The peptoolkit
R package is designed for the
manipulation and analysis of peptides. The package provides a range of
functionalities aimed at assisting researchers in peptide engineering
and proteomics. The package allows users to manipulate peptides by
adding amino acids at every position, count the occurrences of each
amino acid at each position, and transform amino acid counts based on
probabilities. Additionally, the package offers functionalities to
select the best versus the worst peptides and further analyze these
peptides. This includes counting specific residues, reducing peptide
sequences, extracting features through One Hot Encoding (OHE), and
utilizing Quantitative Structure-Activity Relationship (QSAR)
properties. This package is intended for both researchers and
bioinformatics enthusiasts who are working on peptide-based projects,
specially for their use with machine learning.
You can install the released version of peptoolkit from CRAN with:
install.packages("peptoolkit")
You can also install the development version from GitHub with:
# install.packages("devtools") # Uncomment and run if you don't have the devtools package yet
::install_github("jrcodina/peptoolkit") devtools
This is a basic example which shows you how to use the main function:
# Default usage
<- peptoolkit::extract_features_QSAR(n = 3)
result
# Providing a custom peptide list
<- peptoolkit::extract_features_QSAR(n = 3, custom.list = TRUE, PeList = c('ACA', 'ADE')) result
Please refer to function documentation for more details on parameters and their usage.
If you use peptoolkit
in your research, please cite:
Codina J (2023). peptoolkit: A Toolkit for Using Peptide Sequences in Machine Learning and Accelerate Virtual Screening. R package version 0.0.1.
A BibTeX entry for LaTeX users is
@Manual{,
title = {peptoolkit: A Toolkit for Using Peptide Sequences in Machine Learning and Accelerate Virtual Screening},
author = {Josep-Ramon Codina},
year = {2023},
note = {R package version 0.0.1},
}