Realistic and Robust Reproducible Research for Biostatistics
| dc.rights.license | open | en_US |
| hal.structure.identifier | Statistics In System biology and Translational Medicine [SISTM] | |
| hal.structure.identifier | Bordeaux population health [BPH] | |
| dc.contributor.author | HEJBLUM, Boris
ORCID: 0000-0003-0646-452X IDREF: 189970316 | |
| dc.contributor.author | KUNZMANN, Kevin | |
| dc.contributor.author | LAVAGNINI, Ennio | |
| dc.contributor.author | HUTCHINSON, Anna | |
| dc.contributor.author | ROBERTSON, David | |
| dc.contributor.author | JONES, Sacha | |
| dc.contributor.author | ECKES-SHEPHARD, Annemarie | |
| dc.date.accessioned | 2021-05-07T09:53:52Z | |
| dc.date.available | 2021-05-07T09:53:52Z | |
| dc.date.created | 2020 | |
| dc.identifier.uri | https://oskar-bordeaux.fr/handle/20.500.12278/27200 | |
| dc.description.abstractEn | 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. | |
| dc.language.iso | EN | en_US |
| dc.subject.en | Biostatistics | |
| dc.subject.en | Data management | |
| dc.subject.en | Reproducibility | |
| dc.subject.en | Workflow automation | |
| dc.title.en | Realistic and Robust Reproducible Research for Biostatistics | |
| dc.type | Document de travail - Pré-publication | en_US |
| dc.identifier.doi | 10.20944/preprints202006.0002.v1 | en_US |
| dc.subject.hal | Statistiques [stat]/Applications [stat.AP] | en_US |
| dc.subject.hal | Statistiques [stat]/Méthodologie [stat.ME] | en_US |
| bordeaux.hal.laboratories | Bordeaux Population Health Research Center (BPH) - UMR 1219 | en_US |
| bordeaux.institution | Université de Bordeaux | en_US |
| bordeaux.institution | INSERM | en_US |
| bordeaux.team | SISTM_BPH | |
| bordeaux.import.source | hal | |
| hal.identifier | hal-03100421 | |
| hal.version | 1 | |
| hal.export | false | |
| workflow.import.source | hal | |
| bordeaux.COinS | ctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.au=HEJBLUM,%20Boris&KUNZMANN,%20Kevin&LAVAGNINI,%20Ennio&HUTCHINSON,%20Anna&ROBERTSON,%20David&rft.genre=preprint |
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