uafR

uafR automates gas chromatography coupled mass spectrometry (GC-MS) data processing, enabling advanced structural similarity matches and tentative compound identifications through cheminformatics workflows.

Key Features:

• Automated data retrieval: Automates the retrieval process for GC-MS data, eliminating manual steps in standard chemical ecology data analysis pipelines.
• Structural similarity matching: Performs advanced structural similarity matches for chemical comparisons across samples.
• Compound identification: Facilitates tentative compound identifications by integrating component areas with compound data from PubChem (pubchem.gov).
• Fragmentation database integration: Supports matching of m/z spectra against installed chemical fragmentation databases such as NIST.
• Concentration range validation: Algorithms correctly identify known compounds with R2 values ranging from 0.827-0.999 across concentrations from 1 x 10-5 to 1 x 103 ng/ul.

Scientific Applications:

• Metabolomics: Enables systematic interpretation of metabolomic datasets through automated GC-MS data processing.
• Exposomics: Supports high-throughput chemotyping for exposomic research requiring large-scale chemical data analysis.
• Volatilomics: Facilitates analysis of volatile compound profiles via streamlined cheminformatics workflows.
• Chemical ecology: Allows rapid chemical comparisons and compound identifications for ecological research involving GC-MS analysis.
• Landscape-level chemotyping: Enables processing of larger datasets for high-throughput, landscape-scale chemical phenotyping studies.

Methodology:

uafR uses cheminformatics workflows to pull out component areas for tentative compound identifications, matching m/z spectra against installed chemical fragmentation databases (e.g. NIST) and integrating with PubChem for compound reference data.