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A Shiny App to Support Rigor and Reproducibility in Mendelian Randomization Studies

Abstract Number:

2490 

Submission Type:

Contributed Abstract 

Contributed Abstract Type:

Paper 

Participants:

Frederick Boehm (1), Ji Hoon Park (2)

Institutions:

(1) N/A, N/A, (2) South Dakota State University, N/A

Co-Author:

Ji Hoon Park  
South Dakota State University

First Author:

Frederick Boehm  
N/A

Presenting Author:

Frederick Boehm  
N/A

Abstract Text:

We present a Shiny app that supports and facilitates two-sample Mendelian randomization studies with genome-wide association study (GWAS) summary statistics. The proliferation of GWAS and the sharing of their marginal SNP association statistics have enabled researchers to address causal inference questions between two complex traits. Two-sample Mendelian randomization posits a causal relationship between a putative exposure and a putative outcome. Our Shiny app will enable researchers to input GWAS summary statistics for the putative outcome and putative exposure. The app supports diverse sensitivity analyses to assess the assumptions that underlie Mendelian randomization. To ensure computational reproducibility, the user can download a Rmarkdown file with all analysis code from our app. We also briefly discuss anticipated issues with app deployment.

Keywords:

reproducibility|genetics|genome-wide association study|causal inference|software development|

Sponsors:

Section on Statistics in Genomics and Genetics

Tracks:

Miscellaneous

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