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MetaFetcheR: An R Package for Complete Mapping of Small-Compound Data
Small-compound databases contain a large amount of information for metabolites and metabolic pathways. However, the plethora of such databases and the redundancy of their information lead to major issues with analysis and standardization. A lack of preventive establishment of means of data access at...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8620779/ https://www.ncbi.nlm.nih.gov/pubmed/34822401 http://dx.doi.org/10.3390/metabo11110743 |
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author | Yones, Sara A. Csombordi, Rajmund Komorowski, Jan Diamanti, Klev |
author_facet | Yones, Sara A. Csombordi, Rajmund Komorowski, Jan Diamanti, Klev |
author_sort | Yones, Sara A. |
collection | PubMed |
description | Small-compound databases contain a large amount of information for metabolites and metabolic pathways. However, the plethora of such databases and the redundancy of their information lead to major issues with analysis and standardization. A lack of preventive establishment of means of data access at the infant stages of a project might lead to mislabelled compounds, reduced statistical power, and large delays in delivery of results. We developed MetaFetcheR, an open-source R package that links metabolite data from several small-compound databases, resolves inconsistencies, and covers a variety of use-cases of data fetching. We showed that the performance of MetaFetcheR was superior to existing approaches and databases by benchmarking the performance of the algorithm in three independent case studies based on two published datasets. |
format | Online Article Text |
id | pubmed-8620779 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-86207792021-11-27 MetaFetcheR: An R Package for Complete Mapping of Small-Compound Data Yones, Sara A. Csombordi, Rajmund Komorowski, Jan Diamanti, Klev Metabolites Article Small-compound databases contain a large amount of information for metabolites and metabolic pathways. However, the plethora of such databases and the redundancy of their information lead to major issues with analysis and standardization. A lack of preventive establishment of means of data access at the infant stages of a project might lead to mislabelled compounds, reduced statistical power, and large delays in delivery of results. We developed MetaFetcheR, an open-source R package that links metabolite data from several small-compound databases, resolves inconsistencies, and covers a variety of use-cases of data fetching. We showed that the performance of MetaFetcheR was superior to existing approaches and databases by benchmarking the performance of the algorithm in three independent case studies based on two published datasets. MDPI 2021-10-28 /pmc/articles/PMC8620779/ /pubmed/34822401 http://dx.doi.org/10.3390/metabo11110743 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Yones, Sara A. Csombordi, Rajmund Komorowski, Jan Diamanti, Klev MetaFetcheR: An R Package for Complete Mapping of Small-Compound Data |
title | MetaFetcheR: An R Package for Complete Mapping of Small-Compound Data |
title_full | MetaFetcheR: An R Package for Complete Mapping of Small-Compound Data |
title_fullStr | MetaFetcheR: An R Package for Complete Mapping of Small-Compound Data |
title_full_unstemmed | MetaFetcheR: An R Package for Complete Mapping of Small-Compound Data |
title_short | MetaFetcheR: An R Package for Complete Mapping of Small-Compound Data |
title_sort | metafetcher: an r package for complete mapping of small-compound data |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8620779/ https://www.ncbi.nlm.nih.gov/pubmed/34822401 http://dx.doi.org/10.3390/metabo11110743 |
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