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Realistic and Robust Reproducible Research for Biostatistics
HEJBLUM, Boris
Statistics In System biology and Translational Medicine [SISTM]
Bordeaux population health [BPH]
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Statistics In System biology and Translational Medicine [SISTM]
Bordeaux population health [BPH]
HEJBLUM, Boris
Statistics In System biology and Translational Medicine [SISTM]
Bordeaux population health [BPH]
< Reduce
Statistics In System biology and Translational Medicine [SISTM]
Bordeaux population health [BPH]
Language
EN
Document de travail - Pré-publication
English Abstract
The complexity of analysis pipelines in biomedical sciences poses a severe challenge for the transparency and reproducibility of results. Researchers are increasingly incorporating software development technologies and ...Read more >
The complexity of analysis pipelines in biomedical sciences poses a severe challenge for the transparency and reproducibility of results. Researchers are increasingly incorporating software development technologies and methods into their analyses, but this is a quickly evolving landscape and teams may lack the capabilities to set up their own complex IT infrastructure to aid reproducibility. Basing a reproducible research strategy on readily available solutions with zero or low set-up costs whilst maintaining technological flexibility to incorporate domain-specific software tools is therefore of key importance. We outline a practical approach for robust reproducibility of analysis results. In our examples, we rely exclusively on established open-source tools and free services. Special emphasis is put on the integration of these tools with best practices from software development and free online services for the biostatistics domain.Read less <
English Keywords
Biostatistics
Data management
Reproducibility
Workflow automation