Wishart Node of The Metabolomics Innovation Centre

Web Servers and Software

MetaboAnalyst is a comprehensive, Web-based tool designed for processing, analyzing, and interpreting metabolomic data. It handles most of the common metabolomic data types including compound concentration lists, spectral bin lists, peak lists, and raw MS spectra.

PubMed: 2589712827603023225533672163719521633943
19429898309094472995582129762782

  • MetATT is a easy-to-use, web-based tool designed for time-series and two-factor metabolomics data analysis. MetATT offers a number of complementary approaches including 3D interactive principal component analysis, two-way heatmap visualization, two-way ANOVA, ANOVA-simultaneous component analysis and multivariate empirical Bayes time-series analysis.  PubMed: 21712247
  • MSEA is a web-based tool to help identify and interpret patterns of metabolite concentration changes in a biologically meaningful context for human and mammalian metabolomic studies.  PubMed: 20457745 

  • ROCCET is a freely available web-based tool designed to assist clinicians and bench biologists in performing common ROC based analyses on their metabolomic data using both classical univariate and more recently developed multivariate approaches.Receiver Operating Characteristic (ROC) curves are generally considered the method of choice for evaluating the performance of potential biomarkers.  PubMed: 23543913

Bayesil is a web system that automatically identifies and quantifies metabolites using 1D 1H NMR spectra of ultra-filtered plasma, serum or cerebrospinal fluid. The NMR spectra must be collected in a standardized fashion for Bayesil to perform optimally. Bayesil first performs all spectral processing steps, including Fourier transformation, phasing, solvent filtering, chemical shift referencing, baseline correction and reference line shape convolution automatically. It then deconvolutes the resulting NMR spectrum using a reference spectral library. This deconvolution process determines both the identity and quantity of the compounds in the biofluid mixture. Extensive testing shows that Bayesil meets or exceeds the performance of highly trained human experts.

PubMed: 26017271

BioTransformer 3.0 is a freely available software package for accurate, rapid, and comprehensive in silico metabolism prediction and compound identification. BioTransformer combines a machine learning-based approach with a knowledge-based approach to predict small molecule metabolism in human tissues (e.g. liver tissue), the human gut as well as the environment (soil and water microbiota), via its Metabolism Prediction Tool.

PubMed: 355365230612223

CFM-ID 4.0 provides a method for accurately and efficiently identifying metabolites in spectra generated by electrospray tandem mass spectrometry (ESI-MS/MS). The program uses Competitive Fragmentation Modeling to produce a probabilistic generative model for the MS/MS fragmentation process and machine learning techniques to adapt the model parameters from data.

PubMed: 248954322738117231013937
References: Metabolomics 2015 Feb; 11(1): 98–110.

ClassyFire is a web-based application for automated structural classification of chemical entities. This application uses a rule-based approach that relies on a comprehensible, comprehensive, and computable chemical taxonomy. ClassyFire provides a hierarchical chemical classification of chemical entities (mostly small molecules and short peptide sequences), as well as a structure-based textual description, based on a chemical taxonomy named ChemOnt, which covers 4825 chemical classes of organic and inorganic compounds. It can be accessed via the web interface or via the ClassyFire API.

ClassyFire is offered to the public as a freely acessible web server. Use and re-distribution of the data, in whole or in part, for commercial purposes requires explicit permission of the authors and explicit acknowledgment of the source material (ClassyFire) and the original publication (see below). We ask that users who download portions of the database, or use the service (via the server or the API), cite the ClassyFire paper in any resulting publications.

GCAutoFit is a web application that automatically identifies and quantifies metabolites using Gas Chromatography Mass Spectrometry (GC-MS) spectra. For optimal GC-AutoFit performance, the query GC-MS spectra should be prepared according to the instructions (How to collect GC-MS Spectra for GC-AutoFit). GC-AutoFit currently accepts .CDF and .mzXML file formats. It uses alkane standards to calculate the retention index (RI) of each peak in the sample. The extracted EI-MS spectra from each peak, along with the RIs, are then compared to reference spectra (RIs and EI-MS) in the specified library to identify and quantify the compounds. The inclusion of blank spectra is optional, however, it is useful for removing noise effects from the query spectra. Extensive testing shows that GC-AutoFit meets or exceeds the performance of highly trained human experts

PubMed: 248954322738117231013937
References: Metabolomics 2015 Feb; 11(1): 98–110.

Heatmapper is a freely available web server that allows users to interactively visualize their data in the form of heat maps through an easy-to-use graphical interface.  Heatmapper is a versatile tool that allows users to easily create a wide variety of heat maps for many different data types and applications.  Heatmapper allows users to generate, cluster and visualize: 1) expression-based heat maps from transcriptomic, proteomic and metabolomic experiments; 2) pairwise distance maps; 3) correlation maps; 4) image overlay heat maps; 5) latitude and longitude heat maps and 6) geopolitical (choropleth) heat maps.

PubMed: 27190236

PHASTER(PHAge Search Tool Enhanced Release) is a significant upgrade to the popular PHAST web server for the rapid identification and annotation of prophage sequences within bacterial genomes and plasmids. While the steps in the phage identification pipeline in PHASTER remain largely the same as in the original PHAST, numerous software improvements and significant hardware enhancements have now made PHASTER faster, more efficient, more visually appealing and much more user friendly. A number of other optimizations have been implemented, including automated algorithms to reduce the size and redundancy of PHASTER’s databases, improvements in handling multiple (metagenomic) queries and high user traffic, and the ability to perform automated look-ups against >14,000 previously PHAST/PHASTER annotated bacterial genomes (which can lead to complete phage annotations in seconds as opposed to minutes). PHASTER’s web interface has also been entirely rewritten. A new graphical genome browser has been added, gene/genome visualization tools have been improved, and the graphical interface is now more modern, robust, and user-friendly.

PubMed: 27141966

PolySearch 2.0 is an online search engine and text-mining system for identifying relationships between human diseases, genes, proteins, drugs, metabolites, toxins, metabolic pathways, organs, tissues, subcellular organelles, positive health effects, negative health effects, drug actions, Gene Ontology terms, MeSH terms, ICD-10 medical codes, biological taxonomies and chemical taxonomies. PolySearch 2.0 supports a generalized ‘Given X, find all associated Ys’ query, where X and Y can be selected from the aforementioned biomedical entities.

PubMed: 2592557218487273

Coming Soon:  LC AutoFit and Phastest