EBprotV2: A Perseus Plugin for Differential Protein Abundance Analysis of Labeling-Based Quantitative Proteomics Data

Area of Science:

• Proteomics
• Bioinformatics
• Computational Biology

Background:

• Accurate differential protein abundance analysis is crucial in proteomics.
• Existing methods like EBprot have limitations in speed and model flexibility.
• Handling skewed distributions and missing data in large datasets remains challenging.

Purpose of the Study:

• To introduce EBprotV2, an improved Perseus plugin for differential protein abundance analysis.
• To enhance computational speed and model flexibility compared to the original EBprot.
• To enable differential analysis of label-free proteomics data by transforming it into peptide ratio data.

Main Methods:

• Developed EBprotV2 as a C++ based Perseus plugin.
• Implemented a flexible semiparametric mixture model to handle skewed ratio distributions.
• Introduced a MakeGrpData submodule to convert label-free intensity data to peptide ratio data.

Main Results:

• EBprotV2 offers significantly faster computation times than the R implementation of EBprot.
• The semiparametric model provides better handling of skewed ratio distributions.
• The MakeGrpData submodule effectively transforms label-free data for differential analysis, especially with missing values.

Conclusions:

• EBprotV2 provides a faster and more flexible solution for differential protein abundance analysis in proteomics.
• The tool improves upon previous methods by accommodating complex data distributions and enabling label-free data analysis.
• EBprotV2 is a valuable addition to the Perseus software suite for proteomics researchers.