EIPPred: A tool for predicting,and designing MIC of the peptides
Project description
EIPPred
A computational approach to predict the MIC values of inhibitory peptides against E.coli using the amino acid sequence information.
Introduction
EIPpred is developed to predict and design the inhibitory peptides. In the standalone version, the Random Forest regressor-based model has been implemented. EIPpred is also available as a web server at https://webs.iiitd.edu.in/raghava/eippred. Please read/cite the content about the EIPpred for complete information, including the algorithm behind the approach.
Standalone
The Standalone version of transfacpred is written in python3 and following libraries are necessary for the successful run:
- scikit-learn
- Pandas
- Numpy
Minimum USAGE
To know about the available option for the stanadlone, type the following command:
eippred.py -h
To run the example, type the following command:
eippred.py -i example_input.fa
This will predict the MIC values of the submitted sequences, which will help identify the inhibitory activity of the peptides against E.coli. It will use other parameters by default. It will save the output in "outfile.csv" in CSV (comma-separated variables).
Full Usage
usage: eippred.py [-h]
[-i INPUT]
[-o OUTPUT]
[-j {1,2,3}]
[-d {1,2}]
Please provide following arguments for successful run
optional arguments:
-h, --help show this help message and exit
-i INPUT, --input INPUT
Input: protein or peptide sequence(s) in FASTA format or single sequence per line in single letter code
-o OUTPUT, --output OUTPUT
Output: File for saving results by default outfile.csv
-j {1,2,3}, --job {1,2,3}
Job Type: 1:Predict, 2: Design, by default 1
-p POSITION, --Position POSITION
Position of mutation (1-indexed)
-r RESIDUES, --Residues RESIDUES
Mutated residues (one or two of the 20 essential amino acids)
Input File: It allow users to provide input in the FASTA format.
Output File: The Program will save the results in the CSV format; if the user does not provide the output file name, it will be stored in "outfile.csv".
Job: User is allowed to choose between three different modules, such as, 1 for prediction, and 2 for Designing, by default its 1.
Position: User can choose any position in long sequences for mutation. This option is available for only Design module.
Residues: This option allows users to incorporate the mutation of single amino-acid and dipeptide amino-acid residue from the original peptide sequences at the specific position defined by the user.
EIPPred Package Files
It contantain following files, brief descript of these files given below
INSTALLATION : Installations instructions
LICENSE : License information
README.md : This file provide information about this package
eippred.py : Main python program
example_input.fa : Example file contain peptide sequenaces in FASTA format
example_predict_output.csv : Example output file for predict module
example_design_output.csv : Example output file for design module
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