ArticleBMC proceedings2011
Effect of population stratification analysis on false-positive rates for common and rare variants.
Article in BMC proceedings, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT00930280 (Genetic and Environmental Risk Factors for Hemorrhagic Stroke), which is not on this map. Cited by 11 papers.
What it found
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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.
Genetic and Environmental Risk Factors for Hemorrhagic Stroke
Who cites it
11 citing papers in PubMed.
- Whole-exome sequencing to analyze population structure, parental inbreeding, and familial linkage.Proceedings of the National Academy of Sciences of the United States of America · 2016Trial
- Deviation from baseline mutation burden provides powerful and robust rare-variants association test for complex diseases.Nucleic acids research · 2022Article
- Fast and efficient correction for population stratification in multi-locus genome-wide association studies.Genetica · 2021Article
- PAMAM: Power analysis in multiancestry admixture mapping.Genetic epidemiology · 2019Article
- The role of rare variants in systolic blood pressure: analysis of ExomeChip data in HyperGEN African Americans.Human heredity · 2015Article
- In search of low-frequency and rare variants affecting complex traits.Human molecular genetics · 2013Review
- On association analysis of rare variants under population substructure: an approach for the detection of subjects that can cause bias in the analysis--T opt: an outlier detection method.Genetic epidemiology · 2013Article
- Low frequency variants, collapsed based on biological knowledge, uncover complexity of population stratification in 1000 genomes project data.PLoS genetics · 2013Article
- Investigation of genetic risk factors for chronic adult diseases for association with preterm birth.Human genetics · 2013Article
- Using BioBin to explore rare variant population stratification.Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing · 2013Article
- Identification of genetic association of multiple rare variants using collapsing methods.Genetic epidemiology · 2011Article
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
Principal components analysis (PCA) has been successfully used to correct for population stratification in genome-wide association studies of common variants. However, rare variants also have a role in common disease etiology. Whether PCA successfully controls population stratification for rare variants has not been addressed. Thus we evaluate the effect of population stratification analysis on false-positive rates for common and rare variants at the single-nucleotide polymorphism (SNP) and gene level. We use the simulation data from Genetic Analysis Workshop 17 and compare false-positive rates with and without PCA at the SNP and gene level. We found that SNPs' minor allele frequency (MAF) influenced the ability of PCA to effectively control false discovery. Specifically, PCA reduced false-positive rates more effectively in common SNPs (MAF > 0.05) than in rare SNPs (MAF < 0.01). Furthermore, at the gene level, although false-positive rates were reduced, power to detect true associations was also reduced using PCA. Taken together, these results suggest that sequence-level data should be interpreted with caution, because extremely rare SNPs may exhibit sporadic association that is not controlled using PCA.
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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 OpenQuestion graph.