plantdrppred 1.3

A tool to predict Plant Diesease Resistance Protein

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