DEprot: a comprehensive R-package for the analysis of label-free quantitation mass spectrometry data

Area of Science:

• Proteomics
• Bioinformatics
• Computational Biology

Background:

• Proteome-wide protein-protein interaction (PPI) studies are rapidly advancing.
• Improvements in mass spectrometry and new techniques drive this progress.
• Handling missing data, especially non-random missing proteins, remains a challenge.

Purpose of the Study:

• To present DEprot, a novel R-package for end-to-end proteomics data analysis.
• To provide a comprehensive toolset for analyzing and visualizing proteomics data.
• To address the issue of missing data imputation in large-scale PPI studies.

Main Methods:

• Development of the DEprot R-package.
• Implementation of a serial imputation strategy for missing value handling.
• Application to proteomics datasets, including those from protein enrichment and knockout experiments.

Main Results:

• DEprot offers a complete workflow for proteomics data analysis and visualization.
• The serial imputation strategy effectively handles non-random missing values.
• The package is particularly useful for analyzing data from protein enrichment and knockout studies.

Conclusions:

• DEprot provides a robust solution for proteomics data analysis, including missing data imputation.
• The R-package facilitates more accurate and comprehensive insights from proteome-wide PPI studies.
• This toolset aids researchers in overcoming common challenges in proteomics data interpretation.