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Dataset of "A Metabolites Merging Strategy (MMS): Harmonization to enable studies intercomparison" - MaRDI portal

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Dataset of "A Metabolites Merging Strategy (MMS): Harmonization to enable studies intercomparison"

From MaRDI portal
(Redirected from Dataset:6690710)



DOI10.5281/zenodo.8226097Zenodo8226097MaRDI QIDQ6690710

Dataset published at Zenodo repository.

Author name not available (Why is that?)

Publication date: 17 August 2023



Description

Metabolomics encounters challenges in cross-study comparisons due to diverse metabolite nomenclature and reporting practices. To bridge this gap, we introduce the Metabolites Merging Strategy (MMS), offering a systematic framework to harmonize multiple metabolite datasets for enhanced interstudy comparability. MMS has three steps. Step 1: Translation and merging of the different datasets by employing InChIKeys for data integration, encompassing the translation of metabolite names (if needed). Followed by Step 2: Attributes' retrieval from the InChIkey, including descriptors of name (title name from PubChem and RefMet name from Metabolomics Workbench), and chemical properties (molecular weight and molecular formula), both systematic (InChI, InChIKey, SMILES) and non-systematic identifiers (PubChem, CheBI, HMDB, KEGG, LipidMaps, DrugBank, Bin ID and CAS number), and their ontology. Finally, a meticulous three-step curation process is used to rectify disparities for conjugated base/acid compounds (optional step), missing attributes, and synonym checking (duplicated information). The MMS procedure is exemplified through a case study of urinary asthma metabolites, where MMS facilitated the identification of significant pathways hidden when no dataset merging strategy was followed. This study highlights the need for standardized and unified metabolite datasets to enhance the reproducibility and comparability of metabolomics studies.






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