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A generic Transcriptomics Reporting Framework (TRF) for 'omics data processing and analysis.

Timothy W Gant1, Ursula G Sauer2, Shu-Dong Zhang3

  • 1Centre for Radiation, Chemical and Environmental Hazards (CRCE), Public Health England (PHE), Harwell Campus, Oxfordshire, UK.

Regulatory Toxicology and Pharmacology : RTP
|November 9, 2017
PubMed
Summary
This summary is machine-generated.

A new Transcriptomics Reporting Framework (TRF) ensures transparency in omics studies for regulatory use. This framework details reporting parameters from data generation to gene expression analysis, enhancing data reliability.

Keywords:
BioinformaticsDifferentially expressed genesGene expressionNormalisation of ‘omics dataRegulatory toxicologyReproducibilityStatistical analysis

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Area of Science:

  • Transcriptomics
  • Regulatory Science
  • 'omics studies

Background:

  • Omics studies, particularly transcriptomics, are increasingly used in regulatory contexts.
  • Lack of standardized reporting hinders reproducibility and regulatory acceptance of omics data.
  • Existing frameworks may not cover the full scope from data generation to interpretation.

Purpose of the Study:

  • To present a generic Transcriptomics Reporting Framework (TRF) for omics studies in regulatory settings.
  • To define essential reporting parameters for transcriptome profiling and differentially expressed gene (DEG) analysis.
  • To introduce a Reference Baseline Analysis (RBA) for standardized data processing and comparison.

Main Methods:

  • The TRF outlines parameters for reporting, not specific methodologies.
  • The RBA provides a simple, standardized methodology for data processing and analysis.
  • The framework's applicability is demonstrated through a case study using common software tools.

Main Results:

  • The TRF ensures transparency in omics data processing and analysis steps.
  • The RBA serves as a comparative benchmark for evaluating different data processing approaches.
  • The TRF is applicable to all types of regulatory omics studies, including sequencing data.

Conclusions:

  • The TRF enhances confidence in the processing and regulatory application of omics data.
  • The framework's general applicability and simplicity facilitate widespread adoption.
  • Standardized reporting through TRF and RBA supports robust regulatory decision-making.