MassWiz

MassWiz performs peptide identification from mass spectrometry (MS) data to improve accuracy of proteomics analyses.

Key Features:

• Empirical Scoring Function: Uses a novel empirical scoring function that assigns weights to major ions, continuity of b-y ion series, intensities, and supporting neutral losses for peptide-spectrum matches.
• Instrument-specific Calibration: Calibrates scoring weights according to the specific type of mass spectrometry instrument used.
• Consensus High-confidence Identification: Identifies high-confidence peptides corroborated by at least three different algorithms while maintaining peptide assignment counts.

Scientific Applications:

• Standard mixture benchmarking: Evaluated on 486,882 spectra from a standard 18-protein mixture generated on six different instruments from the Seattle Proteome Center.
• Yeast dataset analysis: Demonstrated robustness on a yeast dataset comprising 106,133 spectra obtained from the NCBI Peptidome repository.
• Comparative benchmarking at 1% FDR: Benchmarked against Mascot, Sequest, OMSSA, and X!Tandem at a 1% false discovery rate, outperforming others on the largest dataset acquired on an AGILENT XCT instrument and achieving second-best performance compared to Mascot on other instruments.

Methodology:

Employs an empirical scoring function that weights major ions, continuity of b-y ion series, intensities, and supporting neutral losses with instrument-specific calibration; benchmarking was performed against Mascot, Sequest, OMSSA, and X!Tandem at a 1% FDR.