Pepfeature 1.0.7

A package that consists of functions for calculating epitope/peptide features for prediction purposes (Feature calculation/extraction)

Pepfeature

A package that consists of functions for calculating epitope/peptide features for prediction purposes

What is it

Pepfeature is a Python package providing routines for calculating peptide features on a given amino acid sequence. These features can be used for macine learning purposes such as classification for epitiope prediction.

Pepfeature Requirements

Required Software/Tools:

• Python 3.8

Required Package Dependencies:

• panadas
• numpy
• setuptools
• openpyxl

Installation

pip install Pepfeature

(All missing dependancies are expected to be installed asswell with this 'pip install'.) The source code is currently hosted on GitHub at: https://github.com/essakh/pepfeature

Example Use

NOTE: The Github contains an 'examples.py' with many example use cases

Example:

import pepfeature as pep
import pandas

df = pd.read_csv('pepfeature/data/Sample_Data.csv')

#Use of pepfeature
if __name__ == '__main__':
    #Calculate all features on df
    df_feat = pep.aa_all_feat.calc_df(dataframe=df, aa_column='Info_window_seq', Ncores=4, k=2)

    print(df_feat)

How to use it

Ensure at all times that any lines of code that utilize this package are encapsulated within the code block.

if __name__ == '__main__':

Please see pepfeature/examples.py for example use cases.

Also see the attached API of each function/ algorithm, for a complete documentation.

Contributing to pepfeature

All contributions, bug reports, bug fixes, documentation improvements, enhancements and ideas are welcome.