Web Servers & Data Analysis
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: 25897128, 27603023, 22553367, 21637195, 21633943, 19429898, 30909447, 29955821, 29762782
CFM-ID 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: 24895432, 27381172, 31013937
References: Metabolomics 2015 Feb; 11(1): 98–110.
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.
GC-AutoFit 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.
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.
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.
MetPA (Metabolomics Pathway Analysis) is a free and easy-to-use web application designed to perform pathway analysis and visualization of quantitative metabolomic data.
Receiver Operating Characteristic (ROC) curves are generally considered the method of choice for evaluating the performance of potential biomarkers. 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.
MetaboMiner is a program which can be used to automatically or semi-automatically identify metabolites in complex biofluids from 2D NMR spectra. MetaboMiner is able to handle both 1H-1H total correlation spectroscopy (TOCSY) and 1H-13C heteronuclear single quantum correlation (HSQC) data. It identifies compounds by comparing 2D spectral patterns in the NMR spectrum of the biofluid mixture with specially constructed libraries containing reference spectra of approximately 500 pure compounds. Tests using a variety of synthetic and real spectra of compound mixtures showed that MetaboMiner is able to identify >80% of detectable metabolites from good quality NMR spectra.
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:
- expression-based heat maps from transcriptomic, proteomic and metabolomic experiments
- pairwise distance maps
- correlation maps
- image overlay heat maps
- latitude and longitude heat maps and
- geopolitical (choropleth) heat maps.
Heatmapper offers a number of simple and intuitive customization options for easy adjustments to each heat map’s appearance and plotting parameters.
BioTransformer 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.
The COVIDmapper project is designed to provide geopolitical heatmaps showing the progression of COVID-19 spatially and temporally. COVIDmapper uses the Heatmapper platform and spatio-temporal COVID data collected from the WHO, Johns Hopkins University, and a number of regional health centres from around the world (1,2). It also employs modeled data from reported and existing epidemiological trend data to predict future COVID trends (). Data for COVIDmapper is updated daily at 0:00 GMT.
Using a simple pull-down menu, users can display COVID-19 heatmaps for different geographic levels: 1) the world, 2) continents, 3) individual countries, and 4) states or provinces. Data on the reported number of COVID cases, reported number of COVID deaths, reported per capita cases, reported per capita deaths, “real” number of cases (using 3 different case fatality rate models) and reported COVID tests can be easily displayed using COVIDmapper’s simple pull-down menu. Users may select any date to explore previous COVID statistics or any future date (based on modeled projections) to explore projected COVID statistics for different regions. Tables for all data in COVIDmapper (at the state, country, continent, or global level) are viewable as tables and can be freely downloaded. All maps are interactively zoomable and exact values are interactively displayed over each map by hovering over a region of interest. The intensity (opacity) of the heatmaps can be adjusted to display more (or less) of a country’s geography.
*The management and development of these resources was initially done under the auspices of the Bioinformatics Help Desk (a Genome Canada funded core facility) and the Human Metabolome Project from 2006-2010 but it is now handled through the support of TMIC and CIHR.