Provides a web-based analytical pipeline for high-throughput metabolomics studies. MetaboAnalyst aims to offer a variety of commonly used procedures for metabolomic data processing, normalization, multivariate statistical analysis, as well as data annotation. The current implementation focuses on exploratory statistical analysis, functional interpretation, and advanced statistics for translational metabolomics studies. This tool is also available as desktop version.
A total solution to deal with not only data dependent MS/MS but also data independent MS/MS experiments for metabolomics and lipidomics. Its feature is 1) implementing de-convolution method for data independent MS/MS 2) using unified criteria for peak identification 3) supporting all data processing step from raw data import to statistical analysis 4) user-friendly graphic user interface. MS-DIAL deals with data independent acquisition MS/MS data (ex. SWATH) by means of two step algorithms (peak spotting and MS2Dec) for spectral deconvolution. Also, it supports compound identification, peak alignment, and principal component analysis on the graphical user interface. The spectrum information is outputted by MassBank, NIST, and Mascot formats. And the organized data matrix (sample vs metabolite) is exported as tab delimited text file.
Allows users to query the BinBase gas chromatography–mass spectrometry (GC-MS) metabolome database for exploring compounds. BinVestigate queries biological metadata for each metabolite. The software provides open access information about abundance, frequency, species, and organ origin. It can be used to query unknowns from metabolomics studies and to prioritize and select targeted unknowns for structural identification on the basis of their cross-study specificity and relevance.
Allows users to analyze and visualize liquid chromatography – mass spectrometry (LC-MS) data. PiMP is a comprehensive and integrated web enabled pipeline that consists of five tasks: (1) project administration, (2) data upload, (3) quality control, (4) analysis parameters and (5) data interpretation. Users can define the experimental design, specify metadata and share the project with collaborators with a chosen level of permission. It aims at automatization and standardization of metabolomics analysis.
An LC/MS-based data analysis approach which incorporates novel nonlinear retention time alignment, feature detection, and feature matching. The XCMS software reads and processes LC/MS data stored in netcdf , mzXML, mzData and mzML files. It provides methods for feature detection, non-linear retention time alignment, visualization, relative quantization and statistics. XCMS is capable of simultaneously preprocessing, analyzing, and visualizing the raw data from hundreds of samples. XCMS is freely available under an open-source license.
Extracts metabolite information from raw. ADAP-GC is an automated computational pipeline for untargeted, gas chromatography mass spectrometry (GC/MS)-based metabolomics studies. This workflow is designed to preprocess raw, untargeted, GC/MS metabolomics data. It carries out a sequence of computational tasks that includes construction of extracted ion chromatograms (EICs), detection of peaks from EICs, spectral deconvolution, and alignment of analytes across samples.
Offers a platform dedicated to metabolite annotation. CEU Mass Mediator gives access to more than 270 000 real compounds extracted from four repositories including KEGG and LipidMaps as well as simulated compounds extracted from MINE. The application enables multiple query options, pathway displaying and the scoring of putative annotations, with a focus on reversed phase-liquid chromatography-electro spray ionization-mass spectrometry (RP-LC-ESI-MS) data.
Enables candidate substructure annotation of multistage accurate mass spectral trees. MAGMa is a web server that matches substructures of candidate molecules with multistage fragmentation data, resulting in a calculated candidate score allowing comparison of hundreds of candidates for a detected precursor mass. The software permits automated annotation of mass multistage mass spectrometry (LC−MSn) data with in silico generated metabolites.
An open-source software tool for mass-spectrometry data processing, with the main focus on LC-MS data. It is based on the original MZmine toolbox described in the 2006 Bioinformatics publication, but has been completely redesigned and rewritten since then. Our main goal is to provide a user-friendly, flexible and easily extendable software with a complete set of modules covering the entire LC-MS data analysis workflow.
Allows users to investigate molecular structure repositories starting from tandem mass spectrometry (MS/MS) data of small molecules. CSI:FingerID merges fragmentation trees and molecular fingerprints to elucidate a compound. It employs a Bayesian network to draw dependencies between molecular properties. This tool can find identity and connectivity of the atoms including bond multiplicities, but no spacial information.
Allows users to explore fragment data. MS2LDA is based on the Latent Dirichlet Allocation (LDA) method. It guides interpretation of comparative untargeted metabolomics experiments and prioritizes structural characterization of Mass2Motifs across large sample sets. This tool can find relevant substructures and/or substructures of both endogenous and exogenous origin in urine cohort samples where intragroup variance was suspected to arise from differential drug and/or food administration.
Allows peaks detection from high-resolution liquid-chromatography/mass-spectrometry (LC/MS) data. apLCMS is a machine learning approach designed for the processing of LC/MS based metabolomics data. The method learns directly from various data features of the extracted ion chromatograms (EICs) to differentiate between true peak regions from noise regions in the LC/MS profile. There are two major routes of data analysis: unsupervised analysis and hybrid analysis.
Permits comprehensive metabolomics data pre-processing, statistical analysis and interpretation. W4M includes computational modules for data normalization, multivariate analysis and annotation. It can create interactive web-based documents showing the results of the analyses, and users can share them with collaborators directly on the platform. This tool enables multi-omics analyses in a global systems-biology approach.
Provides a convenient visual summary of the quality and quantity of labelling. mzMatch–ISO is an extension to mzMatch, an open-source Java toolbox for mass spectrometry (MS) data processing and visualization. It provides an efficient and user-friendly output for the analysis and compact visualization of isotope-labelled metabolomics datasets without the need for specialist bioinformatics skills, allowing rapid, precise and meaningful biological interpretation.
Aims to integrate and analyze metabolomics experiment data. MeltDB is a program that can be applied for the description and analysis of metabolomic experiments. This program hosts over 30 experiments predominantly from gas chromatography-mass spectrometry (GC/MS) measurements. Moreover, this tool includes an API allowing users to evaluate novel methods and algorithms for the preprocessing of metabolomic datasets.
Allows users to detect biologically derived compounds. MetExtract is a toolbox for stable isotope labeling (SIL) -assisted and liquid chromatography high resolution mass spectrometry LC-HRMS(/MS)-based untargeted metabolomics. The software consists of three modules: AllExtract, TracExtract and FragExtract and supports experiments using native and highly isotope-enriched biological material or tracer compounds.
Combines statistical analysis modules into pipelines to deal with heterogenous big data. T-BioInfo is an application that can be used for: (1) next-generation sequencing (NGS) data (transcriptomics, genomics/epigenetics, and DNA/RNA); (2) mass-spectroscopy; (3) structural biology; and (4) data integration and modeling (virology, data association, and data mining).
A computational platform entitled MetSign for high-resolution mass spectrometry-based metabolomics. By converting the instrument raw data into mzXML format as its input data, MetSign provides a suite of bioinformatics tools to perform raw data deconvolution, metabolite putative assignment, peak list alignment, normalization, statistical significance tests, unsupervised pattern recognition, and time course analysis. MetSign uses a modular design and an interactive visual data mining approach to enable efficient extraction of useful patterns from data sets.
Provides an application for daily routine and emergency toxicology. AMDIS is a software developed to identify of even low-abundant peaks in the total ion chromatograms (TIC) and the reduction of the evaluation time by half. This method first deconvolutes pure component spectra and related information such as peak shape and retention time from complex chromatograms and subsequently matches the obtained spectra with those of a reference library.
Helps to process accurate mass data as nominal mass data. MetAlign is a software program for the pre-processing and comparison of full scan nominal or accurate mass Liquid chromatography-mass spectrometry (LC–MS) and Gas chromatography-mass spectrometry (GC–MS) data. It involves running multiple threads simultaneously so that a one thread per core situation is established in which memory between threads is not shared.
Allows peak identification, prediction, and data integration of MetAlign results. AIoutput is a non-targeted and targeted analysis software developed for Gas chromatography coupled to mass spectrometry (GC/MS) based metabolomics
An R package of a set of tools and functions to perform an automatic end-to-end analysis of LC/MS metabolomic data, putting special emphasis on peak annotation and metabolite identification. The goal of the MAIT package is to provide an array of tools that makes programmable metabolomic end-to-end statistical analysis possible. MAIT includes functions to improve peak annotation through the process called biotransformations and to assess the predictive power of statistically significant metabolites that quantify class separability.
A tool operating in the Taverna environment for putative identification of metabolites from accurate mass data acquired in mass spectrometry-based metabolic profiling studies. Three workflows perform the following steps. (Step 1) Generation of a list of pairwise peak correlations required for input to workflow 2 (workflow 1) (Step 2) Annotation of features to group different ion types of the same metabolite based on mass differences, similar retention times and correlation coefficient between peak responses (workflow 2). (Step 3) Matching of accurate m/z to the accurate mass of neutral molecules and associated molecular formula in a reference file within a specified mass tolerance (workflow 2). (Step 4) Matching of the molecular formulae to a reference file of metabolites (workflow 3).
An R package for high-throughput processing of metabolomics data analysed by the Automated Mass Spectral Deconvolution and Identification System (AMDIS). In addition, it performs statistical hypothesis test (t-test) and analysis of variance (ANOVA). Doing so, Metab considerably speed up the data mining process in metabolomics and produces better quality results. Metab was developed using interactive features, allowing users with lack of R knowledge to appreciate its functionalities.
Provides a program for the quantitative analysis of high throughput Gas Chromatography-Mass Spectrometry (GC-MS)-based metabolomics data. MetaQuant is intended to automatically determine the accurate intracellular amount of hundreds of metabolites. It provides access to various functions: (i) metabolite definition, (ii) calibration, (iii) quantification, (iv) import and export of data and (v) batch analysis.
Calculates the sum formula of all molecules whose mass equals the input mass. DECOMP is a program to compute decompositions of an input query. Its two primary applications are (i) computing sum formulas of sample molecules from MS spectra, i.e. identifying all molecules with a certain molecular mass from different types of samples: protein, DNA, metabolites or others; and (ii) solving instances of the Money Changing Problem.
Identifies metabolites from multi-stage mass spectrometry (MSn) data. MetiTree aims to assist in designation of chemical compounds by providing a set of tools for compute, visualize, compare and organize MSn information. It contains multiple features allowing users to access to a spectral tree viewer, a way for creating directories for gathering files according to projects and to query for similar MSn data stored in the library.
A software tool to determine, visualize and analyze mass isotopomer distributions across multiple GC–EI-MS datasets in a non-targeted manner. MIA helps to reveal changes in metabolic fluxes, visualizes metabolic proximity of isotopically enriched compounds and shows the fate of the applied stable isotope labeled tracer.
Manages information related with metabolite identification. WebMetabase offers a platform that allows users to store, investigate and visualize data. The application provides modules to analyze specific or grouped compounds that includes features for kinetic, metabolic pathways or peptide frequency analysis as well as managing options to facilitate data sharing, import/export and reporting.
Permits users to realize autonomous and real-time analysis of metabolomic data. SimExTargId is an open source R package that provides an autonomous workflow that can also calculate data preprocessing in real-time, thereby alerting the user to signal degradation or loss. This method also facilitates real-time monitoring of liquid chromatography-mass spectrometry (LC-MS) data acquisition.
Assists researchers in searching compound and predicting elemental compositions. MFSearcher is a RESTful web service which purpose is to refine the prediction of elemental compositions from mass values detected by high-resolution mass spectrometers. The application also allows users to investigate more than 10 databases including ExactMassDB or LipidMaps. It aims to improve comprehensiveness and throughput of annotations of metabolite peaks.
Offers a platform dedicated to chemical annotation of tandem mass spectrometry (MS/MS) data. ChemDistiller is a modulable application that uses in-built large-scale chemical compound databases to retrieve, filter and score candidate molecules. The program can work in conjunction with various software: it accepts information from XCMS and mzMine as well as data generated by SIRIUS and MetaSpace.
Assists users in analyzing unsupervised data mining on gas chromatography-mass spectrometry data. MSeasy is an alternative approach for gas chromatography-mass spectrometry (GC-MS) data processing, insensitive to shift in retention time. It works directly on the raw mass spectra (MS) rather than on extensively corrected chromatograms. This method accelerates the data processing and supports interpretation of complex GC-MS datasets by extracting human-understandable structure and supplying quality control criteria.
Allows users to perform Two Dimensional Gas Chromatography-Mass Spectrometry (2D-GCMS) derived metabolite peak alignment and identification. R2DGC uses individual sample files including basic peak information to generate an alignment table which shows the peaks common to several samples and match the aligned one to a reference library. The pipeline also furnish a reference library gathering information about 298 peaks issued from over 125 metabolite standards and commonly observed background peaks.
Aligns and calculates pairwise similarity scores among mass spectrometry (MS)/MS spectral data. MetCirc is an open-source package to make biological sense of mass spectral similarities from metabolomics data by providing a dedicated data analysis infrastructure and visualization interface to explore small molecules that mediate functionally important phenotypes. It can be used to pinpoint and formulate first structural hypothesis on previously non-characterized metabolites associated with a given phenotype.
Uses probalistic methods for the filtration of liquid chromatography–mass spectrometry or gas chromatography-mass spectrometry. EMP evaluates the given instrument, detects compounds and calculates the probability of individual peaks. It can be useful for multiple purposes: for expert data assessment, automated generation of compound databases, performance analysis of the instrument or for validity assessment of biological models.
Allows users to perform fingerprint prediction. SIMPLE proposes a machine learning model, using fragmentation trees (FTs) for regularization, able to integrate peak interactions with the aim of increasing not using interactions predictions’ efficiency as well as of showing the interpretability of results. This model was tested with real data extracted from the MassBank dataset.
Integrates algorithms to extract compound spectra, annotate isotope and adduct peaks, and propose the accurate compound mass even in highly complex data. CAMERA integrates multiple methods for grouping related features, and uses a dynamic rule table for the annotation of ion species. It is designed to post-process XCMS feature lists, and to collect all features related to a compound into a compound spectrum. For this, a set of algorithms has been implemented in CAMERA, such as the fast retention time-based grouping, but also a graph-based algorithm to integrate the peak shape analysis, isotopic information and intensity correlation across samples. The automatic sample selection avoids poor results if compounds have a low intensity (or are absent) in some samples. The ion species annotation uses a dynamic rule set, and a new strategy to combine spectral information from samples measured in positive and negative ion mode.
A software tool for the efficient and automatic analysis of GC/MS-based metabolomics data. Starting with raw MS data, MetaboliteDetector detects and subsequently identifies potential metabolites. Moreover, a comparative analysis of a large number of chromatograms can be performed in either a targeted or nontargeted approach. It automatically determines appropriate quantification ions and performs an integration of single ion peaks. The analysis results can directly be visualized with a principal component analysis. Since the manual input is limited to absolutely necessary parameters, the program is also usable for the analysis of high-throughput data. However, the intuitive graphical user interface of MetaboliteDetector additionally allows for a detailed examination of a single GC/MS chromatogram including single ion chromatograms, recorded mass spectra, and identified metabolite spectra in combination with the corresponding reference spectra obtained from a reference library. MetaboliteDetector is able to import GC/MS data in NetCDF and FastFlight format.
Analysis of metabolomic profiling data from gas chromatography-mass spectrometry (GC/MS) measurements. SpectConnect allows for systematic, automated analysis of GC/MS metabolite profiling data sets including metabolites that may not be structurally identified by a reference library. It can systematically detect components that are conserved across samples without the need for a reference library or manual curation.
A two-part approach for performing metabolomic identifications. First, MS(2) scans are collected with less stringent isolation settings to obtain improved sensitivity at the expense of specificity. Then, by evaluating MS(2) fragment intensities as a function of retention time and precursor mass targeted for MS(2) analysis, deconvolved MS(2) spectra are obtained that are consistent with pure standards and can therefore be used for metabolite identification.
Clusters non-targeted mass spectrometric metabolomics data. With RAMClustR, feature detection is performed on both MS and idMS/MS (indiscriminant MS/MS) data and feature-feature relationships are determined simultaneously from the MS and idMS/MS data. This tool facilitates identification of metabolites using in-source MS and/or idMS/MS spectra from a single experiment, reduces quantitative analytical variation as compared to single feature measures, and decreases false positive annotations of unpredictable phenomenon as novel compounds.
Enables automatic substructure queries from accurate mass tandem mass spectrometry (MS/ MS) spectra of small molecules. MS2Analyzer can be employed for substructure annotation. It permits users to search four types of mass spectral features: (1) neutral losses, (2) m/z differences, (3) product ions, and (4) precursor ions. This tool provides a query table of about 150 specific accurate mass neutral losses and their associated formulas, names, and substructures.