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Peer-reviewedCC BY-NC-ND 4.0STAR Protocols

Protocol for automated analysis of oil red O-stained Caenorhabditis elegans using Redwormpix, a Python-based application

  • Thibaud Mabit
  • Constance Dubois
  • Audrey Labarre
  • J. Alex Parker
Open at sourcePDFDOICite

Abstract

Oil red O (ORO) staining is a widely used histological technique for visualizing neutral lipids in Caenorhabditis elegans. However, quantitative image analysis of ORO-stained worms remains largely manual, time-consuming, and prone to human error. Here, we present a protocol for automating the quantification of ORO staining using Redwormpix, an open-source Python-based application. We describe steps for installing software, transferring images, and running the application. We then detail procedures for manual validation and exporting results.

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Cite

BibTeXRIS
BibTeX
@article{mabit2026protocol,
  title = {{Protocol for automated analysis of oil red O-stained Caenorhabditis elegans using Redwormpix, a Python-based application}},
  author = {Thibaud Mabit and Constance Dubois and Audrey Labarre and J. Alex Parker},
  journal = {STAR Protocols},
  year = {2026},
  month = nov,
  doi = {10.1016/j.xpro.2026.104599},
  url = {https://nantes-universite.hal.science/hal-05853705v1},
  note = {CC BY-NC-ND 4.0},
}
RIS
TY  - JOUR
TI  - Protocol for automated analysis of oil red O-stained Caenorhabditis elegans using Redwormpix, a Python-based application
AU  - Thibaud Mabit
AU  - Constance Dubois
AU  - Audrey Labarre
AU  - J. Alex Parker
PY  - 2026
DA  - 2026/11/05
JO  - STAR Protocols
DO  - 10.1016/j.xpro.2026.104599
UR  - https://nantes-universite.hal.science/hal-05853705v1
AB  - Oil red O (ORO) staining is a widely used histological technique for visualizing neutral lipids in Caenorhabditis elegans. However, quantitative image analysis of ORO-stained worms remains largely manual, time-consuming, and prone to human error. Here, we present a protocol for automating the quantification of ORO staining using Redwormpix, an open-source Python-based application. We describe steps for installing software, transferring images, and running the application. We then detail procedures for manual validation and exporting results.
SN  - 2666-1667
ER  -