plantdrppred 1.7

A tool to predict Plant Diesease Resistance Protein

PlantDRPpred

A computational method to predict the plant disease resistance protein based on evolutionary profiles.

Introduction

PlantDRPpred is a tool developed by Raghava-Lab in 2024. It is designed to predict whether a plant protein is Disease Resistant or not. It utilizes amino-acid compositions with XGBoost Classifier and PSSM as features to make predictions using an Random Forest Classifier. PlantDRPpred is also available as web-server at https://webs.iiitd.edu.in/raghava/plantdrppred. Please read/cite the content about the PlantDRPpred for complete information including algorithm behind the approach.

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 = 1.3.2
• Pandas
• Numpy
• blastp

Minimum USAGE

To know about the available option for the standalone, type the following command:

python plantdrppred.py -h

To run the example, type the following command:

python plantdrppred.py -i example_input.fasata

This will predict the probability whether a submitted sequence will PDR or non-PDR. It will use other parameters by default. It will save the output in "outfile.csv" in CSV (comma separated variables).

Full Usage

usage: plantdrppred.py [-h] -i INPUT [-o OUTPUT] [-t THRESHOLD] [-m {1,2}] [-d {1,2}]
                    [-wd WORKING]
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To run the example, type the following command:

plantdrppred.py -i example_input.fasta

Please provide following arguments.
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Following is complete list of all options, you may get these options
usage: plantdrppred.py [-h] 
                     [-i INPUT]
                     [-o OUTPUT]
                     [-m {1,2}] 

Please provide following arguments

optional arguments:

options:
  -h, --help            show this help message and exit
  -i INPUT, --input INPUT
                        Input: protein 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 0.50
  -m {1,2}, --model {1,2}
                        Model: 1: PSSM feature based Random Forest Classifier , 2:  PSSM
                        feature based Random Forest + BLAST , by default 1
  -d {1,2}, --display {1,2}
                        Display: 1: PDR, 2: All proteins, by default 2
  -wd WORKING, --working WORKING
                        Working Directory: Temporary directory to write files

Input File: It allow users to provide input in the FASTA format.

Output File: Program will save the results in the CSV format, in case user does not provide output file name, it will be stored in "outfile.csv".

Threshold: User should provide threshold between 0 and 1, by default its 0.5.

Display type: This option allow users to display only PDR proteins or all the input proteins.

Working Directory: Directory where intermediate files as well as final results will be saved

PlantDRPpred Package Files

It contains the following files, brief description of these files given below

LICENSE : License information

README.md : This file provide information about this package

blastdb : The folder contain blast database of all sequences in dataset

model : This folder contains two pickled models

ncbi_blast_2.15 : This folder contains blast psiblast and blastp(for linux)

plantdrppred.py : Main python program

possum : This folder contains the program POSSUM, that is used to calculate PSSM features

example_input.fasta : Example file containing protein sequences in FASTA format

example_output.csv : Example output file for the program