R-ODAF: Omics data analysis framework for regulatory application

M.C.T. Verheijen, M.J. Meier, J.O. Asensio, T.W. Gant, W.D. Tong, C.L. Yauk, F. Caiment*

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review


Despite the widespread use of transcriptomics technologies in toxicology research, acceptance of the data by regulatory agencies to support the hazard assessment is still limited. Fundamental issues contributing to this are the lack of reproducibility in transcriptomics data analysis arising from variance in the methods used to generate data and differences in the data processing. While research applications are flexible in the way the data are generated and interpreted, this is not the case for regulatory applications where an unambiguous answer, possibly later subject to legal scrutiny, is required. A reference analysis framework would give greater credibility to the data and allow the practitioners to justify their use of an alternative bioinformatic process by referring to a standard. In this publication, we propose a method called omics data analysis framework for regulatory application (R-ODAF), which has been built as a user-friendly pipeline to analyze raw transcriptomics data from microarray and next-generation sequencing. In the R-ODAF, we also propose additional statistical steps to remove the number of false positives obtained from standard data analysis pipelines for RNA-sequencing. We illustrate the added value of R-ODAF, compared to a standard workflow, using a typical toxicogenomics dataset of hepatocytes exposed to paracetamol.
Original languageEnglish
Article number105143
Number of pages10
JournalRegulatory Toxicology and Pharmacology
Publication statusPublished - 1 Jun 2022


  • Transcriptomics
  • RNA-Seq
  • Data analysis
  • Statistics
  • DEGs
  • Statistical analysis
  • GENE


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