MetaboAnalyst 2.0—a comprehensive server for metabolomic data analysis

First released in 2009, MetaboAnalyst (www.metaboanalyst.ca) was a relatively simple web server designed to facilitate metabolomic data processing and statistical analysis. With continuing advances in metabolomics along with constant user feedback, it became clear that a substantial upgrade to the original server was necessary. MetaboAnalyst 2.0, which is the successor to MetaboAnalyst, represents just such an upgrade. MetaboAnalyst 2.0 now contains dozens of new features and functions including new procedures for data filtering, data editing and data normalization. It also supports multi-group data analysis, two-factor analysis as well as time-series data analysis. These new functions have also been supplemented with: (i) a quality-control module that allows users to evaluate their data quality before conducting any analysis, (ii) a functional enrichment analysis module that allows users to identify biologically meaningful patterns using metabolite set enrichment analysis and (iii) a metabolic pathway analysis module that allows users to perform pathway analysis and visualization for 15 different model organisms. In developing MetaboAnalyst 2.0 we have also substantially improved its graphical presentation tools. All images are now generated using anti-aliasing and are available over a range of resolutions, sizes and formats (PNG, TIFF, PDF, PostScript, or SVG). To improve its performance, MetaboAnalyst 2.0 is now hosted on a much more powerful server with substantially modified code to take advantage the server’s multi-core CPUs for computationally intensive tasks. MetaboAnalyst 2.0 also maintains a collection of 50 or more FAQs and more than a dozen tutorials compiled from user queries and requests. A downloadable version of MetaboAnalyst 2.0, along detailed instructions for local installation is now available as well.

[1]  Erin E. Carlson,et al.  Targeted profiling: quantitative analysis of 1H NMR metabolomics data. , 2006, Analytical chemistry.

[2]  P. Pavlidis.  Using ANOVA for gene selection from microarray studies of the nervous system. , 2003, Methods.

[3]  H. Senn,et al.  Probabilistic quotient normalization as robust method to account for dilution of complex biological mixtures. Application in 1H NMR metabonomics. , 2006, Analytical chemistry.

[4]  Jens O Krömer,et al.  Towards quantitative metabolomics of mammalian cells: development of a metabolite extraction protocol. , 2010, Analytical biochemistry.

[5]  Gabi Kastenmüller,et al.  metaP-Server: A Web-Based Metabolomics Data Analysis Tool , 2010, Journal of biomedicine & biotechnology.

[6]  Age K. Smilde,et al.  ANOVA-simultaneous component analysis (ASCA): a new tool for analyzing designed metabolomics data , 2005, Bioinform..

[7]  David S. Wishart,et al.  Bioinformatics Applications Note Systems Biology Metatt: a Web-based Metabolomics Tool for Analyzing Time-series and Two-factor Datasets , 2022 .

[8]  David S. Wishart,et al.  HMDB: a knowledgebase for the human metabolome , 2008, Nucleic Acids Res..

[9]  Jing Gao,et al.  Metscape: a Cytoscape plug-in for visualizing and interpreting metabolomic data in the context of human metabolic networks , 2010, Bioinform..

[10]  Jelle J. Goeman,et al.  A global test for groups of genes: testing association with a clinical outcome , 2004, Bioinform..

[11]  A. Smilde,et al.  Large-scale human metabolomics studies: a strategy for data (pre-) processing and validation. , 2006, Analytical chemistry.

[12]  Pablo Tamayo,et al.  Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles , 2005, Proceedings of the National Academy of Sciences of the United States of America.

[13]  Jianguo Xia,et al.  Metabolomic Data Processing, Analysis, and Interpretation Using MetaboAnalyst , 2011, Current protocols in bioinformatics.

[14]  Ann M. Hess,et al.  which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Filtering for increased power for microarray data analysis , 2008 .

[15]  David S. Wishart,et al.  MetaboAnalyst: a web server for metabolomic data analysis and interpretation , 2009, Nucleic Acids Res..

[16]  David S. Wishart,et al.  SMPDB: The Small Molecule Pathway Database , 2009, Nucleic Acids Res..

[17]  Tao Wang,et al.  Automics: an integrated platform for NMR-based metabonomics spectral processing and data analysis , 2009, BMC Bioinformatics.

[18]  David S. Wishart,et al.  MSEA: a web-based tool to identify biologically meaningful patterns in quantitative metabolomic data , 2010, Nucleic Acids Res..

[19]  A. Harvey Millar,et al.  The MetabolomeExpress Project: enabling web-based processing, analysis and transparent dissemination of GC/MS metabolomics datasets , 2010, BMC Bioinformatics.

[20]  Terence P. Speed,et al.  On Gene Ranking Using Replicated Microarray Time Course Data , 2009, Biometrics.

[21]  Jianguo Xia,et al.  Web-based inference of biological patterns, functions and pathways from metabolomic data using MetaboAnalyst , 2011, Nature Protocols.

[22]  Joaquín Dopazo,et al.  GEPAS: a web-based resource for microarray gene expression data analysis , 2003, Nucleic Acids Res..

[23]  David S. Wishart,et al.  Bioinformatics Applications Note Systems Biology Metpa: a Web-based Metabolomics Tool for Pathway Analysis and Visualization , 2022 .

[24]  Macha Nikolski,et al.  MeRy-B: a web knowledgebase for the storage, visualization, analysis and annotation of plant NMR metabolomic profiles , 2011, BMC Plant Biology.

[25]  Yuqin Wang,et al.  Targeted metabolomics for biomarker discovery. , 2010, Angewandte Chemie.

[26]  Nicola Zamboni,et al.  High-throughput quantitative metabolomics: workflow for cultivation, quenching, and analysis of yeast in a multiwell format. , 2009, Analytical chemistry.

[27]  R. Tibshirani,et al.  Significance analysis of microarrays applied to the ionizing radiation response , 2001, Proceedings of the National Academy of Sciences of the United States of America.

[28]  Jens Stoye,et al.  MeltDB: a software platform for the analysis and integration of metabolomics experiment data , 2008, Bioinform..

[29]  R. Gentleman,et al.  Independent filtering increases detection power for high-throughput experiments , 2010, Proceedings of the National Academy of Sciences.

[30]  Age K. Smilde,et al.  UvA-DARE ( Digital Academic Repository ) Assessment of PLSDA cross validation , 2008 .

[31]  J. Mesirov,et al.  GenePattern 2.0 , 2006, Nature Genetics.

[32]  R. A. van den Berg,et al.  Centering, scaling, and transformations: improving the biological information content of metabolomics data , 2006, BMC Genomics.

[33]  Joshua D. Knowles,et al.  Procedures for large-scale metabolic profiling of serum and plasma using gas chromatography and liquid chromatography coupled to mass spectrometry , 2011, Nature Protocols.

[34]  Age K Smilde,et al.  Analyzing longitudinal microbial metabolomics data. , 2009, Journal of proteome research.