Overview
RAMClustR groups features using retention and abundance relationships. Its workflow supports feature filtering, QC normalization and spectral export for subsequent annotation.
What can this tool do?
Common uses
- Reduce redundant features into compound-related clusters.
- Export reconstructed spectra for library matching.
Scientific fit
Primary function
Preprocessing and feature extraction
Data compatibility
Inputs
Feature or peak table, Sample metadata
Outputs
Mass spectra, Feature or peak table
Input formats
CSV or TSV
Output formats
MSP
Scope and considerations
Designed for
- Reduce redundant features into compound-related clusters.
Not designed for
- Treating every cluster as a pure, independently identified metabolite.
Important requirements
- A feature table with m/z, retention time and sample information, or supported XCMS objects.
Considerations
- Correlated coeluting compounds can merge; review clustering thresholds and reconstructed spectra.
Access and documentation
Source and environment specifications are public; review repository license terms before redistribution.
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.
- Broeckling CD, Afsar FA, Neumann S, et al. RAMClust: a novel feature clustering method enables spectral-matching-based annotation for metabolomics data. Anal Chem 86, 6812-6817 (2014). doi:10.1021/ac501530d
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