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HLADR4Pred2.0

A computational approach to predict HLA-DRB1-04:01 binders using the sequence information of the peptides.

Introduction

HLADR4Pred2.0 is an update of HLADR4Pred published by our group in 2004. It is developed to predict, scan, and, design the binders of HLA-Class II allele HLA-DRB1-04:01 using sequence information only. In the standalone version, extra-tree classifier based model is implemented alongwith the BLAST search, named it as hybrid approach. HLADR4Pred2.0 is also available as web-server at https://webs.iiitd.edu.in/raghava/hladr4pred2. Please read/cite the content about the HLADR4Pred2.0 for complete information including algorithm behind the approach.

Reference:

  • Patiyal S, Dhall A, Kumar N, Raghava GPS (2024) HLA-DR4Pred2: an improved method for predicting HLA-DRB104:01 binders. Methods, doi.org/10.1016/j.ymeth.2024.10.007.
  • Bhasin M, Raghava GPS (2004) SVM based method for predicting HLA-DRB1 binding peptides in an antigen sequence. Bioinformatics 20(3): 421-3
  • 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 hladr4pred2
    

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

    hladr4pred2 -h
    

    Standalone

    The Standalone version of transfacpred is written in python3 and following libraries are necessary for the successful run:

    • scikit-learn
    • Pandas
    • Numpy
    • blastp

    Minimum USAGE

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

    python hladr4pred2.py -h
    

    To run the example, type the following command:

    python3 hladr4pred2.py -i example_input.fa
    

    This will predict if the submitted sequences are Binders or Non-binder. It will use other parameters by default. It will save the output in "outfile.csv" in CSV (comma seperated variables).

    Full Usage

    usage: hladr4pred2.py [-h] 
                           [-i INPUT 
                           [-o OUTPUT]
    		       [-j {1,2,3}]
    		       [-t THRESHOLD]
                           [-w {9,10,11,12,13,14,15,16,17,18,19,20}]
    		       [-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, 3:Scan, by default 1
      -t THRESHOLD, --threshold THRESHOLD
                            Threshold: Value between 0 to 1 by default 0.16
      -w {9,10,11,12,13,14,15,16,17,18,19,20}, --winleng {9,10,11,12,13,14,15,16,17,18,19,20}
                            Window Length: 9 to 20 (scan mode only), by default 9
      -d {1,2}, --display {1,2}
                            Display: 1:Binders only, 2: All peptides, by default 1
    

    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 do not provide output file name, it will be stored in "outfile.csv".

    Threshold: User should provide threshold between 0 and 1, by default its 0.16.

    Job: User is allowed to choose between three different modules, such as, 1 for prediction, 2 for Designing and 3 for scanning, by default its 1.

    Window length: User can choose any pattern length between 9 and 20 in long sequences. This option is available for only scanning module.

    Display type: This option allow users to fetch either only HLA-DRB1-04:01 binding peptides by choosing option 1 or prediction against all peptides by choosing option 2.

    HLADR4Pred2.0 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

    model.zip : This zipped file contains the compressed version of model

    envfile : This file compeises of paths for the database and blastp executable

    hladr4pred2.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_scan_output.csv : Example output file for scan module

    example_design_output.csv : Example output file for design module