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dc.contributor.authorSofer, Tamar
dc.contributor.authorZheng, Xiuwen
dc.contributor.authorLaurie, Cecelia A
dc.contributor.authorGogarten, Stephanie M
dc.contributor.authorBrody, Jennifer A
dc.contributor.authorConomos, Matthew P
dc.contributor.authorBis, Joshua C
dc.contributor.authorThornton, Timothy A
dc.contributor.authorSzpiro, Adam
dc.contributor.authorO'Connell, Jeffrey R
dc.contributor.authorLange, Ethan M
dc.contributor.authorGao, Yan
dc.contributor.authorCupples, L Adrienne
dc.contributor.authorPsaty, Bruce M
dc.contributor.authorRice, Kenneth M
dc.date.accessioned2021-06-15T17:19:15Z
dc.date.available2021-06-15T17:19:15Z
dc.date.issued2021-06-09
dc.identifier.urihttp://hdl.handle.net/10713/16016
dc.description.abstractIn modern Whole Genome Sequencing (WGS) epidemiological studies, participant-level data from multiple studies are often pooled and results are obtained from a single analysis. We consider the impact of differential phenotype variances by study, which we term 'variance stratification'. Unaccounted for, variance stratification can lead to both decreased statistical power, and increased false positives rates, depending on how allele frequencies, sample sizes, and phenotypic variances vary across the studies that are pooled. We develop a procedure to compute variant-specific inflation factors, and show how it can be used for diagnosis of genetic association analyses on pooled individual level data from multiple studies. We describe a WGS-appropriate analysis approach, implemented in freely-available software, which allows study-specific variances and thereby improves performance in practice. We illustrate the variance stratification problem, its solutions, and the proposed diagnostic procedure, in simulations and in data from the Trans-Omics for Precision Medicine Whole Genome Sequencing Program (TOPMed), used in association tests for hemoglobin concentrations and BMI.en_US
dc.description.urihttps://doi.org/10.1038/s41467-021-23655-2en_US
dc.language.isoenen_US
dc.publisherSpringer Natureen_US
dc.relation.ispartofNature Communicationsen_US
dc.subjectgenetic association analysesen_US
dc.subjectphenotypic varianceen_US
dc.subjectpopulation stratificationen_US
dc.subjectvariant-specific inflation factorsen_US
dc.subject.meshWhole Genome Sequencingen_US
dc.titleVariant-specific inflation factors for assessing population stratification at the phenotypic variance levelen_US
dc.typeArticleen_US
dc.identifier.doi10.1038/s41467-021-23655-2
dc.identifier.pmid34108454
dc.source.volume12
dc.source.issue1
dc.source.beginpage3506
dc.source.endpage
dc.source.countryUnited States
dc.source.countryUnited States
dc.source.countryEngland


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