Related Experiment Video
Updated: May 30, 2025
07:30
Optimization for Sequencing and Analysis of Degraded FFPE-RNA Samples
Published on: June 8, 2020
11.9K
Comprehensive guide for epigenetics and transcriptomics data quality control
Arianna Comendul1, Frederique Ruf-Zamojski2, Colby T Ford3
1Lincoln Laboratory, Massachusetts Institute of Technology, Lexington, MA, USA.
STAR Protocols
|January 27, 2025
Summary
This guide provides quality control metrics for epigenetics and transcriptomics assays. Implementing these standards improves data quality for discovering environmental exposure signatures.
Area of Science:
- Environmental health
- Genomics
- Molecular biology
Background:
- Host responses to environmental exposures (pathogens, chemicals) involve epigenome and transcriptome modifications.
- Advances in assaying techniques enable discovery of exposure signatures, including agent and timing.
- Analyzing multi-assay, single-cell data from biospecimens is complex.
Purpose of the Study:
- To establish rigorous quality control (QC) standards for epigenetics and transcriptomics assays.
- To provide a comprehensive suite of QC metrics for 11 different assay types.
- To improve benchwork protocols and dataset quality for accurate exposure signature discovery.
Main Methods:
- Development of a comprehensive suite of quality control metrics.
- Identification of quality assurance standards for underlying assays.
- Provision of recommended mitigative actions for failed QC metrics.
Main Results:
- A guide outlining QC metrics for 11 epigenetics and transcriptomics assays.
- Mitigative actions to address failed metrics.
- A workflow to enhance dataset quality.
Conclusions:
- Standardized QC metrics are crucial for reliable epigenetics and transcriptomics data.
- Improved data quality enables accurate identification of environmental exposure signatures.
- This guide supports robust research in environmental health and molecular biology.
