MZmine

MZmine processes liquid chromatography–mass spectrometry (LC/MS) data to detect, align, normalize, and export chromatographic peaks for proteomics and metabolomics differential profiling and biomarker discovery.

Key Features:

• Data processing stages: Spectral filtering, peak detection, alignment, and normalization are provided as a complete suite of preprocessing methods for LC/MS data.
• Recursive peak search algorithm: A novel recursive peak search algorithm is used to enhance the accuracy and efficiency of peak detection.
• Secondary peak picking: A secondary peak picking method refines detected peaks after alignment to improve data quality.
• Normalization with multiple internal standards: An advanced normalization tool employs multiple internal standards to enable reliable quantitative comparisons across samples.
• Visualization for comparative viewing: Visualization features allow comparative inspection of LC/MS data across multiple samples.
• Data export: Peak lists can be exported for downstream analyses in other programs.

Scientific Applications:

• Proteomics: Processing and differential profiling of LC/MS data for proteomics studies.
• Metabolomics: Processing and comparative analysis of LC/MS metabolomics data, including metabolic profiling of Catharanthus roseus cell cultures.
• Biomarker discovery and differential profiling: Support for identifying differential biomolecular components and potential biomarkers across multiple samples.

Methodology:

Spectral filtering to remove noise, recursive peak search for peak detection, secondary peak picking to refine results post-alignment, alignment across samples, normalization using multiple internal standards, and export/visualization of peak lists.