ArticleGenetic epidemiology2012
Stratification-score matching improves correction for confounding by population stratification in case-control association studies.
Article in Genetic epidemiology, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 2 of them syntheses that pooled it.
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Who cites it
14 citing papers in PubMed, 2 syntheses or guidelines pooled it, 21 citations in OpenAlex.
- Multi-Ancestry Genome-Wide Association Study of Spontaneous Clearance of Hepatitis C Virus.Gastroenterology · 2019Pooled it
- Extracorporeal Life Support: The Next Step in Moderate to Severe ARDS-A Review and Meta-Analysis of the Literature.BioMed research international · 2019Pooled it
- Association between MEF2A variants and ischemic stroke risk: a case-control study and two prospective cohort studies in a Chinese population.BMC cardiovascular disorders · 2026Article
- Recommendations for Statistical Reporting in Cardiovascular Medicine: A Special Report From the American Heart Association.Circulation · 2021Review
- PCAmatchR: a flexible R package for optimal case-control matching using weighted principal components.Bioinformatics (Oxford, England) · 2021Article
- Contributions of Rare Gene Variants to Familial and Sporadic FSGS.Journal of the American Society of Nephrology : JASN · 2019Article
- A practical approach to adjusting for population stratification in genome-wide association studies: principal components and propensity scores (PCAPS).Statistical applications in genetics and molecular biology · 2018Article
- Identification of genetic risk factors in the Chinese population implicates a role of immune system in Alzheimer's disease pathogenesis.Proceedings of the National Academy of Sciences of the United States of America · 2018Article
- The relationship between three-dimensional knee MRI bone shape and total knee replacement-a case control study: data from the Osteoarthritis Initiative.Rheumatology (Oxford, England) · 2016Observational
- Novel genetic matching methods for handling population stratification in genome-wide association studies.BMC bioinformatics · 2015Article
- Sparse conditional logistic regression for analyzing large-scale matched data from epidemiological studies: a simple algorithm.BMC bioinformatics · 2015Article
- A genome-wide association study identifies major loci affecting the immune response against infectious bronchitis virus in chicken.Infection, genetics and evolution : journal of molecular epidemiology and evolutionary genetics in infectious diseases · 2014Article
- A fast and noise-resilient approach to detect rare-variant associations with deep sequencing data for complex disorders.Genetic epidemiology · 2012Article
- Families or Unrelated: The Evolving Debate in Genetic Association Studies.Journal of biometrics & biostatistics · 2012Article
Corrections and comments
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Authors and funding
6 authors at 3 institutions in 1 country.
Funding
Abstract
Proper control of confounding due to population stratification is crucial for valid analysis of case-control association studies. Fine matching of cases and controls based on genetic ancestry is an increasingly popular strategy to correct for such confounding, both in genome-wide association studies (GWASs) as well as studies that employ next-generation sequencing, where matching can be used when selecting a subset of participants from a GWAS for rare-variant analysis. Existing matching methods match on measures of genetic ancestry that combine multiple components of ancestry into a scalar quantity. However, we show that including nonconfounding ancestry components in a matching criterion can lead to inaccurate matches, and hence to an improper control of confounding. To resolve this issue, we propose a novel method that assigns cases and controls to matched strata based on the stratification score (Epstein et al. [2007] Am J Hum Genet 80:921-930), which is the probability of disease given genomic variables. Matching on the stratification score leads to more accurate matches because case participants are matched to control participants who have a similar risk of disease given ancestry information. We illustrate our matching method using the African-American arm of the GAIN GWAS of schizophrenia. In this study, we observe that confounding due to stratification can be resolved by our matching approach but not by other existing matching procedures. We also use simulated data to show our novel matching approach can provide a more appropriate correction for population stratification than existing matching approaches.
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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.