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Peptide Identification Using Tandem Mass Spectrometry

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Updated: Dec 22, 2025

Semi-Quantitative Analysis of Peptidoglycan by Liquid Chromatography Mass Spectrometry and Bioinformatics

Semi-Quantitative Analysis of Peptidoglycan by Liquid Chromatography Mass Spectrometry and Bioinformatics

Published on: October 13, 2020

Transfer posterior error probability estimation for peptide identification.

Xinpei Yi^1,2, Fuzhou Gong^3,4, Yan Fu^5,6

¹National Center for Mathematics and Interdisciplinary Sciences, Key Laboratory of Random Complex Structures and Data Science, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, 100190, China.

BMC Bioinformatics

|May 6, 2020

Summary

This summary is machine-generated.

A new algorithm accurately estimates peptide-spectrum match confidence in small groups. This transfer PEP method improves accuracy for specific peptide subsets in proteomics, outperforming existing techniques.

Keywords:

Local false discovery rate Mass spectrometry Posterior error probability Proteomics Quality control Transfer learning

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Last Updated: Dec 22, 2025

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Published on: October 13, 2020

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Published on: May 22, 2018

Area of Science:

Proteomics
Bioinformatics
Statistical analysis

Background:

Shotgun proteomics generates numerous peptide-spectrum matches (PSMs) with many false positives.
Quality control of PSMs involves statistical measures like false discovery rate (FDR) and posterior error probability (PEP).
Estimating PEP for small, specific PSM groups is challenging due to data limitations and distribution differences.

Purpose of the Study:

To develop a more accurate method for estimating PEP in small PSM groups.
To address the limitations of direct and combined PEP estimation methods for targeted analyses.

Main Methods:

Proposed the transfer PEP algorithm for group PEP estimation.
Derived group null distribution from combined null distribution.
Estimated group alternative distribution and null proportion using an iterative semi-parametric approach.

Main Results:

Transfer PEP demonstrated significantly higher accuracy in estimating PEPs for small PSM groups.
Validation on simulated and real proteomic data confirmed the algorithm's effectiveness.
Outperformed direct combined and separate PEP estimation methods.

Conclusions:

Introduced a novel approach for group PEP estimation in proteomics.
The transfer PEP methodology is applicable to small-group PEP estimation challenges in other scientific fields.