SQuAPP-simple quantitative analysis of proteins and PTMs.

Area of Science:

• Proteomics
• Biomedical Research
• Bioinformatics

Background:

• Proteomics and post-translational modification (PTM) analysis are crucial in biological and biomedical studies.
• Existing software for quantitative proteomics is often complex, posing challenges for non-expert scientists.
• Integrating multi-level proteomics data, including various PTMs, remains a significant hurdle for biologists.

Purpose of the Study:

• To develop an accessible R-Shiny web-based pipeline for quantitative proteomics data analysis.
• To provide a streamlined workflow for quality control, data pre-processing, statistical analysis, and visualization.
• To facilitate the integrative analysis of protein, peptide, and PTM datasets for enhanced biological interpretation.

Main Methods:

• Development of SQuAPP, an R-Shiny web application.
• Implementation of a guided workflow for users of varying expertise levels.
• Parallel processing and quantitative integration of protein, peptide, and PTM datasets.

Main Results:

• SQuAPP enables rapid identification of protein modification changes independent of protein-level modulation.
• The pipeline allows for intuitive interpretation of dynamic dependencies between different protein modifications.
• Provides a user-friendly interface for comprehensive quantitative proteomics analysis.

Conclusions:

• SQuAPP addresses the need for accessible and integrated proteomics data analysis tools.
• The pipeline empowers biologists to conduct sophisticated analyses of protein and PTM data.
• Facilitates deeper understanding of biological processes through quantitative proteomics insights.