Overview
OmicsPLS implements O2PLS and related sparse approaches, with component selection and visualization for paired high-dimensional datasets.
What can this tool do?
Common uses
- Relate metabolomics to another omics layer measured in the same samples.
- Inspect joint and data-specific patterns.
Scientific fit
Primary function
Multi-omics integration
Data compatibility
Inputs
Feature or peak table, Sample metadata
Outputs
Statistical results, Human-readable report
Input formats
Other, Two matched numeric matrices in R
Output formats
Other, O2PLS models, scores, loadings and plots
Scope and considerations
Designed for
- Relate metabolomics to another omics layer measured in the same samples.
Not designed for
- Establishing causal regulation from shared statistical variation.
Important requirements
- Two numeric datasets with matched samples and appropriate scaling.
Considerations
- Use cross-validation and inspect confounding; sample alignment and preprocessing strongly affect joint components.
Access and documentation
GPL-3 R package.
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.
- Bouhaddani SE, Uh HW, Jongbloed G, et al. Integrating omics datasets with the OmicsPLS package. BMC Bioinformatics 19, 371 (2018). doi:10.1186/s12859-018-2371-3
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