Unique challenges and best practices for single cell transcriptomic analysis in toxicology

• Published in: Current opinion in toxicology 2024-06, Vol.38, p.100475, Article 100475
• Main Authors: Filipovic, David, Kana, Omar, Marri, Daniel, Bhattacharya, Sudin
• Format: Article
• Language: English
• ISSN: 2468-2020; 2468-2020
• DOI: 10.1016/j.cotox.2024.100475

The application and analysis of single-cell transcriptomics in toxicology presents unique challenges. These include identifying cell sub-populations sensitive to perturbation; interpreting dynamic shifts in cell type proportions in response to chemical exposures; and performing differential expression analysis in dose–response studies spanning multiple treatment conditions. This review examines these challenges while presenting best practices for critical single cell analysis tasks. This covers areas such as cell type identification; analysis of differential cell type abundance; differential gene expression; and cellular trajectories. Towards enhancing the use of single-cell transcriptomics in toxicology, this review aims to address key challenges in this field and offer practical analytical solutions. Overall, applying appropriate bioinformatic techniques to single-cell transcriptomic data can yield valuable insights into cellular responses to toxic exposures. •The analysis of single-cell gene expression data in toxicology presents unique challenges.•Chemical exposure can alter cell type proportions and expression of cell type-specific marker genes.•We discuss best practices for analysis of cell type and abundance, differential gene expression, and cellular trajectories.