Overview
NOREVA evaluates normalization using multiple criteria. Version 2 extends the approach to time-course and multi-class study designs.
What can this tool do?
Common uses
- Compare normalization choices before differential analysis.
- Assess the sensitivity of results to preprocessing strategy.
Scientific fit
Primary function
Normalization and batch correction
Data compatibility
Inputs
Feature or peak table, Sample metadata
Outputs
Feature or peak table, Statistical results, Human-readable report
Input formats
Other, Abundance matrices and study-design metadata
Output formats
Other, Normalized matrices and evaluation results
Scope and considerations
Designed for
- Compare normalization choices before differential analysis.
Not designed for
- Selecting a universally optimal normalization solely from class separation.
Important requirements
- A formatted abundance matrix, sample-group information and any reference or QC data required by the chosen evaluation.
Considerations
- Avoid selecting methods using held-out outcome labels; assess biological plausibility and analytical QC alongside evaluation scores.
Access and documentation
Web service and standalone R scripts are described in the official manual; review distribution terms.
Evidence and review
Documentation-based editorial review on 7 September 2026. Scope and limitations summarize the linked official sources; software execution and developer verification were not assessed.
Core publications
Resource papers, direct updates and tool-specific methods. Selection policy.
- Yang Q, Wang Y, Zhang Y, et al. NOREVA: enhanced normalization and evaluation of time-course and multi-class metabolomic data. Nucleic Acids Res 48, W436-W448 (2020). doi:10.1093/nar/gkaa258
Related tools
Entry history
Changes to this catalogue entry, not the tool's software release history. Acceptance and editorial review are separate.
- 2026-09-08 · Entry update
Audit core publications across existing tools
View change · Entry at this revision - 2026-09-07 · First committed entry
Add 50 documented metabolomics resources
View change · Entry at this revision