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Preprocessing and feature extraction

xcms

An open-source Bioconductor package for chromatographic mass spectrometry data preprocessing, feature detection, alignment, grouping, and visualization.

LC-MSGC-MSUntargeted metabolomicsMetabolite profilingR package
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Overview

xcms is a scriptable Bioconductor framework for processing chromatographically separated mass-spectrometry data in R. It provides algorithms for chromatographic peak detection, retention-time correction, correspondence/grouping across samples, filling missing feature intensities, and inspection of LC-MS and GC-MS datasets within reproducible analysis scripts.

Also known as: XCMS

What can this tool do?

Chromatogram buildingPeak or feature detectionRetention-time alignmentGap fillingSpectral deconvolution

Common uses

  • Build scriptable preprocessing workflows for untargeted chromatographic MS data.
  • Detect chromatographic peaks and align retention times across samples.
  • Export a feature-intensity table with sample metadata for downstream statistics after checking peak quality.

Scientific fit

Primary function

Preprocessing and feature extraction

Other functions

Quality control and filtering, Normalization and batch correction, Visualization and reporting

Analysis types

Untargeted metabolomics, Metabolite profiling

MS level

MS1, MS/MS

Acquisition

Full-scan MS, Data-dependent acquisition (DDA), General or unspecified acquisition

Ion mobility

Not specified

Data compatibility

Inputs

Raw instrument data, Mass spectra, Sample metadata

Outputs

Feature or peak table, Statistical results

Input formats

mzML, mzXML, netCDF or CDF

Output formats

CSV or TSV

Scope and considerations

Designed for

  • Reproducible, script-based preprocessing of LC-MS and GC-MS datasets in the R/Bioconductor ecosystem.

Not designed for

  • Standalone confirmation of compound structures from chromatographic features.

Important requirements

  • R and Bioconductor plus the package dependencies appropriate to the selected xcms release.

Considerations

  • The package is code oriented rather than a standalone point-and-click workflow, so users benefit from basic R familiarity.
  • Inspect representative chromatograms and alignment diagnostics; gap filling integrates signal in an expected region and does not guarantee a true detected metabolite.

Education

Learn this tool

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

Bioconductor untargeted LC-MS preprocessing with XCMSBioconductor / CSAMA · TutorialLC/MS data analysis with XCMS and MetFrag on PhenoMeNalEMBL's European Bioinformatics Institute EMBL-EBI · Video · Needs reviewXCMS tutorials and workshopsJohannes Rainer and Philippine Louail / Bioconductor · Tutorial

Browse all education resources →

Access and documentation

Primary accessSource repositoryDocumentation

The software license applies to the code; separately acquired libraries, vendor readers and hosted services may have their own terms.

License: Artistic-2.0

From tool to strategy

Strategies using xcms

Feature-Based Molecular Networking (FBMN)Molecular-family discovery · Nature MethodsQC-based robust LOESS signal-drift correctionAnalytical quality control · Nature ProtocolsReference-pool discovery with cohort-wide signal extractionPhenotype association · Analytical ChemistryShared-substructure discovery with Mass2MotifsMetabolite annotation · Proceedings of the National Academy of Sciences

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. Smith CA, Want EJ, O'Maille G, et al. XCMS: processing mass spectrometry data for metabolite profiling using nonlinear peak alignment, matching, and identification. Anal Chem 78, 779-787 (2006). doi:10.1021/ac051437y

Related tools

MZmineAlternative to · 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.OpenMSAlternative to · An open-source C++ library, command-line toolkit, and Python interface for reproducible mass spectrometry data processing in metabolomics and proteomics.asariComplementary to · Process high-resolution mass-spectrometry data into aligned feature tables.CAMERAComplementary to · Group and annotate related LC-MS signals after XCMS peak detection.IPOComplementary to · Optimize peak picking, retention-time correction and grouping parameters for XCMS.msconvertComplementary to · Convert mass-spectrometry files into open formats for downstream analysis.Workflow4MetabolomicsComplementary to · Create and share metabolomics processing and analysis workflows in a Galaxy environment.ParamounterIntegrates with · Estimate LC-MS processing parameters from measured data for downstream feature extraction.
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SIMPELIntegrates with · Extract and correct isotopologue distributions from isotope-enriched metabolomics feature lists.

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

    View change · Entry at this revision
  3. 2026-08-24 · Entry update

    Apply v5.2 pre-population hardening

    View change · Entry at this revision
  4. 2026-08-21 · Entry update

    Add files via upload

    View change · Entry at this revision
  5. 2026-08-20 · First committed entry

    Add files via upload

    View change · Entry at this revision

Full GitHub history