Genomic reproducibility in the bioinformatics era

TL;DR

This paper emphasizes the importance of genomic reproducibility in bioinformatics, defining it as consistent results across technical replicates, and discusses methods and best practices to improve and evaluate reproducibility in genomics research.

Contribution

It provides a clear definition of genomic reproducibility, analyzes the impact of bioinformatics tools on reproducibility, and proposes best practices for rigorous assessment across replicates.

Findings

Reproducibility is crucial for validating genomic results.

Bioinformatics tools significantly influence reproducibility outcomes.

Rigorous testing across replicates enhances confidence in genomic analyses.

Abstract

In biomedical research, validation of a new scientific discovery is tied to the reproducibility of its experimental results. However, in genomics, the definition and implementation of reproducibility still remain imprecise. Here, we argue that genomic reproducibility, defined as the ability of bioinformatics tools to maintain consistent genomics results across technical replicates, is key to generating scientific knowledge and enabling medical applications. We first discuss different concepts of reproducibility and then focus on reproducibility in the context of genomics, aiming to establish clear definitions of relevant terms. We then focus on the role of bioinformatics tools and their impact on genomic reproducibility and assess methods of evaluating bioinformatics tools in terms of genomic reproducibility. Lastly, we suggest best practices for enhancing genomic reproducibility, with an emphasis on assessing the performance of bioinformatics tools through rigorous testing across multiple technical replicates.