R-ODAF: Omics data analysis framework for regulatory application

Marcha CT Verheijen, Matthew J. Meier, Juan Ochoteco Asensio, Timothy W. Gant, Weida Tong, Carole L. Yauk, Florian Caiment*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

16 Citations (Scopus)
45 Downloads (Pure)

Abstract

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
JournalRegulatory Toxicology and Pharmacology
Volume131
Early online date3 Mar 2022
DOIs
Publication statusPublished - Jun 2022

Bibliographical note

Funding Information:
This work was funded by the CEFIC LRI C4. TWG is supported under a core grant from the National Institute of Health Research , Health Protection Research Unit, Environmental Exposures and Health held with Imperial College London . CLY acknowledges funding from the Canada Research Chairs Program.

Open Access: This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

Publisher Copyright: © 2022 The Author(s). Published by Elsevier Inc.

Citation: Verheijen, Marcha CT, et al. "R-ODAF: Omics data analysis framework for regulatory application." Regulatory Toxicology and Pharmacology (2022): 105143.

DOI: https://doi.org/10.1016/j.yrtph.2022.105143

Keywords

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

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