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Updated: Oct 12, 2025

An Integrated Workflow of Identification and Quantification on FDR Control-Based Untargeted Metabolome
Published on: September 20, 2022
MetaFetcheR: An R Package for Complete Mapping of Small-Compound Data
Sara A Yones1, Rajmund Csombordi1, Jan Komorowski1,2,3,4
1Department of Cellular and Molecular Biology, Uppsala University, 751 24 Uppsala, Sweden.
Abstract:
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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