count_aa

This function counts the occurrence of each of the 20 amino acids
at each of the first 'n' positions across a vector of peptide sequences.

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) <doi:10.32614/RJ-2015-001>). This package is intended for both researchers and bioinformatics enthusiasts working on peptide-based projects, especially for their use with machine learning.

Josep-Ramon Codina

peptoolkit

A Toolkit for Using Peptide Sequences in Machine Learning

count_aa function

<dl><dt>peptides</dt>
<dd>A character vector of peptide sequences.</dd>
<dt>n</dt>
<dd>The number of initial positions to consider in each peptide sequence.</dd></dl>

Arguments

Count Amino Acids — count_aa

<dl>

<dt>peptides</dt>
<dd>A character vector of peptide sequences.</dd>


<dt>n</dt>
<dd>The number of initial positions to consider in each peptide sequence.</dd>

</dl>

count_aa: Count Amino Acids

Description

Usage

Value

Arguments

Examples