SIMAT

SIMAT implements R/Bioconductor functions to analyze gas chromatography coupled with single quadrupole mass spectrometry (GC-SIM-MS) data acquired in targeted ion monitoring (SIM) mode for qualitative and quantitative targeted small-molecule analysis.

Key Features:

• Fragment Selection Optimization: Employs an optimization algorithm to select optimal fragment ions from a user-provided library of background analytes for target analytes, aiding resolution of overlapping chromatographic peaks.
• Data Visualization: Generates total ion chromatograms (TIC) and extracted ion chromatograms (EIC) for inspection of GC-SIM-MS runs and target analyte signals.
• Retention Index Calibration: Performs retention index (RI) calibration to align experimental retention data with reference standards.
• Data Import and Preprocessing: Imports raw GC-SIM-MS data in netCDF or NIST mass spectral library (MSL) formats and provides preprocessing functions to prepare datasets for analysis.

Scientific Applications:

• Targeted Metabolomics: Enables targeted metabolomics studies and was validated on a GC-SIM-MS dataset from plasma samples of 86 patients.
• Method Development and Validation: Supports method development using mixtures of internal standards spiked into plasma at varying concentrations and can serve as an alternative to AMDIS and MetaboliteDetector for detecting targets and estimating relative intensities.

Methodology:

Computational steps explicitly include importation of raw GC-SIM-MS data and spectral libraries, preprocessing of imported data, an optimization algorithm for fragment selection from overlapping peaks using a user-provided background analyte library, and visualization of TIC/EIC with RI calibration.