POMAShiny: A user-friendly web-based workflow for metabolomics and proteomics data analysis.
Metabolomics and proteomics, like other omics domains, usually face a data mining challenge in providing an understandable output to advance in biomarker discovery and precision medicine. Often, statistical analysis is one of the most difficult challenges and it is critical in the subsequent biologi...
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2021
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oai:doaj.org-article:a39dc8f8b40342da819d099c2c2730712021-12-02T19:57:35ZPOMAShiny: A user-friendly web-based workflow for metabolomics and proteomics data analysis.1553-734X1553-735810.1371/journal.pcbi.1009148https://doaj.org/article/a39dc8f8b40342da819d099c2c2730712021-07-01T00:00:00Zhttps://doi.org/10.1371/journal.pcbi.1009148https://doaj.org/toc/1553-734Xhttps://doaj.org/toc/1553-7358Metabolomics and proteomics, like other omics domains, usually face a data mining challenge in providing an understandable output to advance in biomarker discovery and precision medicine. Often, statistical analysis is one of the most difficult challenges and it is critical in the subsequent biological interpretation of the results. Because of this, combined with the computational programming skills needed for this type of analysis, several bioinformatic tools aimed at simplifying metabolomics and proteomics data analysis have emerged. However, sometimes the analysis is still limited to a few hidebound statistical methods and to data sets with limited flexibility. POMAShiny is a web-based tool that provides a structured, flexible and user-friendly workflow for the visualization, exploration and statistical analysis of metabolomics and proteomics data. This tool integrates several statistical methods, some of them widely used in other types of omics, and it is based on the POMA R/Bioconductor package, which increases the reproducibility and flexibility of analyses outside the web environment. POMAShiny and POMA are both freely available at https://github.com/nutrimetabolomics/POMAShiny and https://github.com/nutrimetabolomics/POMA, respectively.Pol Castellano-EscuderRaúl González-DomínguezFrancesc Carmona-PontaqueCristina Andrés-LacuevaAlex Sánchez-PlaPublic Library of Science (PLoS)articleBiology (General)QH301-705.5ENPLoS Computational Biology, Vol 17, Iss 7, p e1009148 (2021) |
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Biology (General) QH301-705.5 |
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Biology (General) QH301-705.5 Pol Castellano-Escuder Raúl González-Domínguez Francesc Carmona-Pontaque Cristina Andrés-Lacueva Alex Sánchez-Pla POMAShiny: A user-friendly web-based workflow for metabolomics and proteomics data analysis. |
| description |
Metabolomics and proteomics, like other omics domains, usually face a data mining challenge in providing an understandable output to advance in biomarker discovery and precision medicine. Often, statistical analysis is one of the most difficult challenges and it is critical in the subsequent biological interpretation of the results. Because of this, combined with the computational programming skills needed for this type of analysis, several bioinformatic tools aimed at simplifying metabolomics and proteomics data analysis have emerged. However, sometimes the analysis is still limited to a few hidebound statistical methods and to data sets with limited flexibility. POMAShiny is a web-based tool that provides a structured, flexible and user-friendly workflow for the visualization, exploration and statistical analysis of metabolomics and proteomics data. This tool integrates several statistical methods, some of them widely used in other types of omics, and it is based on the POMA R/Bioconductor package, which increases the reproducibility and flexibility of analyses outside the web environment. POMAShiny and POMA are both freely available at https://github.com/nutrimetabolomics/POMAShiny and https://github.com/nutrimetabolomics/POMA, respectively. |
| format |
article |
| author |
Pol Castellano-Escuder Raúl González-Domínguez Francesc Carmona-Pontaque Cristina Andrés-Lacueva Alex Sánchez-Pla |
| author_facet |
Pol Castellano-Escuder Raúl González-Domínguez Francesc Carmona-Pontaque Cristina Andrés-Lacueva Alex Sánchez-Pla |
| author_sort |
Pol Castellano-Escuder |
| title |
POMAShiny: A user-friendly web-based workflow for metabolomics and proteomics data analysis. |
| title_short |
POMAShiny: A user-friendly web-based workflow for metabolomics and proteomics data analysis. |
| title_full |
POMAShiny: A user-friendly web-based workflow for metabolomics and proteomics data analysis. |
| title_fullStr |
POMAShiny: A user-friendly web-based workflow for metabolomics and proteomics data analysis. |
| title_full_unstemmed |
POMAShiny: A user-friendly web-based workflow for metabolomics and proteomics data analysis. |
| title_sort |
pomashiny: a user-friendly web-based workflow for metabolomics and proteomics data analysis. |
| publisher |
Public Library of Science (PLoS) |
| publishDate |
2021 |
| url |
https://doaj.org/article/a39dc8f8b40342da819d099c2c273071 |
| work_keys_str_mv |
AT polcastellanoescuder pomashinyauserfriendlywebbasedworkflowformetabolomicsandproteomicsdataanalysis AT raulgonzalezdominguez pomashinyauserfriendlywebbasedworkflowformetabolomicsandproteomicsdataanalysis AT francesccarmonapontaque pomashinyauserfriendlywebbasedworkflowformetabolomicsandproteomicsdataanalysis AT cristinaandreslacueva pomashinyauserfriendlywebbasedworkflowformetabolomicsandproteomicsdataanalysis AT alexsanchezpla pomashinyauserfriendlywebbasedworkflowformetabolomicsandproteomicsdataanalysis |
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