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...

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Main Authors: Sara A. Yones, Rajmund Csombordi, Jan Komorowski, Klev Diamanti
Format: Article
Language:English
Published: MDPI AG 2021-10-01
Series:Metabolites
Subjects:
Online Access:https://www.mdpi.com/2218-1989/11/11/743
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author Sara A. Yones
Rajmund Csombordi
Jan Komorowski
Klev Diamanti
author_facet Sara A. Yones
Rajmund Csombordi
Jan Komorowski
Klev Diamanti
author_sort Sara A. Yones
collection DOAJ
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.
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spelling doaj.art-73fdb4b1d34945649c5cff5865efa0252023-11-23T00:20:53ZengMDPI AGMetabolites2218-19892021-10-01111174310.3390/metabo11110743MetaFetcheR: An R Package for Complete Mapping of Small-Compound DataSara A. Yones0Rajmund Csombordi1Jan Komorowski2Klev Diamanti3Department of Cellular and Molecular Biology, Uppsala University, 751 24 Uppsala, SwedenDepartment of Cellular and Molecular Biology, Uppsala University, 751 24 Uppsala, SwedenDepartment of Cellular and Molecular Biology, Uppsala University, 751 24 Uppsala, SwedenDepartment of Cellular and Molecular Biology, Uppsala University, 751 24 Uppsala, SwedenSmall-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.https://www.mdpi.com/2218-1989/11/11/743small-compound databasesmetabolomicsmetabolitesqueue-based algorithm
spellingShingle Sara A. Yones
Rajmund Csombordi
Jan Komorowski
Klev Diamanti
MetaFetcheR: An R Package for Complete Mapping of Small-Compound Data
Metabolites
small-compound databases
metabolomics
metabolites
queue-based algorithm
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 small-compound databases
metabolomics
metabolites
queue-based algorithm
url https://www.mdpi.com/2218-1989/11/11/743
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