Package: ProtE
Type: Package
Title: Processing Proteomics Data, Statistical Analysis and
        Visualization
Version: 1.0.3
Authors@R: 
    c(person("Theodoros", "Margelos", email = "ted.margelos02@gmail.com",role = c("aut","cre","cph")),
    person("Rafael", "Stroggilos", email = "rstrog@bioacademy.gr", role = c("ctb","cph")))
Description: 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>).
License: MIT + file LICENSE
Encoding: UTF-8
Imports: dplyr, vegan, UniprotR, stringr, missRanger, car, openxlsx,
        tidyr, broom, reshape2, ggpubr, ggplot2, VIM, forcats,
        grDevices, grid, limma, pheatmap,
Suggests: BiocManager, rmarkdown, knitr
URL: https://github.com/theomargel/ProtE
BugReports: https://github.com/theomargel/ProtE/issues
RoxygenNote: 7.3.2
Config/testthat/edition: 3
Depends: R (>= 2.10)
VignetteBuilder: knitr
Language: en-US
NeedsCompilation: no
Packaged: 2025-02-18 10:11:46 UTC; tedma
Author: Theodoros Margelos [aut, cre, cph],
  Rafael Stroggilos [ctb, cph]
Maintainer: Theodoros Margelos <ted.margelos02@gmail.com>
Repository: CRAN
Date/Publication: 2025-02-18 10:40:02 UTC
Built: R 4.3.3; ; 2025-04-07 04:07:43 UTC; windows
