ArticleBioinformatics (Oxford, England)2014
Association analysis using next-generation sequence data from publicly available control groups: the robust variance score statistic.
Article in Bioinformatics (Oxford, England), 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.
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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.
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Who cites it
22 citing papers in PubMed.
- Integrating External Controls by Regression Calibration for Genome-Wide Association Study.Genes · 2024Article
- Case-only exome variation analysis of severe alcohol dependence using a multivariate hierarchical gene clustering approach.PloS one · 2023Article
- Integrating external controls in case-control studies improves power for rare-variant tests.Genetic epidemiology · 2022Article
- A data harmonization pipeline to leverage external controls and boost power in GWAS.Human molecular genetics · 2022Article
- Recent advances and challenges of rare variant association analysis in the biobank sequencing era.Frontiers in genetics · 2022Review
- Novel score test to increase power in association test by integrating external controls.Genetic epidemiology · 2021Article
- Analysis in case-control sequencing association studies with different sequencing depths.Biostatistics (Oxford, England) · 2020Article
- VikNGS: a C++ variant integration kit for next generation sequencing association analysis.Bioinformatics (Oxford, England) · 2020Article
- Impact of DNA source on genetic variant detection from human whole-genome sequencing data.Journal of medical genetics · 2019Article
- Association score testing for rare variants and binary traits in family data with shared controls.Briefings in bioinformatics · 2019Article
- Complex-Trait Prediction in the Era of Big Data.Trends in genetics : TIG · 2018Review
- Genome-wide linkage and association study implicates the 10q26 region as a major genetic contributor to primary nonsyndromic vesicoureteric reflux.Scientific reports · 2017Article
- Improving power for rare-variant tests by integrating external controls.Genetic epidemiology · 2017Article
- Exploring the genetic architecture of inflammatory bowel disease by whole-genome sequencing identifies association at ADCY7.Nature genetics · 2017Article
- A microRNA-328 binding site in PAX6 is associated with centrotemporal spikes of rolandic epilepsy.Annals of clinical and translational neurology · 2016Article
- Testing Rare-Variant Association without Calling Genotypes Allows for Systematic Differences in Sequencing between Cases and Controls.PLoS genetics · 2016Article
- Progress in methods for rare variant association.BMC genetics · 2016Article
- Family-based genome scan for age at onset of late-onset Alzheimer's disease in whole exome sequencing data.Genes, brain, and behavior · 2015Article
- Whole exome sequencing in extended families with autism spectrum disorder implicates four candidate genes.Human genetics · 2015Article
- Likelihood-based complex trait association testing for arbitrary depth sequencing data.Bioinformatics (Oxford, England) · 2015Article
Corrections and comments
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Authors and funding
9 authors.
Funding
Abstract
motivationSufficiently powered case-control studies with next-generation sequence (NGS) data remain prohibitively expensive for many investigators. If feasible, a more efficient strategy would be to include publicly available sequenced controls. However, these studies can be confounded by differences in sequencing platform; alignment, single nucleotide polymorphism and variant calling algorithms; read depth; and selection thresholds. Assuming one can match cases and controls on the basis of ethnicity and other potential confounding factors, and one has access to the aligned reads in both groups, we investigate the effect of systematic differences in read depth and selection threshold when comparing allele frequencies between cases and controls. We propose a novel likelihood-based method, the robust variance score (RVS), that substitutes genotype calls by their expected values given observed sequence data.
resultsWe show theoretically that the RVS eliminates read depth bias in the estimation of minor allele frequency. We also demonstrate that, using simulated and real NGS data, the RVS method controls Type I error and has comparable power to the 'gold standard' analysis with the true underlying genotypes for both common and rare variants. AVAILABILITY AND IMPLEMENTATION: An RVS R script and instructions can be found at strug.research.sickkids.ca, and at https://github.com/strug-lab/RVS. CONTACT: lisa.strug@utoronto.ca SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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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.