Easyreporting simplifies the implementation of Reproducible Research layers in R software

PLoS One. 2021 May 10;16(5):e0244122. doi: 10.1371/journal.pone.0244122. eCollection 2021.

Abstract

During last years "irreproducibility" became a general problem in omics data analysis due to the use of sophisticated and poorly described computational procedures. For avoiding misleading results, it is necessary to inspect and reproduce the entire data analysis as a unified product. Reproducible Research (RR) provides general guidelines for public access to the analytic data and related analysis code combined with natural language documentation, allowing third-parties to reproduce the findings. We developed easyreporting, a novel R/Bioconductor package, to facilitate the implementation of an RR layer inside reports/tools. We describe the main functionalities and illustrate the organization of an analysis report using a typical case study concerning the analysis of RNA-seq data. Then, we show how to use easyreporting in other projects to trace R functions automatically. This latter feature helps developers to implement procedures that automatically keep track of the analysis steps. Easyreporting can be useful in supporting the reproducibility of any data analysis project and shows great advantages for the implementation of R packages and GUIs. It turns out to be very helpful in bioinformatics, where the complexity of the analyses makes it extremely difficult to trace all the steps and parameters used in the study.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Reproducibility of Results
  • Software*
  • User-Computer Interface

Grants and funding

The work has been partially supported by the Regione Campania Project ADViSE assigned to Dr. Claudia Angelini. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. There was no additional external funding received for this study.