flagme

flagme performs fragment-level analysis of gas chromatography-mass spectrometry (GC-MS) metabolomics data to extract fragment signals for metabolite identification and quantification.

Key Features:

• Fragment-Level Analysis: Parses GC-MS spectra into individual fragments to enable more precise metabolite profiling.
• Bioconductor Integration: Integrates with the Bioconductor ecosystem and the R statistical programming language for compatibility with R-based bioinformatics workflows.
• Statistical and Computational Processing: Applies statistical analysis and computational techniques to process and interpret complex GC-MS metabolomics datasets.

Scientific Applications:

• Metabolite Identification and Quantification: Supports identification and quantification of metabolites from GC-MS fragment-level data.
• Metabolic Pathway Analysis: Facilitates downstream analyses that inform interpretation of metabolic pathways and biochemical processes.

Methodology:

Applies statistical analysis and computational techniques to process and interpret GC-MS metabolomics datasets and integrates with Bioconductor/R.