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Florian Caiment
University of Maastricht

OpenTox Virtual Conference 2023

Omics Data Analysis Framework

Despite 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 is 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 there is flexibility in research applications 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 referencing to a standard. In this project, 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 data from microarray and next-generation sequencing  transcriptomics. 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-Seq.