RawVegetable

RawVegetable assesses mass spectrometry data quality for shotgun proteomics and cross-linking experiments, enabling chromatography optimization, artefact identification, sampling-density analysis, and reproducibility evaluation.

Key Features:

• Charge State Chromatogram Module: Independently displays ion current across different charge states to visualize charge distribution and support chromatographic optimization for highly charged ions, including cases with lower extracted-ion chromatograms (XIC) values.
• XL-Artefact Determination: Identifies potential noncovalent peptide associations arising during cross-linking experiments and flags them to distinguish true covalent cross-links from artefacts.
• TopN Density Estimation: Detects retention-time intervals of TopN under- or over-sampling to inform adjustments for more comprehensive MS/MS coverage.
• Chromatography Reproducibility Module: Performs pairwise comparisons between multiple experiments to assess chromatographic reproducibility and compare chromatographic profiles.

Scientific Applications:

• Shotgun proteomics: Assessing LC-MS/MS data quality, charge-state distributions, and sampling density to improve peptide identification and quantitation.
• Cross-linking experiments: Optimizing chromatography for highly charged cross-linked species and distinguishing covalent cross-links from noncovalent artefacts.
• Chromatography optimization: Informing adjustments to chromatographic conditions based on charge-state profiles and TopN sampling density.
• Reproducibility assessment: Validating experimental consistency through pairwise comparisons of chromatographic runs.

Methodology:

Accepts Thermo mass spectrometer RAW files, *.mzML files, and Agilent file formats; the chromatography reproducibility module accepts PatternLab for proteomics *.xic or *.plp files or SIM-XL output files to visualize identifications along the chromatogram.