IDSL.CSA: Composite Spectra Analysis for Chemical Annotation of Untargeted Metabolomics Datasets

Sadjad Fakouri Baygi, Yashwant Kumar, Dinesh Kumar Barupal

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

Poor chemical annotation of high-resolution mass spectrometry data limits applications of untargeted metabolomics datasets. Our new software, the Integrated Data Science Laboratory for Metabolomics and Exposomics─Composite Spectra Analysis (IDSL.CSA) R package, generates composite mass spectra libraries from MS1-only data, enabling the chemical annotation of high-resolution mass spectrometry coupled with liquid chromatography peaks regardless of the availability of MS2 fragmentation spectra. We demonstrate comparable annotation rates for commonly detected endogenous metabolites in human blood samples using IDSL.CSA libraries versus MS/MS libraries in validation tests. IDSL.CSA can create and search composite spectra libraries from any untargeted metabolomics dataset generated using high-resolution mass spectrometry coupled to liquid or gas chromatography instruments. The cross-applicability of these libraries across independent studies may provide access to new biological insights that may be missed due to the lack of MS2 fragmentation data. The IDSL.CSA package is available in the R-CRAN repository at https://cran.r-project.org/package=IDSL.CSA. Detailed documentation and tutorials are provided at https://github.com/idslme/IDSL.CSA.

Original languageEnglish
Pages (from-to)9480-9487
Number of pages8
JournalAnalytical Chemistry
Volume95
Issue number25
DOIs
StatePublished - 27 Jun 2023

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