Overview
Norm-ISWSVR normalizes metabolomics tables by combining internal-standard correction with support-vector-regression-based adjustment. Its Python implementation supports matched or unmatched internal-standard settings, cross-validation and hyperparameter search.
What can this tool do?
Common uses
- Norm-ISWSVR normalizes metabolomics tables by combining internal-standard correction with support-vector-regression-based adjustment.
Scientific fit
Primary function
Normalization and batch correction
Other functions
Machine learning and prediction
Analysis types
Targeted metabolomics, Untargeted metabolomics
Data compatibility
Inputs
Feature or peak table, Sample metadata
Outputs
Feature or peak table
Input formats
Abundance CSV and sample CSV with optional standard/run metadata
Output formats
Normalized abundance tables and validation/tuning results
Scope and considerations
Designed for
- Norm-ISWSVR normalizes metabolomics tables by combining internal-standard correction with support-vector-regression-based adjustment.
Not designed for
- Correcting every biological/technical confounding pattern or establishing accurate absolute concentrations solely by normalization.
Important requirements
- Documented Python dependencies, abundance and sample CSV tables, internal-standard information and appropriate QC/run metadata for the selected mode.
Considerations
- Review matched-standard assignments, QC coverage and biological preservation. Injection-order and batch columns are optional in the template but their absence limits corresponding diagnostics and interpretation.
Access and documentation
README states a patent application and strictly prohibits commercial use. No unrestricted open-source grant is claimed.
Evidence and review
Enveda intake rechecked against official repository documentation, package/license metadata and primary publication identity on 2026-10-27. Editorial source review only; no software execution or independent benchmark. See docs/enveda-expansion-review-2026-10-27-batch3.md.
Core publications
Resource papers, direct updates and tool-specific methods. Selection policy.
- Norm ISWSVR: A Data Integration and Normalization Approach for Large-Scale Metabolomics. Analytical Chemistry (2022). doi:10.1021/acs.analchem.1c05502
Related tools
Entry history
Changes to this catalogue entry, not the tool's software release history. Acceptance and editorial review are separate.
- 2026-10-27 · First committed entry
Add 45 source-reviewed Enveda tool entries in third expansion batch
View change · Entry at this revision