Tailor: A Nonparametric and Rapid Score Calibration Method for Database Search-Based Peptide Identification in...

Area of Science:

• Proteomics
• Bioinformatics
• Computational Biology

Background:

• Peptide-spectrum match (PSM) scores are crucial for database searching in proteomics.
• Current calibration methods for PSM scores often rely on specific assumptions or are computationally intensive.
• Inaccurate calibration can lead to suboptimal spectrum annotations and reduced discovery rates.

Purpose of the Study:

• To introduce Tailor, a novel, nonparametric, heuristic method for PSM score calibration.
• To improve the accuracy and efficiency of spectrum annotation in mass spectrometry-based proteomics.
• To provide a faster alternative to existing calibration methods without compromising performance.

Main Methods:

• Tailor calibrates PSM scores using the top 100-quantile of empirical, spectrum-specific null distributions.
• This heuristic approach avoids optimization steps and assumptions about score distribution forms.
• The method leverages the observed correlation between the mean and variance of null distributions.

Main Results:

• Re-calibrating XCorr, HyperScore, and OMSSA p-values with Tailor increased spectrum annotations compared to raw scores.
• Tailor-calibrated scores outperformed X!Tandem and OMSSA E-values and approached exact p-value method performance for XCorr.
• On high-resolution data, Tailor with XCorr achieved state-of-the-art performance, surpassing Res-ev scores significantly faster.

Conclusions:

• Tailor offers an accurate and computationally efficient method for PSM score calibration.
• This approach enhances spectrum annotation rates across various scoring algorithms and data resolutions.
• Tailor represents a significant advancement for accelerating and improving proteomic data analysis.