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metabolomicsR: a streamlined workflow to analyze metabolomic data in R
SUMMARY: metabolomicsR is a streamlined, flexible and user-friendly R package to preprocess, analyze and visualize metabolomic data. metabolomicsR includes comprehensive functionalities for sample and metabolite quality control, outlier detection, missing value imputation, dimensional reduction, bat...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9512519/ https://www.ncbi.nlm.nih.gov/pubmed/36177485 http://dx.doi.org/10.1093/bioadv/vbac067 |
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author | Han, Xikun Liang, Liming |
author_facet | Han, Xikun Liang, Liming |
author_sort | Han, Xikun |
collection | PubMed |
description | SUMMARY: metabolomicsR is a streamlined, flexible and user-friendly R package to preprocess, analyze and visualize metabolomic data. metabolomicsR includes comprehensive functionalities for sample and metabolite quality control, outlier detection, missing value imputation, dimensional reduction, batch effect normalization, data integration, regression, metabolite annotation and visualization of data and results. In this application note, we demonstrate the step-by-step use of the main functions from this package. AVAILABILITY AND IMPLEMENTATION: The metabolomicsR package is available via CRAN and GitHub (https://github.com/XikunHan/metabolomicsR/). A step-by-step online tutorial is available at https://xikunhan.github.io/metabolomicsR/docs/articles/Introduction.html. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics Advances online. |
format | Online Article Text |
id | pubmed-9512519 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-95125192022-09-27 metabolomicsR: a streamlined workflow to analyze metabolomic data in R Han, Xikun Liang, Liming Bioinform Adv Application Note SUMMARY: metabolomicsR is a streamlined, flexible and user-friendly R package to preprocess, analyze and visualize metabolomic data. metabolomicsR includes comprehensive functionalities for sample and metabolite quality control, outlier detection, missing value imputation, dimensional reduction, batch effect normalization, data integration, regression, metabolite annotation and visualization of data and results. In this application note, we demonstrate the step-by-step use of the main functions from this package. AVAILABILITY AND IMPLEMENTATION: The metabolomicsR package is available via CRAN and GitHub (https://github.com/XikunHan/metabolomicsR/). A step-by-step online tutorial is available at https://xikunhan.github.io/metabolomicsR/docs/articles/Introduction.html. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics Advances online. Oxford University Press 2022-09-16 /pmc/articles/PMC9512519/ /pubmed/36177485 http://dx.doi.org/10.1093/bioadv/vbac067 Text en © The Author(s) 2022. Published by Oxford University Press. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Application Note Han, Xikun Liang, Liming metabolomicsR: a streamlined workflow to analyze metabolomic data in R |
title | metabolomicsR: a streamlined workflow to analyze metabolomic data in R |
title_full | metabolomicsR: a streamlined workflow to analyze metabolomic data in R |
title_fullStr | metabolomicsR: a streamlined workflow to analyze metabolomic data in R |
title_full_unstemmed | metabolomicsR: a streamlined workflow to analyze metabolomic data in R |
title_short | metabolomicsR: a streamlined workflow to analyze metabolomic data in R |
title_sort | metabolomicsr: a streamlined workflow to analyze metabolomic data in r |
topic | Application Note |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9512519/ https://www.ncbi.nlm.nih.gov/pubmed/36177485 http://dx.doi.org/10.1093/bioadv/vbac067 |
work_keys_str_mv | AT hanxikun metabolomicsrastreamlinedworkflowtoanalyzemetabolomicdatainr AT liangliming metabolomicsrastreamlinedworkflowtoanalyzemetabolomicdatainr |