Combining High-Resolution and Exact Calibration To Boost Statistical Power: A Well-Calibrated Score Function for...

Area of Science:

• Proteomics
• Mass Spectrometry
• Bioinformatics

Background:

• Accurate peptide identification in shotgun proteomics relies on high-resolution mass spectrometry data.
• Calibrating search engine scores for meaningful comparison across different spectra remains a challenge.

Purpose of the Study:

• To develop a novel database search score function that utilizes high-resolution mass spectrometry data for accurate peptide identification.
• To create a combined score function for improved performance and comparability of search results.

Main Methods:

• Introduced the "residue evidence" (res-ev) score function to leverage high-resolution spectral information.
• Developed a "combined p value" score by integrating calibrated res-ev and XCorr scores.
• Benchmarked the combined p value against existing score functions using four mass spectrometry datasets.

Main Results:

• The residue evidence (res-ev) score simultaneously utilizes high-resolution data and ensures score calibration.
• The combined p value score function demonstrates state-of-the-art performance in peptide identification.
• The combined p value generally outperforms MS Amanda and Morpheus, and is comparable to MS-GF+.

Conclusions:

• The developed res-ev and combined p value scores enhance the accuracy and comparability of peptide identification in shotgun proteomics.
• These scoring functions are available in the Tide search engine within the Crux mass spectrometry toolkit.
• The findings offer a significant advancement for mass spectrometry data analysis and proteomics research.