Examining the role of unmeasured confounding in mediation analysis with genetic and genomic applications

BMC Bioinformatics

Software

Debashis Ghosh¹  Annie Thwing¹  Sarah Schmiege¹  Miranda Kroehl¹  Sharon M. Lutz¹  John E. Hokanson²  Anne P. Starling²  Christopher D. Baker³ 

[1] Department of Biostatistics and Informatics, University of Colorado Anschutz Medical Campus, 13001 E. 17th Place, B119 Bldg. 500 W3128, 80045, Aurora, CO, USA;Department of Epidemiology, University of Colorado Anschutz Medical Campus, Aurora, CO, USA;Department of Pediatrics and Pulmonary Medicine, Children’s Hospital Colorado, Aurora, CO, USA;

关键词: Mediation analysis;    Mediated effects;    Direct effects;    Unmeasured confounding;    Population stratification;   

DOI  :  10.1186/s12859-017-1749-y

 received in 2017-04-03, accepted in 2017-07-04,  发布年份 2017

来源: Springer

【 摘 要 】

BackgroundIn mediation analysis if unmeasured confounding is present, the estimates for the direct and mediated effects may be over or under estimated. Most methods for the sensitivity analysis of unmeasured confounding in mediation have focused on the mediator-outcome relationship.ResultsThe Umediation R package enables the user to simulate unmeasured confounding of the exposure-mediator, exposure-outcome, and mediator-outcome relationships in order to see how the results of the mediation analysis would change in the presence of unmeasured confounding. We apply the Umediation package to the Genetic Epidemiology of Chronic Obstructive Pulmonary Disease (COPDGene) study to examine the role of unmeasured confounding due to population stratification on the effect of a single nucleotide polymorphism (SNP) in the CHRNA5/3/B4 locus on pulmonary function decline as mediated by cigarette smoking.ConclusionsUmediation is a flexible R package that examines the role of unmeasured confounding in mediation analysis allowing for normally distributed or Bernoulli distributed exposures, outcomes, mediators, measured confounders, and unmeasured confounders. Umediation also accommodates multiple measured confounders, multiple unmeasured confounders, and allows for a mediator-exposure interaction on the outcome. Umediation is available as an R package at https://github.com/SharonLutz/Umediation A tutorial on how to install and use the Umediation package is available in the Additional file 1.

【 授权许可】

CC BY   
© The Author(s). 2017