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

IF 4.6
David Filipovic , Omar Kana , Daniel Marri , Sudin Bhattacharya
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引用次数: 0

Abstract

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.

毒理学中单细胞转录组分析的独特挑战和最佳实践
单细胞转录组学在毒理学中的应用和分析面临着独特的挑战。这些挑战包括识别对扰动敏感的细胞亚群;解释细胞类型比例对化学暴露反应的动态变化;以及在跨越多种处理条件的剂量反应研究中进行差异表达分析。本综述探讨了这些挑战,同时介绍了关键单细胞分析任务的最佳实践。其中包括细胞类型鉴定、细胞类型丰度差异分析、差异基因表达和细胞轨迹等领域。为了加强单细胞转录组学在毒理学中的应用,本综述旨在解决该领域的关键挑战,并提供实用的分析解决方案。总之,将适当的生物信息学技术应用于单细胞转录组数据,可以获得细胞对毒性暴露反应的宝贵见解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Current opinion in toxicology
Current opinion in toxicology Toxicology, Biochemistry
CiteScore
8.50
自引率
0.00%
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0
审稿时长
64 days
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