PaDuA: a Python library for high-throughput (phospho)proteomic data analysis

Abstract

The increased speed and sensitivity in mass spectrometry-based proteomics has encouraged its use in biomedical research in recent years. Large-scale detection of proteins in cells, tissues and whole organisms yields highly-complex quantitative data, the analysis of which poses significant challenges. Standardized proteomic workflows are necessary to ensure automated, sharable and reproducible proteomics analysis. Likewise, standardized data processing workflows are also essential for the overall reproducibility of results. To this purpose, we developed PaDuA, a Python package optimized for the processing and analysis of (phospho)proteomics data. PaDuA provides a collection of tools which can be used to build scripted workflows within Jupyter Notebooks, to facilitate bioinformatics analysis by both end-users and developers.