Variant-specific inflation factors for assessing population stratification at the phenotypic variance level

NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium

Research output: Contribution to journalArticlepeer-review

Abstract

In 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.

Original languageEnglish (US)
Article number3506
JournalNature communications
Volume12
Issue number1
DOIs
StatePublished - Dec 1 2021

Bibliographical note

Funding Information:
T.S. was supported by National Heart, Lung, and Blood Institute (NHLBI; R01HL120393‐03S1, 1R35HL135818, and 1R21HL145425). The views expressed in this manuscript are those of the authors and do not necessarily represent the views of the National Heart, Lung, and Blood Institute; the National Institutes of Health; or the U.S. Department of Health and Human Services. Study acknowledgements are provided in Supplementary File 1.

Publisher Copyright:
© 2021, The Author(s).

PubMed: MeSH publication types

  • Journal Article
  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

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