Overview
ISFrag recognizes candidate in-source fragments in LC-MS data by combining feature relationships and available MS/MS evidence. Its R workflow accepts XCMS-derived features or a custom peak table and supports multiple levels of fragment annotation.
What can this tool do?
Common uses
- ISFrag recognizes candidate in-source fragments in LC-MS data by combining feature relationships and available MS/MS evidence.
Scientific fit
Primary function
Quality control and filtering
Other functions
Metabolite annotation and identification, Preprocessing and feature extraction
Analysis types
Untargeted metabolomics
Data compatibility
Inputs
Feature or peak table, Mass spectra
Outputs
Feature or peak table, Compound list or annotations
Input formats
mzXML LC-MS files or CSV peak tables with m/z, RT and intensities
Output formats
Annotated feature tables and in-source-fragment relationship plots
Scope and considerations
Designed for
- ISFrag recognizes candidate in-source fragments in LC-MS data by combining feature relationships and available MS/MS evidence.
Not designed for
- Confirming a metabolite structure from a coeluting feature relationship alone or automatically deleting all proposed fragments.
Important requirements
- R and documented XCMS dependencies, mzXML files or correctly ordered CSV peak tables; retention times must use seconds and MS/MS evidence must match the selected workflow.
Considerations
- Adduct/isotope processing through CAMERA belongs to the XCMS route. Distinguish evidence levels and retain ambiguous coeluting alternatives.
Access and documentation
MIT source distribution. External datasets, dependent packages and any hosted routes retain their own terms; software operation was not tested.
License: MIT
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.
- ISFrag: De Novo Recognition of In-Source Fragments for Liquid Chromatography–Mass Spectrometry Data. Analytical Chemistry (2021). doi:10.1021/acs.analchem.1c01644
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