Comprehensive Guide for Epigenetics and Transcriptomics Data Quality Control

• Published in: STAR protocols 2025-01, Vol.6 (1), p.103607, Article 103607
• Main Authors: Comendul, Arianna, Ruf-zamojski, Frederique, Ford, Colby T., Agarwal, Pankaj, Zaslavsky, Elena, Nudelman, German, Hariharan, Manoj, Rubenstein, Aliza, Pincas, Hanna, Nair, Venugopalan D., Michaleas, Adam M., Fremont-Smith, Philip D., Ricke, Darrell O., Sealfon, Stuart C., Woods, Christopher W., Claypool, Kajal T., Jaimes, Rafael
• Format: Article
• Language: English
• ISSN: 2666-1667; 2666-1667
• DOI: 10.1016/j.xpro.2025.103607

Host response to environmental exposures such as pathogens and chemicals can include modifications to the epigenome and transcriptome. Improved signature discovery, including the identification of the agent and timing of exposure, has been enabled by advancements in assaying techniques to detect RNA expression, DNA base modifications, histone modifications, and chromatin accessibility. The interrogation of the epigenome and transcriptome cascade requires analyzing disparate datasets from multiple assay types, often at single cell resolution, derived from the same biospecimen. However, there remains a paucity of rigorous quality control standards of those datasets that reflect quality assurance of the underlying assay. This guide outlines a comprehensive suite of metrics that can be used to ensure quality from 11 different epigenetics and transcriptomics assays. Recommended mitigative actions to address failed metrics are provided. The workflow presented aims to improve benchwork protocols and dataset quality to enable accurate discovery of exposure signatures. [Display omitted] •Bench protocols reviewed for epigenetic & transcriptomic assays•Quality metrics are defined for 11 different epigenetics and transcriptomics assays•Recommendations on mitigation approaches to address poor and failed metrics