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      Using MetaboAnalyst 4.0 for Comprehensive and Integrative Metabolomics Data Analysis

      1 , 2 , 3 , 1 , 4 , 5
      Current Protocols in Bioinformatics
      Wiley

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          MS-DIAL: Data Independent MS/MS Deconvolution for Comprehensive Metabolome Analysis

          Data-independent acquisition (DIA) in liquid chromatography tandem mass spectrometry (LC-MS/MS) provides more comprehensive untargeted acquisition of molecular data. Here we provide an open-source software pipeline, MS-DIAL, to demonstrate how DIA improves simultaneous identification and quantification of small molecules by mass spectral deconvolution. For reversed phase LC-MS/MS, our program with an enriched LipidBlast library identified total 1,023 lipid compounds from nine algal strains to highlight their chemotaxonomic relationships.
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            Is Open Access

            MetaboAnalyst: a web server for metabolomic data analysis and interpretation

            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
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              XCMS Online: a web-based platform to process untargeted metabolomic data.

              Recently, interest in untargeted metabolomics has become prevalent in the general scientific community among an increasing number of investigators. The majority of these investigators, however, do not have the bioinformatic expertise that has been required to process metabolomic data by using command-line driven software programs. Here we introduce a novel platform to process untargeted metabolomic data that uses an intuitive graphical interface and does not require installation or technical expertise. This platform, called XCMS Online, is a web-based version of the widely used XCMS software that allows users to easily upload and process liquid chromatography/mass spectrometry data with only a few mouse clicks. XCMS Online provides a solution for the complete untargeted metabolomic workflow including feature detection, retention time correction, alignment, annotation, statistical analysis, and data visualization. Results can be browsed online in an interactive, customizable table showing statistics, chromatograms, and putative METLIN identities for each metabolite. Additionally, all results and images can be downloaded as zip files for offline analysis and publication. XCMS Online is available at https://xcmsonline.scripps.edu.
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                Author and article information

                Journal
                Current Protocols in Bioinformatics
                Current Protocols in Bioinformatics
                Wiley
                1934-3396
                1934-340X
                September 20 2019
                December 2019
                September 20 2019
                December 2019
                : 68
                : 1
                Affiliations
                [1 ]Institute of ParasitologyMcGill University Sainte‐Anne‐de‐Bellevue Quebec Canada
                [2 ]Department of Computing ScienceUniversity of Alberta Edmonton Alberta Canada
                [3 ]Department of Biological SciencesUniversity of Alberta Edmonton Alberta Canada
                [4 ]Department of Animal SciencesMcGill University Sainte‐Anne‐de‐Bellevue Quebec Canada
                [5 ]Department of Microbiology and ImmunologyMcGill University Montreal Quebec Canada
                Article
                10.1002/cpbi.86
                31756036
                6ffada83-a048-4394-a3cd-95c82cf6b9b1
                © 2019

                http://onlinelibrary.wiley.com/termsAndConditions#vor

                http://doi.wiley.com/10.1002/tdm_license_1.1

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