using GWAS data from a study of testicular germ cell tumors. PCAPS provided a more conservative adjustment than PCA. Advantages of the PCAPS approach include reduction of bias compared to PCA, consistent selection of propensity scores to adjust for PS, the potential ability to handle outliers, and ease of implementation using existing software packages.
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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.