MetaboAnalyst: a web server for metabolomic data analysis and interpretation

By Jianguo Xia, Nick Psychogios, Nelson Young, David S. Wishart. Nucleic Acids Res., 2009

2,093 citations recorded by the source corpus.

Metabolomics is a newly emerging field of ‘omics’ research that is concerned with characterizing large numbers of metabolites using NMR, chromatography and mass spectrometry. It is frequently used in biomarker identification and the metabolic profiling of cells, tissues or organisms. The data processing challenges in metabolomics are quite unique and often require specialized (or expensive) data analysis software and a detailed knowledge of cheminformatics, bioinformatics and statistics. In an effort to simplify metabolomic data analysis while at the same time improving user accessibility, we have developed a freely accessible, easy-to-use web server for metabolomic data analysis called MetaboAnalyst. Fundamentally, MetaboAnalyst is a web-based metabolomic data processing tool not unlike many of today's web-based microarray analysis packages. It accepts a variety of input data (NMR peak lists, binned spectra, MS peak lists, compound/concentration data) in a wide variety of formats. It also offers a number of options for metabolomic data processing, data normalization, multivariate statistical analysis, graphing, metabolite identification and pathway mapping. In particular, MetaboAnalyst supports such techniques as: fold change analysis, t-tests, PCA, PLS-DA, hierarchical clustering and a number of more sophisticated statistical or machine learning methods. It also employs a large library of reference spectra to facilitate compound identification from most kinds of input spectra. MetaboAnalyst guides users through a step-by-step analysis pipeline using a variety of menus, information hyperlinks and check boxes. Upon completion, the server generates a detailed report describing each method used, embedded with graphical and tabular outputs. MetaboAnalyst is capable of handling most kinds of metabolomic data and was designed to perform most of the common kinds of metabolomic data analyses. MetaboAnalyst is accessible at http://www.metaboanalyst.ca

Subfields: Biomedical Engineering, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/94549a171a61039ed1f9b5954ce42181c574ccc3

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Biomedical Engineering

In Molecular Biology

Citations in the corpus

A tutorial review: Metabolomics and partial least squares-discriminant analysis--a marriage of convenience or a shotgun wedding. (2015, methodology): “The increasing interest in PLS-DA, especially in the field of metabolomics, is mainly due to its availability in most of the common statistical software packages such as: R, S-Plus, SAS, SPSS, MATLAB [7–13].”
METAGENassist: a comprehensive web server for comparative metagenomics (2012, methodology): “The phenotype database is largely built from the annotations found in BacMap (12,13), an up-to-date electronic atlas of over 1700 annotated prokaryotic genomes and expanded or extrapolated to include other species through extensive text mining and intelligent inference by taxonomic relationships.”
MetaboAnalyst 5.0: narrowing the gap between raw spectra and functional insights (2021, background): “0) of MetaboAnalyst was introduced over a decade ago, focusing on data normalization and statistical analysis (11).”
Using MetaboAnalyst 3.0 for Comprehensive Metabolomics Data Analysis (2016, methodology): “In developing MetaboAnalyst we liberally borrowed many of the ideas and data-processing tools originally developed for microarray analysis and adopted them to the specific needs or requirements of metabolomic data (Xia et al., 2009).”
Glycolysis-mediated changes in acetyl-CoA and histone acetylation control the early differentiation of embryonic stem cells. (2015, methodology): “NMR spectral bins were analyzed using MetaboAnalyst 2.0 (Xia et al., 2009).”
MetaboAnalyst 2.0—a comprehensive server for metabolomic data analysis (2012, neutral): “It was originally released in 2009 (1).”
Metabolomics in pesticide research and development: review and future perspectives (2011, neutral): “…Suhre and Schmitt-Kopplin (2008) MathDAMP http://mathdamp.iab.keio.ac.jp/ Baran et al. (2006) Metaboanalyst http://www.metaboanalyst.ca Xia et al. (2009) MetHouse http://msbi.ipb-halle.de/msbi/metware/methouse Gaida and Neumann (2007) MET-IDEA…”
Web-based inference of biological patterns, functions and pathways from metabolomic data using MetaboAnalyst (2011, background): “In response to this trend toward quantitative metabolomics, as well as the growing community shift toward using open-access, web-based tools in many 'omics' applications, we have developed a web-based software tool called MetaboAnalys”
Using MetaboAnalyst 4.0 for Comprehensive and Integrative Metabolomics Data Analysis (2019, background): “In developing MetaboAnalyst, many of the ideas and data processing strategies originally developed for microarray analysis were liberally borrowed and adopted to fit the specific needs or requirements of metabolomic data (Xia et al., 2009).”
Double-check: validation of diagnostic statistics for PLS-DA models in metabolomics studies (2011, neutral): “2.1 PLS-DA modeling with a double-cross validation scheme”
MSEA: a web-based tool to identify biologically meaningful patterns in quantitative metabolomic data (2010, methodology): “Many commonly used feature selection and feature clustering methods are available from our companion web application MetaboAnalyst (32).”
MetPA: a web-based metabolomics tool for pathway analysis and visualization (2010, background): “The current library contains 874 metabolic pathways from 11 model organisms including humans, mouse, Drosophila, Arabidopsis, Escherichia coli, etc. Metabolic pathways are presented as a network of chemical compounds with metabolites as nodes and reactions as edges.”