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ProtE  

Processing Proteomics Data, Statistical Analysis and Visualization
View on CRAN: Click here


Download and install ProtE package within the R console
Install from CRAN:
install.packages("ProtE")

Install from Github:
library("remotes")
install_github("cran/ProtE")

Install by package version:
library("remotes")
install_version("ProtE", "1.0.3")



Attach the package and use:
library("ProtE")
Maintained by
Theodoros Margelos
[Scholar Profile | Author Map]
First Published: 2025-01-20
Latest Update: 2025-01-20
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>).
How to cite:
Theodoros Margelos (2025). ProtE: Processing Proteomics Data, Statistical Analysis and Visualization. R package version 1.0.3, https://cran.r-project.org/web/packages/ProtE. Accessed 02 Apr. 2025.
Previous versions and publish date:
1.0.1 (2025-01-15 19:40), 1.0.2 (2025-02-17 19:30)
Other packages that cited ProtE R package
View ProtE citation profile
Other R packages that ProtE depends, imports, suggests or enhances
Complete documentation for ProtE
Functions, R codes and Examples using the ProtE R package
Full ProtE package functions and examples
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