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Science Forum: A community-led initiative for training in reproducible research

  1. Susann Auer
  2. Nele A Haeltermann
  3. Tracey L Weissberger
  4. Jeffrey C Erlich
  5. Damar Susilaradeya
  6. Magdalena Julkowska
  7. Małgorzata Anna Gazda
  8. Benjamin Schwessinger  Is a corresponding author
  9. Nafisa M Jadavji  Is a corresponding author
  10. Reproducibility for Everyone Team
  1. Department of Plant Physiology, Institute of Botany, Faculty of Biology, Technische Universität Dresden, Germany
  2. Department of Molecular and Human Genetics, Baylor College of Medicine, United States
  3. QUEST Center, Berlin Institute of Health, Charité Universitätsmedizin Berlin, Germany
  4. Shanghai Key Laboratory of Brain Functional Genomics, East China Normal University, China
  5. Medical Technology Cluster, Indonesian Medical Education and Research Institute, Faculty of Medicine, Universitas Indonesia, Indonesia
  6. Boyce Thompson Institute, United States
  7. CIBO/InBIOO, Centro de Investigação em Biodiversidade e Recursos Genéticos, Campus Agrário de Vairão, Portugal
  8. Departamento de Biologia, Faculdade de Ciências, Universidade do Porto, Portugal
  9. Research School of Biology, Australian National University, Australia
  10. Department of Biomedical Science, Midwestern University, United States
  11. Department of Neuroscience, Carleton University, Canada
  12. Reproducibility for Everyone, United States
Feature Article
Cite this article as: eLife 2021;10:e64719 doi: 10.7554/eLife.64719
2 figures


Factors that affect reproducibility in research.

An approximation of the classification of categories that contribute to irreproducible scientific results, including technical, human, errors in study design and statistical analysis and external. Specific examples have been listed under each category.

Approaches that scientists can use to increase the reproducibility of their publications.

From top to bottom, approaches that can be used on their own or in combination to increase the reproducibility of experiments, ordered from least reproducibility to most. The column on the right includes details of tools and resources than can be used to help scientists take each specific approach.

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