Applying the omics data analysis framework for regulatory application (R-ODAF) filtering criteria: A case study with...

The omics data analysis framework for regulatory application (R-ODAF) is a proposed reference framework designed to promote the use of toxicogenomic data for chemical risk assessments. Despite its potential impact on stakeholders, studies examining its characteristics have been limited. The objective of this paper is to gain insight into the applicability of the R-ODAF by applying its filtering criteria to RNA-Seq data at hand. Here, the R-ODAF filtering criteria were applied to gene expression analysis of human lymphoblastoid TK6 cells exposed to the carcinogen 3-methylcholanthrene (3-MCA). All samples passed the processing criteria, and the false discovery rate (FDR) filter discarded the most genes among the filters designed for differentially expressed genes (DEGs). The information entropy of the transcriptome was measured to assess whether a change with biological significance occurred in TK6 cells exposed to 3-MCA. The results of pathway and literature analyses for DEGs discarded by the FDR filter suggest that these genes support the interpretation of the effects of 3-MCA on gene expression in TK6 cells. Finally, we discuss the potential limitations of basing gene selection on the R-ODAF.