Metabolomics Navigator Tools, strategies & workflow guidance for metabolomics

Metabolite annotation and identification

SIRIUS

A cross-platform small-molecule MS/MS framework for LC-MS preprocessing, molecular-formula annotation, spectral-library searching, structure-database searching, compound-class prediction, confidence scoring, and de novo structure generation.

LC-MSDirect-infusion MSUntargeted metabolomicsMetabolite profilingDesktop graphical interface
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Documented workflows

Published software workflows and their original methodological context. Check current software documentation for version-specific changes.

Molecular-formula annotation with SIRIUS and ZODIAC

SIRIUS uses isotope patterns and fragmentation trees to score molecular-formula candidates. ZODIAC adds dataset-level re-ranking by exploiting shared fragments and neutral losses between fragmentation trees, using Bayesian inference and Gibbs sampling to improve formula assignments across related spectra.

  1. Import centroided spectra or LC-MS runs

    Import preprocessed .ms/.mgf/.msp-style spectra or centroided mzML/mzXML runs. SIRIUS 6 can create a project space and perform its built-in LC-MS feature detection/alignment for mzML/mzXML inputs.

  2. Generate formula candidates with SIRIUS

    Use accurate precursor mass, isotope-pattern evidence, and fragmentation trees to score candidate molecular formulas and annotate fragment formulas.

  3. Apply ZODIAC when dataset-level re-ranking is useful

    Use ZODIAC to jointly re-rank formula candidates across a collection of spectra based on shared fragmentation-tree fragments and losses.

  4. Review formula confidence and ambiguity

    Inspect top formula candidates, scores, adduct assumptions, isotope/fragmentation support, and alternative candidates before downstream structural annotation.

Requirements

  • Accurate precursor mass and preferably informative MS/MS; isotope-pattern quality improves formula annotation.

Considerations

  • Molecular-formula annotation is an intermediate step, not complete structural identification.
  • ZODIAC is most useful when processing collections of compounds/spectra because its re-ranking uses relationships across fragmentation trees.

Ludwig M, Nothias L-F, Dührkop K, et al. Database-independent molecular formula annotation using Gibbs sampling through ZODIAC. Nature Machine Intelligence 2, 629–641 (2020).

Read the source method

Overview

SIRIUS is a Java-based small-molecule MS/MS framework integrating local and webservice-backed analysis. Current SIRIUS 6 can import centroided mzML/mzXML runs, perform feature detection/alignment with lcms-align, search spectral libraries by identity or analog similarity, annotate molecular formulas with fragmentation trees and isotope patterns, re-rank formulas with ZODIAC, search structure databases through CSI:FingerID/COSMIC, predict compound classes with CANOPUS, and generate de novo candidates with MSNovelist. GUI, CLI, and API-oriented project-space workflows share a common analysis environment.

What can this tool do?

Chromatogram buildingCompound-class predictionIdentification-confidence assessmentSpectral-library matchingMolecular-formula predictionMS/MS processingPeak or feature detectionRetention-time alignmentStructure-database searchingStructure elucidationSubstructure prediction

Common uses

  • Import centroided LC-MS mzML/mzXML files and perform feature detection/alignment into a SIRIUS project space.
  • Annotate molecular formulas using isotope patterns, fragmentation trees, and optional ZODIAC dataset-level re-ranking.
  • Perform identity and analog spectral-library searching, including custom spectral/structure databases.
  • Search molecular-structure databases with CSI:FingerID/COSMIC, predict compound classes with CANOPUS, and generate de novo candidates with MSNovelist.
  • Export formula, structure and class results while retaining feature identifiers for linking back to the abundance table.

Scientific fit

Primary function

Metabolite annotation and identification

Other functions

Machine learning and prediction, Preprocessing and feature extraction, Reference data and database search, Spectral processing and comparison

Analysis types

Untargeted metabolomics, Metabolite profiling

MS level

MS1, MS/MS

Acquisition

Data-dependent acquisition (DDA), Targeted MS/MS, General or unspecified acquisition

Ion mobility

Ion mobility not required

Data compatibility

Inputs

Mass spectra, Feature or peak table

Outputs

Compound list or annotations, Molecular structures, Human-readable report

Input formats

mzML, MGF, MSP, mzXML

Output formats

CSV or TSV, JSON

Scope and considerations

Designed for

  • Molecular-formula and structure-candidate annotation from accurate-mass MS/MS data, including compound-class prediction when exact structures remain uncertain.

Not designed for

  • Peptides, polymers, or stereochemical elucidation; SIRIUS is designed primarily for accurate-mass small molecules, usually below about 1000 Da.

Important requirements

  • High-mass-accuracy MS and preferably informative MS/MS data; the current documentation recommends mass deviations within about 20 ppm.
  • A SIRIUS account/license and internet connection are required for webservice-backed features such as CSI:FingerID, CANOPUS, and MSNovelist; these remain free for academic use under current terms.

Considerations

  • Formula, library, class, and structure results represent computational evidence and should be combined with orthogonal evidence and appropriate metabolite-identification confidence levels.
  • SIRIUS contains both local open-source analysis and proprietary/webservice-backed functions, so access requirements differ among workflow components.
  • DIA spectra require prior deconvolution; the documented default workflow expects centroided, high-accuracy spectra with little chimeric signal.

Education

Learn this tool

External tutorials and workshops collected by Navigator. Entries marked Needs review have not been checked end to end.

NTMSS2023 Day3 S4 - Sirius+CSI:FingerID IFunctional Metabolomics Lab · Video Workshop · Needs reviewNTMSS2026 Day2 S2 - Kai Duehrkopp - SIRIUS part1Functional Metabolomics Lab · Video Workshop · Needs reviewNTMSS2026 Day2 S3 - Kai Duehrkopp - SIRIUS part2Functional Metabolomics Lab · Video Workshop · Needs review

Browse all education resources →

Access and documentation

Primary accessHomepageSource repository

Local features and webservice-backed features have different access and licensing conditions. The official documentation should be checked for the current academic and commercial terms.

From tool to strategy

Strategies using SIRIUS

MS2DECIDENatural-product discovery · Chemistry–MethodsTarget-decoy-controlled DIA metabolomicsMetabolite annotation · Nature Communications

Evidence and review

Documentation-based editorial pass on 6 September 2026: scope, interpretation limits and practical use reviewed against the linked official documentation and cited literature. Software execution, service availability and developer verification were not assessed.

Core publications

Resource papers, direct updates and tool-specific methods. Selection policy.

  1. Dührkop K, Fleischauer M, Ludwig M, et al. SIRIUS 4: a rapid tool for turning tandem mass spectra into metabolite structure information. Nat Methods 16, 299-302 (2019). doi:10.1038/s41592-019-0344-8

Related tools

CANOPUSContains or hosts · CANOPUS provides compound-class prediction within SIRIUS.CSI:FingerIDContains or hosts · CSI:FingerID provides molecular-fingerprint prediction and structure-database searching within SIRIUS.MSNovelistContains or hosts · MSNovelist provides de novo structure generation within SIRIUS.MZmineIntegrates with · A modular mass-spectrometry environment for raw-data import, feature detection/alignment, multimodal LC/IMS/GC/MSI processing, molecular networking, annotation, lipid analysis, visualization, normalization, statistics, and downstream exports.BUDDY / msbuddyComplementary to · Generate and rank molecular formula annotations for small-molecule mass-spectrometry queries.LC-MS2StructIntegrates with · Jointly rank molecular candidates using LC retention order and precomputed MS/MS scores.MS2DECIDEIntegrates with · Combine GNPS, ISDB-LOTUS and SIRIUS annotations into scores for natural-product feature prioritization.

Entry history

Changes to this catalogue entry, not the tool's software release history. Acceptance and editorial review are separate.

  1. 2026-09-08 · Entry update

    Audit core publications across existing tools

    View change · Entry at this revision
  2. 2026-09-07 · Entry update

    Expand and document 31 metabolomics tools and resources

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  3. 2026-08-24 · Entry update

    Complete GNPS SIRIUS and MZmine tool ecosystems

    View change · Entry at this revision
  4. 2026-08-24 · Entry update

    Add GNPS, SIRIUS, and MZmine content batch

    View change · Entry at this revision
  5. 2026-08-21 · Entry update

    Add files via upload

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  6. 2026-08-20 · First committed entry

    Add files via upload

    View change · Entry at this revision

Full GitHub history