Package: ProtE 1.0.3

ProtE: Processing Proteomics Data, Statistical Analysis and Visualization

The 'Proteomics Eye' ('ProtE') offers a comprehensive and intuitive framework for the univariate analysis of label-free proteomics data. By integrating essential data wrangling and processing steps into a single function, 'ProtE' streamlines pairwise statistical comparisons for categorical variables. It provides quality checks and generates publication-ready visualizations, enabling efficient and robust data analysis. 'ProtE' is compatible with proteomics data outputs from 'MaxQuant' (Cox & Mann, (2008) <doi:10.1038/nbt.1511>), 'DIA-NN' (Demichev et al., (2020) <doi:10.1038/s41592-019-0638-x>), and 'Proteome Discoverer' (Thermo Fisher Scientific, version 2.5). The package leverages 'ggplot2' for visualization (Wickham, (2016) <doi:10.1007/978-3-319-24277-4>) and 'limma' for statistical analysis (Ritchie et al., (2015) <doi:10.1093/nar/gkv007>).

Authors:Theodoros Margelos [aut, cre, cph], Rafael Stroggilos [ctb, cph]