Learning Lessons on Reproducibility and Replicability in Large Scale Genome-Wide Association Studies

Abstract

Reproducibility and replicability play a pivotal role in science. The article reflects on reproducibility and replicability as they figure in large scale genome-wide association studies. Overall, we emphasize the importance of enhancing data reproducibility, analysis reproducibility, and result replicability. We make recommendations pertaining to the development of study designs that address 1) batch effects and selection bias, 2) the incorporation of discrete discovery and replication phases, and 3) the procurement of a large sample size. We emphasize the importance of systematic and transparent data generation, processing, and quality control pipelines, as well as a rigorous field-specific standardized analysis protocol, We offer guidance with respect to collaborative frameworks, open access analysis tools, and software, and the use of supporting mandates, infrastructure, and repositories for data and resource sharing. Finally, we identify the role of incentives and culture in fueling the production of reproducible and replicable research through partnerships of researchers, funding agencies, and journals.