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June 20, 2026Journal of Microscopy0 citationsOpen Access

Assessing the reproducibility of a bioimage analysis workflow characterising tissue flow in Drosophila

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MAMélodie AmbrosetCVCesar Augusto Valades‐CruzLTLibert Brice Tonfack

Key Points

  • The aim is to assess the reproducibility of a specific bioimage analysis workflow without evaluating biological claims.
  • Assessed the reproducibility of Gehrels et al. (2023) bioimage analysis workflow.
  • Evaluated available data in the BioImage Archive and code on GitHub for completeness.
  • Identified limitations in reporting and repository configuration that affected reproducibility.
  • Materials provided were insufficient for complete replication of the analysis.
  • Repository lacked configuration necessary for straightforward workflow and result replication.
  • Incomplete reporting significantly hindered reproducibility of bioimage analysis workflows.

Abstract

Reproducibility challenges in bioimage analysis are common. The proliferation of tools and workflows creates a complex ecosystem that is difficult to reproduce without deliberate, explicit reporting and support. We assess the reproducibility of Gehrels et al.(2023) as a representative bioimage analysis workflow. We do not evaluate the biological claims; instead, we examine the reproducibility of the bioimage analysis methods used and the implications for current peer-review practices in the field. Although some data were deposited in the BioImage Archive and code was available on GitHub, the materials were insufficient to completely reproduce the analysis. Moreover, the repository lacked the configuration to enable straightforward replication of the workflow or results. This case study highlighted how incomplete reporting can significantly hinder the reproduction of bioimage analysis workflows. Because scientific progress relies on verifiable replications, insufficiently reproducible results can erode confidence in the scientific record.

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Cite This Study

Ambroset et al. (2026) studied this question.

synapsesocial.com/papers/6a3632a0db0793dc1a5392d1https://doi.org/10.1111/jmi.70125
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