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peptoolkit
View on CRAN: Click
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Download and install peptoolkit package within the R console
Install from CRAN:
install.packages("peptoolkit")
Install from Github:
library("remotes")
install_github("cran/peptoolkit")
Install by package version:
library("remotes")
install_version("peptoolkit", "0.0.1")
Attach the package and use:
library("peptoolkit")
Maintained by
Josep-Ramon Codina
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
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First Published: 2023-07-13
Latest Update: 2023-07-13
Description:
This toolkit is designed for manipulation and analysis of peptides. It provides functionalities to assist researchers in peptide engineering and proteomics. Users can manipulate peptides by adding amino acids at every position, count occurrences of each amino acid at each position, and transform amino acid counts based on probabilities. The package offers functionalities to select the best versus the worst peptides and analyze these peptides, which includes counting specific residues, reducing peptide sequences, extracting features through One Hot Encoding (OHE), and utilizing Quantitative Structure-Activity Relationship (QSAR) properties (based in the package 'Peptides' by Osorio et al. (2015) ). This package is intended for both researchers and bioinformatics enthusiasts working on peptide-based projects, especially for their use with machine learning.
How to cite:
Josep-Ramon Codina (2023). peptoolkit: A Toolkit for Using Peptide Sequences in Machine Learning. R package version 0.0.1, https://cran.r-project.org/web/packages/peptoolkit
Previous versions and publish date:
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Other R packages that peptoolkit depends,
imports, suggests or enhances
Functions, R codes and Examples using
the peptoolkit R package
Some associated functions: appearance_to_binary . count_aa . extract_features_OHE . extract_features_QSAR . filter_residues . increment . reduce_sequences . select_best_vs_worst .
Some associated R codes: appearance_to_binary.R . count_aa.R . extract_features_OHE.R . extract_features_QSAR.R . filter_residues.R . increment_seq.R . reduce_sequences.R . select_best_vs_worst.R . Full peptoolkit package functions and examples
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