A tool to predict Plant Diesease Resistance Protein
Project description
PlantDRPpred
A method for prediction of Plant Disease Resistance Protein
Introduction
PlantDRPpred is developed for predicting, mapping and scanning plant resistance proteins. More information on PlantDRPpred is available from its web server http://webs.iiitd.edu.in/raghava/plantdrppred. This page provides information about the standalone version of PlantDRPpred.
PIP Installation
PIP version is also available for easy installation and usage of this tool. The following command is required to install the package
pip install plantdrppred
To know about the available option for the pip package, type the following command:
plantdrppred -h
Standalone
Standalone version of PlantDRPpred is written in python3 and the following libraries are necessary for a successful run:
- scikit-learn > 1.3.0
- Pandas
- Numpy
- blastp
Minimum USAGE
To know about the available option for the standalone, type the following command:
PlantDRPpred.py -h
To run the example, type the following command:
PlantDRPpred.py -i seq.fasta
where seq.fasta is a input FASTA file. This will predict plant resistance protein in FASTA format. It will use other parameters by default. It will save output in "output_result.csv" in CSV (comma separated variables).
Full Usage:
Following is complete list of all options, you may get these options
usage: plantdrppred [-h] -i INPUT [-o OUTPUT] [-t THRESHOLD] [-m {1,2}] [-d {1,2}] [-wd WORKING]
Please provide the following arguments.
optional arguments:
-h, --help show this help message and exit
-i INPUT, --input INPUT
Input: protein or peptide sequence in FASTA format
-o OUTPUT, --output OUTPUT
Output: File for saving results by default outfile.csv
-t THRESHOLD, --threshold THRESHOLD
Threshold: Value between 0 to 1 by default 0.48
-m {1,2}, --model {1,2}
Model: 1: AAC feature based ExtraTrees Classifier , 2: AAC + PSSM feature based ExtraTrees Classifier, by default 1
-d {1,2}, --display {1,2}
Display: 1:AFP, 2: All peptides, by default 2
-wd WORKING, --working WORKING
Working Directory: Temporary directory to write files
Input File: It allow users to provide input in two format; i) FASTA format (standard) (e.g. seq.fasta)
Output File: Program will save result in CSV format, in case user do not provide output file name, it will be stored in output_result.csv.
Models: In this program, two models have been incorporated;
i) Model1 for predicting given input protein sequence as R protein and non-R proteins using SVC based on amino-acid composition of the proteins;
ii) Model2 for predicting given input peptide/protein sequence as R proteins and non-R protein using Hybrid approach, which is the ensemble of ET + BLAST. It combines the scores generated from machine learning (ET), and BLAST as Hybrid Score, and the prediction is based on Hybrid Score.
PlantDRPpred Package Files
It contain following files, brief description of these files given below
It contains the following files, brief description of these files given below
LICENSE : License information
README.md : This file provide information about this package
model : This folder contains two pickled models
plantdrppred.py : Main python program
possum : This folder contains the program POSSUM, that is used to calculate PSSM features
blastdb : Folder that contains the blast database of training dataset
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