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ProSAP: Streamlined Protein Stability Analysis for Thermal Shift Assays with Intuitive GUI

Hazem Abbas

Oct 16, 2024 — 2 min read

Photo by National Cancer Institute / Unsplash

ProSAP (Protein Stability Analysis Pod) is standalone software designed with a user-friendly graphical user interface (GUI) to facilitate the analysis of protein stability using thermal shift assays. ProSAP provides an integrated workflow consisting of five distinct modules:

Data Preprocessing: Cleans and formats raw data for subsequent analysis.
Data Visualization: Generates intuitive graphical representations of the data.
TPP Analysis: Conducts Thermal Proteome Profiling (TPP) for protein stability insights.
NPARC Analysis: Performs Non-Parametric Analysis for robust statistical evaluation.
iTSA Analysis: Offers isothermal shift analysis for comparing protein stability under various conditions.

This comprehensive tool allows researchers to compare several statistical strategies with ease. By analyzing the quantitative proteomics data generated by tools like Proteome Discoverer or MaxQuant, ProSAP enables users to evaluate the performance of different algorithms and apply the most suitable one to their dataset.

Its intuitive interface ensures that even complex analyses can be handled with minimal effort, providing researchers with clear insights and conclusions.

Supported Systems

Windows
Linux
macOS

Citation

@article{10.1093/bib/bbac057,
    author = {Ji, Hongchao and Lu, Xue and Zheng, Zhenxiang and Sun, Siyuan and Tan, Chris Soon Heng},
    title = "{ProSAP: a GUI software tool for statistical analysis and assessment of thermal stability data}",
    journal = {Briefings in Bioinformatics},
    year = {2022},
    month = {03}
    issn = {1477-4054},
    doi = {10.1093/bib/bbac057},
    url = {https://doi.org/10.1093/bib/bbac057},
    eprint = {https://academic.oup.com/bib/advance-article-pdf/doi/10.1093/bib/bbac057/42704881/bbac057.pdf}}

License

GPL-3.0 License

Resources & Downloads

Github

research Open-source protein Statistics statistical analysis