{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Baygi SF"],"funding":["National Institute of Environmental Health Sciences","National Center for Advancing Translational Sciences","NCATS NIH HHS","NIEHS NIH HHS"],"pagination":["13315-13322"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC9682628"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["94(39)"],"pubmed_abstract":["Untargeted liquid chromatography/high-resolution mass spectrometry (LC/HRMS) assays in metabolomics and exposomics aim to characterize the small molecule chemical space in a biospecimen. To gain maximum biological insights from these data sets, LC/HRMS peaks should be annotated with chemical and functional information including molecular formula, structure, chemical class, and metabolic pathways. Among these, molecular formulas may be assigned to LC/HRMS peaks through matching theoretical and observed isotopic profiles (MS1) of the underlying ionized compound. For this, we have developed the Integrated Data Science Laboratory for Metabolomics and Exposomics-United Formula Annotation (IDSL.UFA) R package. In the untargeted metabolomics validation tests, IDSL.UFA assigned 54.31-85.51% molecu"],"journal":["Analytical chemistry"],"pubmed_title":["IDSL.UFA Assigns High-Confidence Molecular Formula Annotations for Untargeted LC/HRMS Data Sets in Metabolomics and Exposomics."],"pmcid":["PMC9682628"],"funding_grant_id":["UL1TR001433","U2C ES026561","UL1 TR001433","P30ES023515","U2C ES030859","R01 ES032831","UL1 TR004419","R01ES032831","U2C ES026555","P30 ES023515","U2CES030859","U2CES026561","U2CES026555","UL1TR004419"],"pubmed_authors":["Banerjee SK","Kumar Y","Baygi SF","Chakraborty P","Barupal DK"],"additional_accession":[]},"is_claimable":false,"name":"IDSL.UFA Assigns High-Confidence Molecular Formula Annotations for Untargeted LC/HRMS Data Sets in Metabolomics and Exposomics.","description":"Untargeted liquid chromatography/high-resolution mass spectrometry (LC/HRMS) assays in metabolomics and exposomics aim to characterize the small molecule chemical space in a biospecimen. To gain maximum biological insights from these data sets, LC/HRMS peaks should be annotated with chemical and functional information including molecular formula, structure, chemical class, and metabolic pathways. Among these, molecular formulas may be assigned to LC/HRMS peaks through matching theoretical and observed isotopic profiles (MS1) of the underlying ionized compound. For this, we have developed the Integrated Data Science Laboratory for Metabolomics and Exposomics-United Formula Annotation (IDSL.UFA) R package. In the untargeted metabolomics validation tests, IDSL.UFA assigned 54.31-85.51% molecu","dates":{"release":"2022-01-01T00:00:00Z","publication":"2022 Oct","modification":"2025-04-18T14:59:06.616Z","creation":"2025-02-19T03:59:22.889Z"},"accession":"S-EPMC9682628","cross_references":{"pubmed":["36137231"],"doi":["10.1021/acs.analchem.2c00563"]}}