Cédric Delporte, Marie Tremblay-Franco, Yann Guitton, Cécile Canlet, Ralf J. M. Weber, Helge Hecht, Elliott James Price, Jana Klánová, Charlotte Joly, Céline Dalle, Julien Saint-Vanne, Etienne Thévenot, Isabelle Schmitz, Sylvain Chéreau, Sylvain Dechaumet, Binta Diémé, Franck Giacomoni, Gildas Le Corguillé, Mélanie Pétéra, Florence Souard
{"title":"Workflow4Metabolomics (W4M)：一个用户友好的代谢组学平台，用于分析质谱和核磁共振数据。","authors":"Cédric Delporte, Marie Tremblay-Franco, Yann Guitton, Cécile Canlet, Ralf J. M. Weber, Helge Hecht, Elliott James Price, Jana Klánová, Charlotte Joly, Céline Dalle, Julien Saint-Vanne, Etienne Thévenot, Isabelle Schmitz, Sylvain Chéreau, Sylvain Dechaumet, Binta Diémé, Franck Giacomoni, Gildas Le Corguillé, Mélanie Pétéra, Florence Souard","doi":"10.1002/cpz1.70095","DOIUrl":null,"url":null,"abstract":"<p>Various spectrometric methods can be used to conduct metabolomics studies. Nuclear magnetic resonance (NMR) or mass spectrometry (MS) coupled with separation methods, such as liquid or gas chromatography (LC and GC, respectively), are the most commonly used techniques. Once the raw data have been obtained, the real challenge lies in the bioinformatics required to conduct: (i) data processing (including preprocessing, normalization, and quality control); (ii) statistical analysis for comparative studies (such as univariate and multivariate analyses, including PCA or PLS-DA/OPLS-DA); (iii) annotation of the metabolites of interest; and (iv) interpretation of the relationships between key metabolites and the relevant phenotypes or scientific questions to be addressed. Here, we will introduce and detail a stepwise protocol for use of the Workflow4Metabolomics platform (W4M), which provides user-friendly access to workflows for processing of LC–MS, GC–MS, and NMR data. Those modular and extensible workflows are composed of existing standalone components (e.g., XCMS and CAMERA packages) as well as a suite of complementary W4M-implemented modules. This tool suite is accessible worldwide through a web interface and is hosted on UseGalaxy France. The extensible Virtual Research Environment (VRE) provided offers pre-configured workflows for metabolomics communities (platforms, end users, etc.), as well as possibilities for sharing among users. By providing a consistent ecosystem of tools and workflows through Galaxy, W4M makes it possible to process MS and NMR data from hundreds of samples using an ordinary personal computer, after step-by-step workflow optimization. © 2025 Wiley Periodicals LLC.</p><p><b>Basic Protocol 1</b>: W4M account creation, working history preparation, and data upload</p><p><b>Support Protocol 1</b>: How to prepare an NMR zip file</p><p><b>Support Protocol 2</b>: How to convert MS data from proprietary format to open format</p><p><b>Support Protocol 3</b>: How to get help with W4M (IFB forum) and how to report a problem on the GitHub repository</p><p><b>Basic Protocol 2</b>: LC–MS data processing</p><p><b>Alternate Protocol 1</b>: GC–MS data processing</p><p><b>Alternate Protocol 2</b>: NMR data processing</p><p><b>Basic Protocol 3</b>: Statistical analysis</p><p><b>Basic Protocol 4</b>: Annotation of metabolites from LC–MS data</p><p><b>Alternate Protocol 3</b>: Annotation of metabolites from NMR data</p>","PeriodicalId":93970,"journal":{"name":"Current protocols","volume":"5 2","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2025-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Workflow4Metabolomics (W4M): A User-Friendly Metabolomics Platform for Analysis of Mass Spectrometry and Nuclear Magnetic Resonance Data\",\"authors\":\"Cédric Delporte, Marie Tremblay-Franco, Yann Guitton, Cécile Canlet, Ralf J. M. Weber, Helge Hecht, Elliott James Price, Jana Klánová, Charlotte Joly, Céline Dalle, Julien Saint-Vanne, Etienne Thévenot, Isabelle Schmitz, Sylvain Chéreau, Sylvain Dechaumet, Binta Diémé, Franck Giacomoni, Gildas Le Corguillé, Mélanie Pétéra, Florence Souard\",\"doi\":\"10.1002/cpz1.70095\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>Various spectrometric methods can be used to conduct metabolomics studies. Nuclear magnetic resonance (NMR) or mass spectrometry (MS) coupled with separation methods, such as liquid or gas chromatography (LC and GC, respectively), are the most commonly used techniques. Once the raw data have been obtained, the real challenge lies in the bioinformatics required to conduct: (i) data processing (including preprocessing, normalization, and quality control); (ii) statistical analysis for comparative studies (such as univariate and multivariate analyses, including PCA or PLS-DA/OPLS-DA); (iii) annotation of the metabolites of interest; and (iv) interpretation of the relationships between key metabolites and the relevant phenotypes or scientific questions to be addressed. Here, we will introduce and detail a stepwise protocol for use of the Workflow4Metabolomics platform (W4M), which provides user-friendly access to workflows for processing of LC–MS, GC–MS, and NMR data. Those modular and extensible workflows are composed of existing standalone components (e.g., XCMS and CAMERA packages) as well as a suite of complementary W4M-implemented modules. This tool suite is accessible worldwide through a web interface and is hosted on UseGalaxy France. The extensible Virtual Research Environment (VRE) provided offers pre-configured workflows for metabolomics communities (platforms, end users, etc.), as well as possibilities for sharing among users. By providing a consistent ecosystem of tools and workflows through Galaxy, W4M makes it possible to process MS and NMR data from hundreds of samples using an ordinary personal computer, after step-by-step workflow optimization. © 2025 Wiley Periodicals LLC.</p><p><b>Basic Protocol 1</b>: W4M account creation, working history preparation, and data upload</p><p><b>Support Protocol 1</b>: How to prepare an NMR zip file</p><p><b>Support Protocol 2</b>: How to convert MS data from proprietary format to open format</p><p><b>Support Protocol 3</b>: How to get help with W4M (IFB forum) and how to report a problem on the GitHub repository</p><p><b>Basic Protocol 2</b>: LC–MS data processing</p><p><b>Alternate Protocol 1</b>: GC–MS data processing</p><p><b>Alternate Protocol 2</b>: NMR data processing</p><p><b>Basic Protocol 3</b>: Statistical analysis</p><p><b>Basic Protocol 4</b>: Annotation of metabolites from LC–MS data</p><p><b>Alternate Protocol 3</b>: Annotation of metabolites from NMR data</p>\",\"PeriodicalId\":93970,\"journal\":{\"name\":\"Current protocols\",\"volume\":\"5 2\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2025-02-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Current protocols\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1002/cpz1.70095\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Current protocols","FirstCategoryId":"1085","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/cpz1.70095","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Workflow4Metabolomics (W4M): A User-Friendly Metabolomics Platform for Analysis of Mass Spectrometry and Nuclear Magnetic Resonance Data
Various spectrometric methods can be used to conduct metabolomics studies. Nuclear magnetic resonance (NMR) or mass spectrometry (MS) coupled with separation methods, such as liquid or gas chromatography (LC and GC, respectively), are the most commonly used techniques. Once the raw data have been obtained, the real challenge lies in the bioinformatics required to conduct: (i) data processing (including preprocessing, normalization, and quality control); (ii) statistical analysis for comparative studies (such as univariate and multivariate analyses, including PCA or PLS-DA/OPLS-DA); (iii) annotation of the metabolites of interest; and (iv) interpretation of the relationships between key metabolites and the relevant phenotypes or scientific questions to be addressed. Here, we will introduce and detail a stepwise protocol for use of the Workflow4Metabolomics platform (W4M), which provides user-friendly access to workflows for processing of LC–MS, GC–MS, and NMR data. Those modular and extensible workflows are composed of existing standalone components (e.g., XCMS and CAMERA packages) as well as a suite of complementary W4M-implemented modules. This tool suite is accessible worldwide through a web interface and is hosted on UseGalaxy France. The extensible Virtual Research Environment (VRE) provided offers pre-configured workflows for metabolomics communities (platforms, end users, etc.), as well as possibilities for sharing among users. By providing a consistent ecosystem of tools and workflows through Galaxy, W4M makes it possible to process MS and NMR data from hundreds of samples using an ordinary personal computer, after step-by-step workflow optimization. © 2025 Wiley Periodicals LLC.
Basic Protocol 1: W4M account creation, working history preparation, and data upload
Support Protocol 1: How to prepare an NMR zip file
Support Protocol 2: How to convert MS data from proprietary format to open format
Support Protocol 3: How to get help with W4M (IFB forum) and how to report a problem on the GitHub repository
Basic Protocol 2: LC–MS data processing
Alternate Protocol 1: GC–MS data processing
Alternate Protocol 2: NMR data processing
Basic Protocol 3: Statistical analysis
Basic Protocol 4: Annotation of metabolites from LC–MS data
Alternate Protocol 3: Annotation of metabolites from NMR data
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号
