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promor  

Proteomics Data Analysis and Modeling Tools
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("promor", "0.2.1")



Attach the package and use:
library("promor")
Maintained by
Chathurani Ranathunge
[Scholar Profile | Author Map]
First Published: 2022-07-20
Latest Update: 2023-07-17
Description:
A comprehensive, user-friendly package for label-free proteomics data analysis and machine learning-based modeling. Data generated from 'MaxQuant' can be easily used to conduct differential expression analysis, build predictive models with top protein candidates, and assess model performance. promor includes a suite of tools for quality control, visualization, missing data imputation (Lazar et. al. (2016) ), differential expression analysis (Ritchie et. al. (2015) ), and machine learning-based modeling (Kuhn (2008) ).
How to cite:
Chathurani Ranathunge (2022). promor: Proteomics Data Analysis and Modeling Tools. R package version 0.2.1, https://cran.r-project.org/web/packages/promor. Accessed 29 Mar. 2025.
Previous versions and publish date:
0.1.0 (2022-07-20 19:30), 0.1.1 (2022-11-01 15:55), 0.2.0 (2023-01-17 19:20)
Other packages that cited promor R package
View promor citation profile
Other R packages that promor depends, imports, suggests or enhances
Complete documentation for promor
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