Skip to Main content Skip to Navigation
Journal articles

Experimenting with reproducibility: a case study of robustness in bioinformatics

Abstract : Reproducibility has been shown to be limited in many scientific fields. This question is a fundamental tenet of scientific activity, but the related issues of reusability of scientific data are poorly documented. Here, we present a case study of our difficulties in reproducing a published bioinformatics method even though code and data were available. First, we tried to re-run the analysis with the code and data provided by the authors. Second, we reimplemented the whole method in a Python package to avoid dependency on a MATLAB license and ease the execution of the code on a high-performance computing cluster. Third, we assessed reusability of our reimplementation and the quality of our documentation, testing how easy it would be to start from our implementation to reproduce the results. In a second section, we propose solutions from this case study and other observations to improve reproducibility and research efficiency at the individual and collective levels.While finalizing our code, we created case-specific documentation and tutorials for the associated Python package StratiPy. Readers are invited to experiment with our reproducibility case study by generating the two confusion matrices (see more in section "Robustness: from MATLAB to Python, language and organization"). Here, we propose two options: a step-by-step process to follow in a Jupyter/IPython notebook or a Docker container ready to be built and run.
Document type :
Journal articles
Complete list of metadatas

Cited literature [46 references]  Display  Hide  Download

https://hal-pasteur.archives-ouvertes.fr/pasteur-02066542
Contributor : Guillaume Dumas <>
Submitted on : Wednesday, March 13, 2019 - 2:50:39 PM
Last modification on : Thursday, June 18, 2020 - 12:32:06 PM
Long-term archiving on: : Friday, June 14, 2019 - 5:11:01 PM

Licence


Distributed under a Creative Commons Attribution 4.0 International License

Identifiers

Citation

Yang-Min Kim, Jean-Baptiste Poline, Guillaume Dumas. Experimenting with reproducibility: a case study of robustness in bioinformatics. GigaScience, BioMed Central, 2018, 7 (7), pp.giy077. ⟨10.1093/gigascience/giy077⟩. ⟨pasteur-02066542⟩

Share

Metrics

Record views

297

Files downloads

881