Isotope tracing and flux analysis
13C-SpaceM analysis code
Analyze spatial carbon-13 labeling of fatty acids in single cells and tissue imaging experiments.
Includes: Isotopologue correction
TOOLS & RESOURCES
Browse software, databases, spectral libraries, repositories, web services and workflow platforms used across mass-spectrometry-based metabolomics.
Isotope tracing and flux analysis
Analyze spatial carbon-13 labeling of fatty acids in single cells and tissue imaging experiments.
Includes: Isotopologue correction
Visualization and reporting
Web-based software for interactive visualization of molecular distributions on 2D images and 3D surfaces.
Includes: Interactive dashboard
Isotope tracing and flux analysis
An R package for reading, annotating, scoring, and visualizing isotopic mass spectra in stable-isotope-probing workflows for metabolites and peptides.
Includes: In-silico spectrum prediction · Spectral data reading and writing
Data conversion and import
AirdPro converts mass-spectrometry vendor data into the Aird storage format through a graphical batch-conversion workflow.
Includes: Spectral data reading and writing
Reference data and database search
ALISTER provides literature-based information about pre-analytical metabolite and lipid stability in EDTA plasma and serum.
Includes: Metadata-based contextualization
Statistical analysis
An R package for quantitative and qualitative meta-analysis of metabolomics studies when only significance, effect-size, identifier, or direction information is available.
Includes: Univariate statistics
Data conversion and import
arcMS converts Waters UNIFI MS-E and HDMS-E data into tabular Parquet or HDF5 storage for analysis in R or Python.
Includes: Spectral data reading and writing
Preprocessing and feature extraction
Process high-resolution mass-spectrometry data into aligned feature tables.
Includes: Peak or feature detection · Retention-time alignment
Preprocessing and feature extraction
An open-source Python tool for calculating and calibrating experimental collision cross sections from ion-mobility mass-spectrometry data across drift-tube and traveling-wave workflows.
Includes: Spectral data reading and writing
Data acquisition and instrument control
Automate ion-mobility metabolomic fingerprinting on a configured RapidFire system.
Includes: Peak or feature detection
Data acquisition and instrument control
BAGO is an open-source bioinformatics tool designed for the systematic optimization of LC gradient using the Bayesian optimization framework. It is particularly useful for optimizing LC gradients in LC-MS-based metabolomics, lipidomics, and exposomics.
Metabolite annotation and identification
BAM generates and ranks structural candidates for suspect metabolites by applying biotransformation rules to known anchor structures.
Includes: Structure elucidation
Pathway and biological interpretation
LIPID MAPS web tool for exploring changes in mammalian lipid pathways and predicting relative reaction or enzyme activity from quantitative lipidomics data.
Includes: Pathway enrichment · Network visualization
Spectral processing and comparison
A Python package for efficient cosine-based similarity scoring and matching of large collections of fragmentation mass spectra, including analog-search workflows.
Includes: Spectral-library matching · MS/MS processing
Preprocessing and feature extraction
breathXplorer processes high-resolution breath mass-spectrometry data with feature extraction, alignment and breath-recognition functions.
Includes: Peak or feature detection · Retention-time alignment · MS/MS processing
Metabolite annotation and identification
Generate and rank molecular formula annotations for small-molecule mass-spectrometry queries.
Includes: Molecular-formula prediction
Preprocessing and feature extraction
Group and annotate related LC-MS signals after XCMS peak detection.
Includes: Adduct and isotope grouping
Metabolite annotation and identification
A SIRIUS-integrated machine-learning method and webservice for predicting compound classes directly from high-resolution MS/MS data without requiring an exact database structure match.
Includes: Compound-class prediction · Substructure prediction
Statistical analysis
Open-source R/Bioconductor toolbox for preprocessing, statistical analysis, segmentation, classification and visualization of mass spectrometry imaging data.
Includes: Multivariate statistics
Preprocessing and feature extraction
CCSfind builds experimentally derived small-molecule databases from LC-drift-tube-ion-mobility-MS data.
Includes: Adduct and isotope grouping
Metabolite annotation and identification
Predict tandem mass spectra, annotate fragments and rank candidate structures for small molecules.
Includes: In-silico spectrum prediction · Structure-database searching
Reference data and database search
Look up curated chemical entities, names and ontology relationships.
Includes: Structure-database searching
Statistical analysis
Prioritize putative transformations between molecular-network features using abundance changes across ordered samples.
Includes: Interactive dashboard
Metabolite annotation and identification
Rank candidate molecular structures by propagating spectral-library annotation evidence through molecular networks using random walks.
Includes: In-silico spectrum prediction
Visualization and reporting
Visualize CMMC enrichment results alongside feature abundances, metadata and molecular-network information.
Includes: Metadata-based contextualization · Interactive dashboard · Network visualization
Metabolite annotation and identification
A community-curated knowledgebase for microbial metabolites that links reference MS/MS evidence, microbial producers, annotations, and GNPS2 analysis resources.
Includes: Spectral-library matching · Metadata-based contextualization · Provenance tracking
Reference data and database search
Search an aggregated, curated collection of natural-product structures and source records.
Includes: Structure-database searching
Molecular networking and chemical similarity
ConCISE propagates consensus chemical-class annotations by combining molecular-network relationships, library matches and in-silico class predictions.
Includes: Compound-class prediction
Reference data and database search
Search public LC-MS/MS evidence for potential conjugated forms of a molecule supplied as a SMILES structure.
Includes: Repository-scale spectral search · Interactive dashboard
Normalization and batch correction
An R package implementing concordance-based batch-effect correction for large-scale metabolomics studies.
Includes: Batch-effect correction
Multi-omics integration
Explore associations between paired metabolomics and other omics feature tables and export correlation networks.
Includes: Interactive dashboard
Machine learning and prediction
CRISP analyzes GC×GC-TOFMS contour images with modules for region selection/deep stacking, synthetic contour generation, image enhancement and classifier training.
Includes: Feature selection
Metabolite annotation and identification
A SIRIUS-integrated machine-learning method and webservice for predicting molecular fingerprints from MS/MS data and ranking candidate structures from molecular-structure databases.
Includes: Structure-database searching · Substructure prediction · Structure elucidation
Visualization and reporting
Desktop network visualization and analysis for exploring MS molecular networks alongside feature annotations and sample metadata.
Includes: Network visualization · Interactive dashboard
Quality control and filtering
Compare statistical batch-correction models and inspect technical variation in metabolomics matrices.
Includes: Batch-effect correction
Machine learning and prediction
DeepGCN-RT predicts small-molecule retention times from molecular graphs.
Includes: Retention-time prediction
Machine learning and prediction
DeepION learns compact representations of MSI ion images for finding co-localized ions or candidate isotope relationships.
Includes: Multivariate statistics
Preprocessing and feature extraction
Align retention times across large LC-MS sample collections.
Includes: Retention-time alignment
Preprocessing and feature extraction
An open-source Python and command-line toolkit for high-dimensional mass-spectrometry processing, including feature detection and alignment, CCS calibration, isotope detection, and MS/MS spectral deconvolution.
Includes: Peak or feature detection · Retention-time alignment · Spectral deconvolution · MS/MS processing
Metabolite annotation and identification
DiffMS generates candidate molecular structures conditioned on mass-spectral information using a diffusion model.
Includes: Structure elucidation
Spectral processing and comparison
A transformer-based framework for learning molecular representations from tandem mass spectra, supporting spectral similarity, clustering, molecular networking, and downstream prediction tasks.
Includes: Spectral-library matching · MS/MS processing
Preprocessing and feature extraction
Match corresponding features across untargeted LC-MS datasets.
Includes: Retention-time alignment
Preprocessing and feature extraction
Detect, align and gap-fill LC-MS features, with a GNPS2 workflow connecting raw LC-MS/MS data to feature-based molecular networking.
Includes: Peak or feature detection · Retention-time alignment · Gap filling
Isotope tracing and flux analysis
Estimate fatty-acid synthesis, import, elongation and desaturation from carbon-13 isotopologue profiles.
Includes: Metabolic-flux estimation
Reference data and database search
Accelerated indexed infrastructure for searching very large collections of tandem mass spectra, enabling current GNPS2 repository-scale search services to return results at billion-spectrum scale.
Includes: Repository-scale spectral search · Spectral-library matching
Spectral processing and comparison
Search electron-ionization spectra against a large predicted reference library.
Includes: Spectral-library matching
Statistical analysis
Clean and statistically explore feature-based molecular networking abundance tables with guided notebooks and a web app.
Includes: Blank and contaminant filtering · Batch-effect correction · Univariate statistics · Multivariate statistics · +1 more
Metabolite annotation and identification
FIDDLE predicts and rescores molecular-formula candidates from tandem mass spectra using deep learning.
Includes: Molecular-formula prediction
Pathway and biological interpretation
Prioritize core metabolite nodes from a perturbed metabolic network.
Includes: Feature selection
Reference data and database search
Explore food constituents, chemical properties and reported dietary sources.
Includes: Structure-database searching
Reference data and database search
A domain-specific GNPS search resource for identifying foods and beverages whose reference metabolomics data contain spectra matching a query MS/MS spectrum.
Includes: Repository-scale spectral search · Metadata-based contextualization · Spectral-library matching
Spectral processing and comparison
Standardize and combine reference mass-spectral libraries.
Includes: Identifier harmonization · Spectral data reading and writing
Preprocessing and feature extraction
An open-source graph-based method for aligning untargeted LC-MS features across runs by solving the correspondence problem as a multidimensional assignment task.
Includes: Retention-time alignment
Preprocessing and feature extraction
Resolve overlapping GC-MS peaks into component spectra and profiles.
Includes: Spectral deconvolution
Statistical analysis
An R package for targeted and untargeted metabolomics feature-table processing, QC-aware analysis, and advanced statistical modeling including regression and mixed-effects models.
Includes: Univariate statistics · Multivariate statistics
Metabolite annotation and identification
Predict chromatographic retention times from molecular structures.
Includes: Retention-time prediction
Molecular networking and chemical similarity
A web-based mass-spectrometry ecosystem for molecular networking, spectral-library search, repository-scale search, interactive visualization, knowledgebase curation, and public-data integration.
Includes: Interactive dashboard · Spectral-library matching · Metadata-based contextualization · Network visualization · +2 more
Visualization and reporting
A browser-based interactive viewer for raw and public mass-spectrometry data, chromatograms, spectra, quantitative traces, and GNPS-associated datasets without requiring local analysis software.
Includes: Interactive dashboard · Chromatogram building · Provenance tracking
Molecular networking and chemical similarity
GNPS2 workflow for organizing MS/MS spectra into molecular families using pairwise spectral similarity and spectral-library searching.
Includes: Spectral-library matching · Network visualization
Visualization and reporting
Convert a GNPS2 GraphML network into a styled desktop Cytoscape session in the browser.
Includes: Network visualization
Visualization and reporting
Annotate GNPS2 feature-based networking results with drug and drug-metabolite context for exposure-oriented interpretation.
Includes: Metadata-based contextualization · Interactive dashboard
Molecular networking and chemical similarity
Dedicated GNPS2 workflow that combines an aligned LC-MS feature table with MS/MS spectra to build quantitative molecular networks.
Includes: Spectral-library matching · Network visualization
Visualization and reporting
Annotate molecular features with dietary and food-ontology context to explore potential food-derived exposures.
Includes: Metadata-based contextualization · Interactive dashboard
Spectral processing and comparison
Hosted interface for exploring MS/MS spectral libraries with MassQL and using LLM assistance to draft or explain queries.
Includes: MS/MS processing
Spectral processing and comparison
Explore recurring fragment peaks and neutral losses across selected tandem mass spectra.
Includes: Interactive dashboard
Visualization and reporting
Attach custom feature attributes to an existing GNPS2 molecular network using matching node identifiers.
Includes: Network visualization
Reference data and database search
Search public MS/MS data using spectrum identifiers and explore matched samples by their biological metadata.
Includes: Metadata-based contextualization
Data management and sharing
Prepare spectrum references from GNPS2 jobs, public dataset identifiers and MassIVE file paths.
Includes: Interactive dashboard
Data management and sharing
Lipid shorthand grammars and parser implementations for validating and normalizing names in MS lipidomics workflows.
Includes: Identifier harmonization
Visualization and reporting
Graph exploration and correlation-network analysis for processed MS metabolomics tables and existing networks.
Includes: Network visualization · Interactive dashboard
Reference data and database search
Find chemical, biological and spectral reference information for human metabolites.
Includes: Structure-database searching
Normalization and batch correction
An R package for hierarchical normalization of multi-batch metabolomics studies using intra-batch and inter-batch replicate information to estimate and remove unwanted variation.
Includes: Batch-effect correction · QC-based drift correction
Metabolite annotation and identification
ICEBERG is a two-stage neural network that predicts mass spectra from molecular structures. It can rank candidate structures against a spectrum for metabolite annotation.
Includes: Structure elucidation
Reference data and database search
Web-based MALDI-TOF mass spectrometry platform and community knowledgebase for bacterial identification, culture-collection analysis, and comparison of specialized-metabolite profiles.
Includes: Metadata-based contextualization · Interactive dashboard · Network visualization
Machine learning and prediction
IDSL_MINT provides transformer-based workflows connecting tandem mass spectra and molecular representations.
Includes: Substructure prediction · Structure elucidation · In-silico spectrum prediction
Statistical analysis
An R package and Shiny application for simulating and imputing missing values across omics datasets, including metabolomics, with multiple imputation algorithms and evaluation utilities.
Includes: Multivariate statistics · Interactive dashboard
Quality control and filtering
A web service for designing LC-MS and GC-MS multi-omics injection sequences with QC placement, inter-batch balancing, intra-batch randomization, and downloadable worksheets.
Includes: Metadata-based contextualization
Quality control and filtering
IonToolPack groups graphical mass-spectrometry utilities for raw-data visualization, PeakQC quality assessment, tandem-library matching, targeted MS1 extraction and feature-list comparison.
Includes: Interactive dashboard · Spectral-library matching · Multivariate statistics
Preprocessing and feature extraction
Optimize peak picking, retention-time correction and grouping parameters for XCMS.
Includes: Peak or feature detection · Retention-time alignment
Quality control and filtering
ISFrag recognizes candidate in-source fragments in LC-MS data by combining feature relationships and available MS/MS evidence.
Includes: Adduct and isotope grouping
Isotope tracing and flux analysis
An R package for identifying biologically relevant 12C/13C feature pairs in stable-isotope-tracing metabolomics, including differential analysis and redundant-feature merging.
Includes: Adduct and isotope grouping · Univariate statistics
Isotope tracing and flux analysis
Integrate stable-isotope-labeling peaks from GC chemical-ionization mass spectrometry data.
Includes: Peak or feature detection
Preprocessing and feature extraction
JPA combines MS1 chromatographic peak picking with MS/MS-precursor-based feature extraction to broaden LC-MS feature detection.
Includes: Peak or feature detection · Retention-time alignment
Metabolite annotation and identification
Group LC-MS isotope and adduct features into empirical compounds and infer neutral masses.
Includes: Adduct and isotope grouping
Metabolite annotation and identification
Jointly rank molecular candidates using LC retention order and precomputed MS/MS scores.
Includes: Structure elucidation
Visualization and reporting
lcmsWorld is an interactive three-dimensional viewer for LC-MS data.
Includes: Interactive dashboard
Pathway and biological interpretation
Web-based lipid ontology enrichment tool that connects lipid lists or rankings to chemical, biophysical, cellular and functional lipid properties.
Includes: Pathway enrichment
Reference data and database search
Find lipid structures, classifications, nomenclature guidance and lipidomics analysis resources.
Includes: Structure-database searching
Pathway and biological interpretation
Group lipid names into ontology terms and test enrichment using a locally run Shiny interface.
Includes: Pathway enrichment · Network visualization
Metabolite annotation and identification
LipidA-IDER annotates lipid A structures from high-resolution tandem mass spectra using lipid A-specific fragmentation interpretation.
Includes: Structure elucidation · MS/MS processing
Reference data and database search
Use an in-silico tandem mass-spectral library to support lipid annotation.
Includes: Spectral-library matching
Data acquisition and instrument control
Design targeted lipidomics assays and predicted fragment libraries for PRM and MRM experiments.
Includes: In-silico spectrum prediction
Metabolite annotation and identification
A deep-learning framework for identifying molecular lipid species from tandem mass spectra.
Includes: Structure elucidation · Compound-class prediction
Metabolite annotation and identification
A standalone LC-MS lipidomics suite for in-silico library generation, MS/MS and MSn spectral searching, lipid feature annotation, peak-table integration, and automated identification quality control.
Includes: In-silico spectrum prediction · Spectral-library matching · Identification-confidence assessment · MS/MS processing
Preprocessing and feature extraction
Filter LC-MS lipid features and obtain putative database annotations.
Includes: Blank and contaminant filtering · Structure-database searching
Data management and sharing
Convert, cross-match and link lipid names across supported nomenclatures before downstream MS lipidomics interpretation.
Includes: Identifier harmonization
Metabolite annotation and identification
Determine lipid carbon–carbon double-bond positions using diagnostic ozone-induced dissociation data.
Includes: Structure elucidation
Quantification and targeted analysis
LipidQMap visualizes and quantifies lipid mass-spectrometry images using user-defined internal standards.
Includes: Isotopologue correction · Interactive dashboard
Statistical analysis
Analyze lipid abundance tables and test patterns across lipid classes and structural properties.
Includes: Univariate statistics · Multivariate statistics · Pathway enrichment
Statistical analysis
Explore lipid abundance tables through statistical analysis, lipid characteristics, enrichment and network visualizations.
Includes: Univariate statistics · Multivariate statistics · Pathway enrichment · Network visualization
Statistical analysis
Analyze lipid abundance changes and lipid characteristics in R.
Includes: Univariate statistics · Multivariate statistics · Pathway enrichment
Statistical analysis
LipidSpace compares lipidomes using graph-based distances between lipid structures and quantitative information.
Includes: Multivariate statistics · Network visualization
Reference data and database search
Connect natural-product structures, organism occurrences and literature references.
Includes: Structure-database searching
Metabolite annotation and identification
LPPtiger 2 supports epilipidomics by predicting modified lipid candidates and their fragmentation patterns, preparing acquisition inclusion lists and annotating modified lipids in LC-MS experiments.
Includes: In-silico spectrum prediction · Structure elucidation
Quality control and filtering
Normalize metabolomics feature intensities using selected features and corrected signal responses.
Includes: Feature selection
Statistical analysis
Integrate multiple LC-MS assays using multiblock statistical models.
Includes: Multivariate statistics · Feature selection · Network visualization
Metabolite annotation and identification
mass2adduct analyzes pairwise mass differences to investigate possible adducts in MSI data.
Includes: Adduct and isotope grouping
Metabolite annotation and identification
Mass2SMILES uses deep learning to predict candidate molecular structures and functional groups from tandem mass spectra.
Includes: Structure elucidation · Substructure prediction
Reference data and database search
Find and download open reference mass spectra with compound and acquisition metadata.
Includes: Spectral-library matching · Provenance tracking
Preprocessing and feature extraction
An integrated Python package for LC-MS data processing with nontargeted peak detection and segmentation, feature quality evaluation, feature-group annotation, and MS/MS library or analog searching.
Includes: Chromatogram building · Peak or feature detection · Gap filling · Adduct and isotope grouping · +2 more
Spectral processing and comparison
A research implementation of a graph-transformer model for predicting small-molecule tandem mass spectra from molecular structures.
Includes: In-silico spectrum prediction
Metabolite annotation and identification
MASSISTANT provides research code for learning molecular SELFIES representations from electron-ionization mass spectra.
Includes: Structure elucidation
Data management and sharing
A public repository for depositing, preserving, browsing, downloading, and reusing mass-spectrometry datasets, including datasets connected to GNPS analyses.
Includes: Repository-scale spectral search · Provenance tracking
Machine learning and prediction
Learn spectral features and classify tissue regions in mass-spectrometry images.
Includes: Feature selection
Spectral processing and comparison
An open-source, instrument-independent query language and software ecosystem for searching mass-spectrometry data using reusable MS1, MS/MS, chromatographic, and ion-mobility patterns.
Includes: Repository-scale spectral search · MS/MS processing · Provenance tracking
Spectral processing and comparison
Browser-based MassQL query editor and runner for exploring fragmentation patterns in local mass-spectrometry files.
Includes: MS/MS processing
Spectral processing and comparison
MassQLab applies named MassQL queries across a directory of mass-spectrometry data and summarizes results as tables and figures.
Includes: MS/MS processing
Reference data and database search
A GNPS repository-scale spectral search service for finding where a query MS/MS spectrum or related spectra occur across public metabolomics data and spectral libraries.
Includes: Spectral-library matching · Metadata-based contextualization · Repository-scale spectral search
Spectral processing and comparison
Build Python workflows for spectral cleaning, metadata harmonization and MS/MS similarity scoring.
Includes: Spectral-library matching · MS/MS processing
Quality control and filtering
Explore sample and feature quality in metabolomics matrices through interactive visualizations.
Includes: Interactive dashboard
Workflow management and reproducibility
A reproducible metabolome-annotation workflow combining spectral-database dereplication and compound-database annotation from tandem mass-spectrometry data.
Includes: Spectral-library matching · Structure-database searching · Provenance tracking
Data management and sharing
MB-POST is a metabolomics mass spectrometry data repository which implements a reanalysis-oriented metadata framework that captures the information essential for data reuse. It provides a streamlined submission system that enables the rapid deposition of standardized metabolomics metadata together with experimental data.
Pathway and biological interpretation
Test functional enrichment in lists of annotated metabolites.
Includes: Pathway enrichment
Spectral processing and comparison
A workflow for extracting and merging LC-MS/MS spectra into local GNPS-style spectral libraries with user metadata, plus local and public-library searching for annotation.
Includes: Reference-spectrum selection · Spectral-library matching · Spectral data reading and writing
Data management and sharing
MESSES extracts tagged experimental metadata from spreadsheets or CSV into JSON, validates structured metadata against schemas and converts supported records to mwTab for Metabolomics Workbench deposition.
Includes: Metadata-based contextualization · Provenance tracking
Preprocessing and feature extraction
Process LC-ion-mobility-MS data across supported four-dimensional acquisition modes.
Includes: Peak or feature detection · MS/MS processing
Statistical analysis
A web platform and associated R package for metabolomics data processing, statistical analysis, visualization, functional interpretation, and multi-omics integration.
Includes: Univariate statistics · Multivariate statistics · Feature selection · Pathway enrichment · +1 more
Statistical analysis
Run metabolomics processing, statistics and functional interpretation through R.
Includes: Univariate statistics · Multivariate statistics
Metabolite annotation and identification
MetaboAnnotate is an AI-powered system for metabolite annotation of MS/MS data. Agents (Supervisor, Planner, Executor, Evaluator) orchestrate workflows and call external tools. The goal of MetabAnnotate is to streamline complex annotation workflows in metabolomics using a modular AI-agent framework.
Metabolite annotation and identification
Match metabolomics features and spectra against reference values through a unified R interface.
Includes: Spectral-library matching · Structure-database searching
Metabolite annotation and identification
An R package for annotating LC-MS all-ion-fragmentation metabolomics features using fragment-ion databases and centroided chromatographic data.
Includes: Spectral-library matching · MS/MS processing
Workflow management and reproducibility
A modular collection of browser-based downstream analysis applications that extend GNPS2 results with targeted interpretation, statistics, metadata, and domain-specific readouts.
Includes: Interactive dashboard · Provenance tracking
Statistical analysis
Perform differential metabolomics analysis and explore metabolic correlation modules in R.
Includes: Univariate statistics · Multivariate statistics
Pathway and biological interpretation
MetaboGraph is a Framework for Metabolomics and Lipidomics Annotation and Pathway Network Analysis that provides end-to-end workflow for metabolite identification, pathway enrichment, net analysis, and multi-omics integration. Designed for both beginner and advanced users, MetaboGraph combines powerful computational methods with an intuitive graphical interface.
Data management and sharing
Deposit and find metabolomics studies with experimental files and structured sample and assay metadata.
Includes: Metadata-based contextualization · Provenance tracking
Reference data and database search
Discover publicly released metabolomics studies across participating repositories.
Includes: Metadata-based contextualization
Data management and sharing
Deposit, discover and retrieve metabolomics studies through the National Metabolomics Data Repository.
Includes: Repository-scale spectral search · Metadata-based contextualization · Provenance tracking
Workflow management and reproducibility
An open educational and reproducible workflow resource for script-based untargeted LC-MS/MS metabolomics using R and Bioconductor packages across preprocessing, QC, statistics, and annotation.
Includes: Provenance tracking · Chromatogram building · Peak or feature detection · Retention-time alignment · +2 more
Quality control and filtering
An R package for importing processed metabolomics data, applying standardized sample and feature quality-control filters, and generating summary tables and HTML reports.
Includes: Feature selection
Statistical analysis
Explore mass-spectrometry metabolomics tables through an R/Shiny interface.
Includes: Univariate statistics · Multivariate statistics
Multi-omics integration
Explore relationships between genes and metabolites in combined metabolic and signaling networks.
Includes: Network visualization
Quality control and filtering
MetaPro is a locally deployed web application for targeted LC-MS analysis, batch inspection and spectral-library curation.
Includes: Spectral-library matching · Interactive dashboard
Reference data and database search
Annotate imaging mass-spectrometry datasets and explore community-contributed spatial metabolomes.
Includes: Metadata-based contextualization · Interactive dashboard
Metabolite annotation and identification
A metabolite-annotation platform using knowledge-driven and data-driven two-layer networking with recursive annotation propagation for untargeted metabolomics.
Includes: Structure-database searching · Identification-confidence assessment
Statistical analysis
MeTEor explores longitudinal metabolomics tables with repeated-measures statistical models, dimensionality reduction, prediction models and interactive plots.
Includes: Univariate statistics · Multivariate statistics · Interactive dashboard
Pathway and biological interpretation
MetExplore is an open-access web server that provides interactive tools for metabolic network analysis and visualization. The platform offers: A collection of curated genome-scale metabolic networks for multiple organisms, together with the possibility to import custom metabolic networks from SBML files. A metabolite identification module that maps experimental metabolites onto metabolic networks using ChEBI identifiers. Pathway overrepresentation analysis to identify significantly enriched m...
Metabolite annotation and identification
Rank candidate molecular structures by comparing predicted fragments with an experimental MS/MS spectrum.
Includes: Structure-database searching · In-silico spectrum prediction
Molecular networking and chemical similarity
Local desktop generation and exploration of MS/MS similarity networks and two-dimensional spectral projections.
Includes: Network visualization
Metabolite annotation and identification
Annotate LC-MS features using accurate mass, retention time and tandem mass spectra in R.
Includes: Spectral-library matching · Structure-database searching
Reference data and database search
MetLinkR is an R package used for cross-linking of metabolite identifiers across disparate data sets. It uses RefMet and RaMP-DB links to recognize metabolites referred to by different names or database identifiers. MetLinkR can be used as an R package or accessed through the RaMP-DB web interface.
Pathway and biological interpretation
Cytoscape app for interpreting identified metabolites and expression data in metabolic and correlation networks.
Includes: Network visualization
Reference data and database search
Curated biosynthetic gene-cluster and product references for interpreting MS-based natural-product and metabologenomics results.
Includes: Metadata-based contextualization
Reference data and database search
A taxonomically informed GNPS search service that connects query MS/MS spectra to matching spectra from curated bacterial, fungal, and archaeal monoculture datasets.
Includes: Repository-scale spectral search · Metadata-based contextualization · Spectral-library matching
Reference data and database search
A GNPS-associated metadata-network search resource for mapping query metabolites and MS/MS spectra across microbiome metabolomics studies, sample contexts, hosts, and microbial metadata.
Includes: Repository-scale spectral search · Metadata-based contextualization · Network visualization
Metabolite annotation and identification
Predict molecular fingerprints from tandem mass spectra and retrieve candidate structures.
Includes: Structure-database searching · Substructure prediction
Metabolite annotation and identification
A machine-learning tool for ranking molecular formula and adduct assignments directly from MS/MS spectra using a transformer-based model without requiring spectral-library matching.
Includes: Molecular-formula prediction
Multi-omics integration
mixOmics is an R package with tools for integrating multi-omic datasets, such as proteomics, metabolomics, metagenomics, microbiome, lipidomics, and more. It can assist in data visualization and advanced multivariate techniques for integration of varied omics studies.
Quality control and filtering
Assess and correct lipid collision-cross-section bias using labeled internal standards.
Includes: Univariate statistics
Data conversion and import
MobilityTransformR converts CE-MS migration times to an effective-mobility scale using added mobility markers.
Includes: Spectral data reading and writing
Preprocessing and feature extraction
MOCCal calibrates traveling-wave ion-mobility measurements and calculates class-specific experimental CCS values.
Includes: Multivariate statistics
Metabolite annotation and identification
A GNPS2-associated computational tool for localizing structural modification sites by aligning MS/MS spectra of a known compound and a structurally related unknown analogue.
Includes: Structure elucidation · Substructure prediction · MS/MS processing
Machine learning and prediction
A research codebase for graph-neural-network prediction of ion-mobility collision cross sections from molecular structure, developed to evaluate model generalizability across chemical domains.
Includes: Collision-cross-section prediction
Molecular networking and chemical similarity
Combine molecular networking, substructure motifs and chemical classifications into annotated networks.
Includes: Network visualization · Compound-class prediction
Molecular networking and chemical similarity
Create metadata-based molecular networks from GNPS networks or feature tables to explore how metabolites are distributed across sample groups.
Includes: Network visualization
Molecular networking and chemical similarity
A Python package that interprets LC-MS/MS ion relationships and spectral evidence to infer molecule-centric networks rather than networks of individual ion signals.
Includes: Ion identity networking · Spectral-library matching · Network visualization
Reference data and database search
Search aggregated mass spectra and download reference libraries for local annotation workflows.
Includes: Metadata-based contextualization · Provenance tracking
Quantification and targeted analysis
Quantify targeted metabolites from MRM chromatograms.
Includes: Calibration-curve quantification · Peak or feature detection
Metabolite annotation and identification
MS-BART models molecular representations and mass-spectral information with a unified language-model workflow for structure elucidation.
Includes: Structure elucidation
Preprocessing and feature extraction
A graphical and command-line workbench for untargeted metabolomics and lipidomics data processing across multiple chromatography and mass spectrometry platforms.
Includes: Peak or feature detection · Spectral deconvolution · Retention-time alignment · Gap filling · +4 more
Metabolite annotation and identification
Explore formula and structure candidates using fragmentation rules and EI-MS or MS/MS library searches.
Includes: Molecular-formula prediction · Structure elucidation · Spectral-library matching
Preprocessing and feature extraction
MS-MINT (MS-Metabolomics Integrator) is a Python application for processing, analyzing, and visualizing large liquid chromatography-mass spectrometry (LC-MS) metabolomics datasets
Metabolite annotation and identification
MS-Net combines annotation levels from both mass spectral libraries and in silico tools such as MS-Finder or Sirius-CSI to build a comprehensive candidate chemical space. Then, MS-Net prioritizes annotation using the molecular network and Tanimoto-based similarity with optional biosource reranking. Additionnaly it can combine positive and negative acquisition modes and add metadata to all annotated features, such as chemical ontology or database identifiers.
Metabolite annotation and identification
An open-source Python application for interpreting radical-induced dissociation tandem mass spectra, with current support focused on oxygen attachment dissociation for detailed lipid structural annotation.
Includes: Structure elucidation · MS/MS processing
Metabolite annotation and identification
Combine GNPS, ISDB-LOTUS and SIRIUS annotations into scores for natural-product feature prioritization.
Includes: Identification-confidence assessment
Spectral processing and comparison
Estimate molecular structural similarity from pairs of tandem mass spectra.
Includes: Spectral-library matching
Spectral processing and comparison
Find recurring patterns of fragments and neutral losses across tandem mass spectra.
Includes: Substructure prediction
Metabolite annotation and identification
A Python package for machine-learning prediction of lipid subclasses from tandem mass spectra using curated lipid MS/MS reference data.
Includes: Compound-class prediction · MS/MS processing
Data acquisition and instrument control
Plan precursor acquisition schedules from LC-MS survey features.
Includes: Blank and contaminant filtering
Spectral processing and comparison
MS/MS analogue-search tool that combines learned spectral similarity and precursor-mass information to retrieve structurally related reference compounds.
Includes: Spectral-library matching
Spectral processing and comparison
Embed tandem spectra for similarity scoring and reference-library matching.
Includes: Spectral-library matching
Data conversion and import
Convert mass-spectrometry files into open formats for downstream analysis.
Includes: Provenance tracking
Spectral processing and comparison
An open-source multi-language implementation of spectral entropy, entropy similarity, and flash entropy search for comparing and querying small-molecule mass spectra.
Includes: Spectral-library matching · MS/MS processing
Metabolite annotation and identification
A research implementation for de novo molecular-structure generation from mass-spectral evidence using pseudodata-trained machine learning.
Includes: Structure elucidation
Preprocessing and feature extraction
GC-MS processing workflow that aligns chromatographic data and deconvolves overlapping signals into spectra and quantitative tables for downstream GNPS analysis.
Includes: Spectral deconvolution
Visualization and reporting
Explore ion images and region-of-interest spectra in a napari imaging-MS interface.
Includes: Interactive dashboard
Workflow management and reproducibility
msiFlow provides Snakemake workflows for MSI preprocessing, segmentation, registration to immunofluorescence microscopy and region-based statistical or machine-learning analysis.
Includes: Container support · Multivariate statistics
Machine learning and prediction
MSIonization is a Python package for predicting the optimal ionization mode with higher ionization efficiency for organic molecules from their SMILES representations.
Visualization and reporting
Vendor-neutral desktop software for visualization, analysis and interpretation of high-resolution mass spectrometry imaging datasets.
Includes: Interactive dashboard
Quality control and filtering
MSlineaR, is an open-source R-based software tool implementing a six-step process to assess dilution-dependent response behavior in metabolomic data sets.
Spectral processing and comparison
A GNPS workflow for automatically selecting candidate reference MS/MS spectra from LC-MS data of known standards using supplied molecular structures and expected precursor masses.
Includes: Reference-spectrum selection · MS/MS processing
Spectral processing and comparison
Manipulate, process and visualize mass-spectrometry data within R.
Includes: MS/MS processing
Reference data and database search
Open multistage fragmentation reference spectra and a reproducible library-generation workflow implemented with mzmine.
Includes: Reference-spectrum selection
Metabolite annotation and identification
A SIRIUS-integrated de novo structure-generation method that proposes molecular structures from a predicted molecular formula and CSI:FingerID fingerprint when database search is insufficient.
Includes: Structure elucidation · Substructure prediction · Molecular-formula prediction
Data conversion and import
mspack provides lossless and configurable lossy compression of mass-spectrometry arrays through a C++ API and example mzML/mzXML command-line implementation.
Includes: Spectral data reading and writing
Quality control and filtering
Calculate standardized per-sample quality metrics from mass spectrometry data in R.
Includes: Spectral data reading and writing
Spectral processing and comparison
Apply a predefined sequence of MassQL queries to GNPS2 networking spectra to investigate bile acids and their isomers.
Includes: MS/MS processing · Compound-class prediction
Normalization and batch correction
A Bioconductor R package for batch-effect correction in single-omics and multi-omics datasets, including metabolomics.
Includes: Batch-effect correction
Pathway and biological interpretation
Generate pathway and network hypotheses from untargeted metabolomics feature tables.
Includes: Pathway enrichment
Metabolite annotation and identification
Estimate molecular weight from electron-ionization spectra.
Includes: Spectral data reading and writing · Interactive dashboard
Data conversion and import
Convert multidimensional mass-spectrometry data from vendor formats or mzML into an HDF5-based MZA structure for efficient storage and programmatic access.
Includes: MS/MS processing
Preprocessing and feature extraction
Read, extract, calibrate, and visualize multidimensional mass-spectrometry data in Python, including LC-IM-MS datasets stored in MZA and selected vendor-supported formats.
Includes: Chromatogram building · Peak or feature detection · MS/MS processing
Preprocessing and feature extraction
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.
Includes: Adduct and isotope grouping · Batch-effect correction · Blank and contaminant filtering · Chromatogram building · +12 more
Quality control and filtering
An R package for metabolomics study quality control, including outlier detection, pooled-QC batch correction, reliability filtering, diagnostic visualization, and reporting.
Includes: Batch-effect correction · QC-based drift correction · Calibration-curve quantification
Visualization and reporting
Open-source environment for interactive processing, visualization and registration of two- and three-dimensional mass spectrometry imaging data.
Includes: Spectral data reading and writing · Peak or feature detection · Container support
Reference data and database search
Explore structures and literature for bacterial and fungal natural products.
Includes: Structure-database searching
Quality control and filtering
An open-source Python package that uses neural-network classification to label and filter false-positive MS1 peaks from untargeted LC-MS feature-detection workflows.
Includes: Feature selection
Metabolite annotation and identification
An R-based global network-optimization method for annotating untargeted LC-MS features using measured masses, retention times, known chemical relationships, and optional MS/MS evidence.
Includes: Adduct and isotope grouping · Spectral-library matching · Structure-database searching
Workflow management and reproducibility
A reproducible Nextflow workflow for LC-HRMS metabolomics that executes MS-DIAL-based processing across local, containerized, and high-performance computing environments.
Includes: Provenance tracking · Container support · Peak or feature detection · Retention-time alignment · +1 more
Normalization and batch correction
Normalize metabolomics data and compare the performance of alternative normalization strategies.
Includes: Batch-effect correction
Normalization and batch correction
Norm-ISWSVR normalizes metabolomics tables by combining internal-standard correction with support-vector-regression-based adjustment.
Includes: Batch-effect correction · QC-based drift correction
Preprocessing and feature extraction
Process LC-MS/MS data for natural-product profiling and molecular-network exploration.
Includes: MS/MS processing · Spectral-library matching · Network visualization
Metabolite annotation and identification
Deep neural-network tool that classifies natural-product structures into biosynthetic pathways, superclasses and structural classes.
Includes: Compound-class prediction
Multi-omics integration
Ranks candidate links between microbial biosynthetic gene clusters and MS metabolomics spectra or molecular families using paired strain data.
Includes: Metadata-based contextualization
Statistical analysis
omicsMIC provides an interactive framework for simulating missingness and comparing imputation methods in mass-spectrometry-based omics matrices.
Includes: Interactive dashboard
Multi-omics integration
Separate shared and dataset-specific variation when integrating two omics data matrices.
Includes: Multivariate statistics
Preprocessing and feature extraction
Inspect and process chromatographic and mass-spectrometric data in a desktop workbench.
Includes: Peak or feature detection
Workflow management and reproducibility
An open-source C++ library, command-line toolkit, and Python interface for reproducible mass spectrometry data processing in metabolomics and proteomics.
Includes: Peak or feature detection · Retention-time alignment · Gap filling · Provenance tracking
Data conversion and import
Read Bruker timsTOF TDF data through C++, Python or R interfaces.
Includes: Spectral data reading and writing
Metabolite annotation and identification
OrbiFragsNets annotates Orbitrap data-dependent MS2 peaks with candidate fragment formulas using peak-specific uncertainty and chemical-consistency networks.
Includes: MS/MS processing
Machine learning and prediction
PACCS predicts CCS from molecular conformers using voxel-projected area, molecular-graph information, mass-to-charge ratio and adduct encoding.
Includes: Collision-cross-section prediction
Pathway and biological interpretation
Visualize metabolomics alongside other omics layers on biological pathways.
Includes: Pathway enrichment · Network visualization
Data management and sharing
A pan-repository metadata harmonization and search infrastructure for finding, contextualizing, downloading, and reanalyzing public metabolomics data across major repositories.
Includes: Metadata-based contextualization · Repository-scale spectral search
Preprocessing and feature extraction
Estimate LC-MS processing parameters from measured data for downstream feature extraction.
Includes: Peak or feature detection
Workflow management and reproducibility
Assemble reproducible non-target screening workflows for environmental mass spectrometry in R.
Includes: Provenance tracking · Structure-database searching
Preprocessing and feature extraction
Detect chromatographic peaks in profile-mode LC-HRMS data using machine learning.
Includes: Peak or feature detection
Metabolite annotation and identification
Use machine learning to support metabolite identification and error-rate estimation in multidimensional LC-IM-MS-DIA data.
Includes: Identification-confidence assessment · MS/MS processing
Preprocessing and feature extraction
R package for targeted extraction and integration of predefined metabolic features across LC-MS profiling files.
Includes: Peak or feature detection · Chromatogram building
Reference data and database search
A domain-specific GNPS search and exploration resource for contextualizing query MS/MS spectra across taxonomically defined plant metabolomics datasets.
Includes: Repository-scale spectral search · Metadata-based contextualization · Spectral-library matching · Interactive dashboard
Machine learning and prediction
PLSKO generates partial-least-squares-based knockoff variables and applies knockoff filtering for omics feature selection.
Includes: Feature selection
Preprocessing and feature extraction
Preprocess multidimensional ion-mobility mass-spectrometry data with demultiplexing, smoothing, noise filtering, saturation repair, and format-conversion utilities.
Includes: Spectral deconvolution
Spectral processing and comparison
Run MassQL chemical-pattern queries directly on consensus spectra produced by GNPS molecular networking.
Includes: MS/MS processing · Provenance tracking
Reference data and database search
Search chemical structures, identifiers, properties and contributed annotations.
Includes: Structure-database searching
Quality control and filtering
A Python implementation of EVA for automated evaluation of extracted-ion chromatogram fidelity, using deep learning to classify LC-MS features as likely true or false signals.
Includes: Feature selection
Data conversion and import
Python library for reading and writing imzML imaging mass-spectrometry data.
Includes: Spectral data reading and writing
Visualization and reporting
pyOpenMS-viz extends pandas plotting for mass-spectrometry data, including chromatograms, mobilograms, spectra and two- or three-dimensional peak maps.
Includes: Interactive dashboard
Workflow management and reproducibility
An open Python workflow for LC-MS metabolomics that converts supported raw data, performs feature extraction with Asari, applies QC and normalization, groups empirical compounds, and supports MS1/MS2 annotation.
Includes: Provenance tracking · Peak or feature detection · Blank and contaminant filtering · Batch-effect correction · +2 more
Quality control and filtering
Monitor LC-MS data quality with a configurable processing service, database and dashboard.
Includes: Container support · Interactive dashboard
Quantification and targeted analysis
Calculate concentrations from integrated LC-MS signals with calibration and drift correction.
Includes: Calibration-curve quantification · QC-based drift correction
Normalization and batch correction
An R-based regularized adversarial-learning method for harmonizing metabolomics batches using shared reference samples while preserving biological similarity structure.
Includes: Batch-effect correction
Preprocessing and feature extraction
Cluster related mass-spectrometry features and export compound-level spectra and abundances.
Includes: Spectral deconvolution · Adduct and isotope grouping
Pathway and biological interpretation
Integrated metabolite, gene/protein, reaction, ontology and pathway resource for metabolomics and multi-omics pathway analysis.
Includes: Pathway enrichment
Quality control and filtering
Monitor LC-MS acquisition quality through an interactive dashboard.
Includes: Interactive dashboard
Spectral processing and comparison
A research implementation for rapid prediction of electron-ionization mass spectra from molecular structures using neural-network models.
Includes: In-silico spectrum prediction
Quality control and filtering
Inspect LC-MS instrument logs and raw QC measurements through an R Shiny interface.
Includes: Interactive dashboard
Reference data and database search
Explore curated metabolic and signaling reactions with literature-linked pathway context.
Includes: Structure-database searching
Reference data and database search
Map metabolite names to a standardized reference nomenclature for cross-study comparisons.
Includes: Structure-database searching
Machine learning and prediction
A research implementation of transfer-learning graph neural networks for chromatographic retention-time prediction from molecular structure using small target training datasets.
Includes: Retention-time prediction
Metabolite annotation and identification
An R package for broad-scoped targeted and semi-targeted LC-MS metabolomics analysis designed to deeply characterize biological and environmental samples.
Includes: Chromatogram building · Peak or feature detection
Preprocessing and feature extraction
rIDIMS processes direct-infusion MS by selecting usable scans, forming consensus spectra and filtering features with replicate and background information.
Includes: Blank and contaminant filtering · Interactive dashboard · Reference-spectrum selection
Visualization and reporting
Open-source R package and GUI for memory-efficient handling, exploration and visualization of mass spectrometry imaging datasets.
Includes: Interactive dashboard
Preprocessing and feature extraction
Open-source R/C++ package for large-scale MSI preprocessing, including smoothing, alignment, recalibration, normalization, peak picking and binning.
Includes: Peak or feature detection
Metabolite annotation and identification
Predict relative LC retention behavior and combine it with MS/MS scores to rank candidate structures.
Includes: Structure elucidation
Statistical analysis
Fit and assess multivariate PCA, PLS and OPLS models for omics data in R.
Includes: Multivariate statistics · Feature selection
Visualization and reporting
Commercial software suite for processing, statistical analysis, segmentation, annotation and 2D/3D visualization of mass spectrometry imaging data.
Includes: Interactive dashboard · Multivariate statistics
Metabolite annotation and identification
Generate candidate molecular structures from tandem spectra and a supplied molecular formula.
Includes: Structure elucidation
Normalization and batch correction
SERDA applies denoising-autoencoder normalization to processed metabolomics data.
Includes: Batch-effect correction
Molecular networking and chemical similarity
SGMNS propagates candidate metabolite annotations through a structure-guided background molecular network.
Includes: Structure-database searching
Metabolite annotation and identification
Predict collision cross sections from molecular structures and ion adducts.
Includes: Collision-cross-section prediction
Spectral processing and comparison
A Python library for relating fragmentation spectra using statistically assessed fragment and neutral-loss relationships, including pairwise and multiple spectral matching.
Includes: MS/MS processing
Isotope tracing and flux analysis
Extract and correct isotopologue distributions from isotope-enriched metabolomics feature lists.
Includes: Isotopologue correction
Metabolite annotation and identification
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.
Includes: Chromatogram building · Compound-class prediction · Identification-confidence assessment · Spectral-library matching · +7 more
Quantification and targeted analysis
Develop and review targeted mass-spectrometry assays, including small-molecule quantification.
Includes: Calibration-curve quantification · Chromatogram building
Preprocessing and feature extraction
A scalable, containerized workflow for untargeted LC-MS preprocessing with automated parameter optimization, feature detection, alignment, gap filling, isotope/adduct grouping, and DDA MS/MS consolidation.
Includes: Peak or feature detection · Retention-time alignment · Gap filling · Adduct and isotope grouping · +2 more
Metabolite annotation and identification
Rank molecular-formula candidates for spatial-metabolomics mass features.
Includes: Molecular-formula prediction
Statistical analysis
Analyze metabolomics data with the SMART R/GUI processing, QC and statistical modules.
Includes: Univariate statistics · Multivariate statistics
Quantification and targeted analysis
Automate targeted and semi-targeted chromatographic data processing and quantification.
Includes: Calibration-curve quantification · Peak or feature detection
Quality control and filtering
Inspect and filter spatial-metabolomics peak matrices through interactive QC views.
Includes: Interactive dashboard · Adduct and isotope grouping
Multi-omics integration
Open-source framework for joint analysis, annotation, alignment, integration and visualization of spatial metabolomics and spatial transcriptomics.
Includes: Univariate statistics · Multivariate statistics · Pathway enrichment · Container support
Spectral processing and comparison
Compare tandem mass spectra using embeddings learned from recurring peaks and neutral losses.
Includes: Spectral-library matching
Molecular networking and chemical similarity
SpecReBoot brings the statistical rigor of phylogenetic bootstrapping to mass spectrometry. It resamples spectral features to estimate edge support and build consensus molecular networks with quantified confidence.
Spectral processing and comparison
Store, filter, process and compare mass spectra through a common R interface.
Includes: MS/MS processing
Spectral processing and comparison
Spectral Denoising removes candidate electronic and chemical noise ions from tandem spectra.
Includes: MS/MS processing · Spectral-library matching
Data conversion and import
An R package that connects the RforMassSpectrometry Spectra ecosystem with Python, enabling exchange and joint analysis of mass-spectrometry data across R and Python workflows.
Includes: Spectral data reading and writing
Metabolite annotation and identification
SpecTUS translates GC-electron-ionization mass spectra into candidate SMILES structures using a transformer pretrained on synthetic spectra and fine-tuned on experimental spectra.
Includes: Structure elucidation
Visualization and reporting
An open-source Python resource for interactive exploration and visualization of mass-spectral similarity relationships.
Includes: Network visualization · Interactive dashboard
Quality control and filtering
Correct signal drift and analyze molecular-profile data from single- or multi-batch studies.
Includes: QC-based drift correction · Batch-effect correction
Reference data and database search
A GNPS2 web application for structure- and substructure-centric searching across public metabolomics repositories using chemical names, SMILES, SMARTS, and matched reference spectra.
Includes: Repository-scale spectral search · Metadata-based contextualization · Structure-database searching · Substructure prediction
Quantification and targeted analysis
An R package for targeted raw-data integration in mass spectrometry, designed to extract and quantify user-specified signals directly from raw or converted data.
Includes: Chromatogram building
Workflow management and reproducibility
Connect LC-MS processing, quality control, annotation and interpretation through an R package ecosystem.
Includes: Provenance tracking
Preprocessing and feature extraction
A Python library for reading, processing, curating, and visualizing mass-spectrometry data in metabolomics, including LC-MS feature detection, correspondence, and data-matrix curation.
Includes: Chromatogram building · Peak or feature detection · Retention-time alignment
Metabolite annotation and identification
timaR helps annotate metabolites in MS/MS data by combining spectral matching with taxonomic information about the organisms being studied. It can incorporate retention-time evidence and existing SIRIUS or GNPS annotations to prioritize candidate compounds.
Includes: Spectral-library matching
Data conversion and import
An open-source workflow for converting Bruker timsTOF raw data, including trapped-ion-mobility information, into open mzML and imzML formats for downstream analysis.
Includes: Spectral data reading and writing
Visualization and reporting
Hosted utility for sharing mass spectra through reusable spectrum identifiers in the GNPS2 ecosystem.
Includes: Provenance tracking
Workflow management and reproducibility
A Snakemake workflow for high-throughput untargeted metabolomics that combines file conversion, OpenMS preprocessing, SIRIUS-family annotation, GNPS export, spectral matching, and graph-based outputs.
Includes: Provenance tracking · Container support · Peak or feature detection · Retention-time alignment · +4 more
Data acquisition and instrument control
ViMMS simulates LC-MS/MS acquisition at scan level so researchers can prototype and compare fragmentation strategies.
Includes: Spectral data reading and writing
Metabolite annotation and identification
Search tandem spectra against candidate molecules and their mass-shifted variants.
Includes: Structure elucidation · Identification-confidence assessment
Normalization and batch correction
Correct injection-order-associated variation in untargeted metabolomics tables.
Includes: Batch-effect correction
Reference data and database search
Find and contribute biological pathway diagrams and machine-readable pathway knowledge.
Includes: Structure-database searching
Workflow management and reproducibility
Create and share metabolomics processing and analysis workflows in a Galaxy environment.
Includes: Provenance tracking
Preprocessing and feature extraction
An open-source Bioconductor package for chromatographic mass spectrometry data preprocessing, feature detection, alignment, grouping, and visualization.
Includes: Chromatogram building · Peak or feature detection · Retention-time alignment · Gap filling · +1 more
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