IDSL CSA

IDSL CSA generates composite mass spectra libraries from MS1-only high-resolution mass spectrometry data coupled to liquid or gas chromatography to enable chemical annotation in untargeted metabolomics and exposomics.


Key Features:

  • Composite spectra generation: Creates composite mass spectra libraries exclusively from MS1-only data to represent chromatographic peaks without requiring MS2 fragmentation spectra.
  • MS1-based library search: Enables searches for liquid chromatography peaks using MS1-derived composite spectra instead of MS2 spectra.
  • High-resolution MS support: Operates on datasets generated by high-resolution mass spectrometry coupled to liquid chromatography or gas chromatography.
  • Validation on human samples: Demonstrated comparable annotation rates for commonly detected endogenous metabolites in validation tests using human blood samples.
  • Implementation: Provided as an R package (IDSL.CSA) for computational integration into data analysis workflows.

Scientific Applications:

  • Chemical annotation in untargeted metabolomics: Supports metabolite identification when MS2 fragmentation data are unavailable or incomplete.
  • Exposomics studies: Facilitates annotation of exogenous and endogenous compounds in exposomics datasets derived from LC- or GC-coupled high-resolution MS.
  • Cross-study spectral library use: Enables creation and reuse of composite spectra libraries across different untargeted metabolomics datasets and instrument setups.
  • Biological validation: Applicable to annotation and discovery efforts in human blood metabolomics as demonstrated in validation tests.

Methodology:

Generates composite mass spectra libraries from MS1-only high-resolution mass spectrometry data and performs MS1-based library searches for liquid chromatography peaks; implemented as an R package (IDSL.CSA).

Topics

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Details

License:
MIT
Cost:
Free of charge
Tool Type:
library
Operating Systems:
Mac, Linux, Windows
Programming Languages:
R
Added:
8/7/2023
Last Updated:
11/24/2024

Operations

Data Inputs & Outputs

Publications

Baygi SF, Kumar Y, Barupal DK. IDSL.CSA: Composite Spectra Analysis for Chemical Annotation of Untargeted Metabolomics Datasets. Analytical Chemistry. 2023;95(25):9480-9487. doi:10.1021/acs.analchem.3c00376. PMID:37311059. PMCID:PMC11080491.

PMID: 37311059
Funding: - National Institute of Environmental Health Sciences: K12ES033594, P30ES023515, R01ES032831, R01ES033688, U2CES026555, U2CES026561, U2CES030859 - National Center for Advancing Translational Sciences: UL1TR001433, UL1TR004419

Documentation

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