Skip to main content

A tool for predicting and scanning the peptides with the ability to bind non-classical class-I HLA alleles

Project description

HLAncPred

Introduction

HLAncPred is developed for predicting and scanning the peptides with the ability to bind non-classical class-I HLA alleles such as HLA-G*01:01,HLA-G*01:03,HLA-G*01:04, HLA-E*01:01, HLA-E*01:03 . More information on HLAncPred is available from its web-server https://webs.iiitd.edu.in/raghava/hlancpred/stand.html. This page provides information about stnadalone version of HLAncPred. Please read/cite the content about the HLAncPred for complete information including algorithm behind HLAncPred.

Models: In this program, five best models devoted to each allele, have been implemented for predicting the non-classical class-I HLA binder peptides. The models were trained on experimentally verified binders and randomly generated non-binders using Swiss-Prot database.

Modules/Jobs: This program implements two modules (job types); i) Predict: for prediction of non-classical class-I HLA allele binder peptides, ii) Scan: for creating all possible overlapping peptides of given length (window) and computing binding potential (score) of the overlapping peptides.

Minimum USAGE: Minimum usage is "python3 hlancpred.py -i peptide.fa -a G0101," where peptide.fa is a input fasta file, and 'G0101' is the name for HLA-G*01:01 against which the binders will be predicted. This will predict the binding ability of sequence in fasta format against HLA-G*01:01. It will use other parameters by default. It will save output in "outfile.csv" in CSV (comma seperated variables).

Full Usage: Following is complete list of all options, you may get these options by "python hlancpred.py -h"

usage: hlancpred [-h] -i INPUT -a {G0101,G0103,G0104,E0101,E0103} [-o OUTPUT] [-j {1,2}] [-w {8,9,10,11,12,13,14,15}] [-d {1,2}]

Please provide following arguments

optional arguments:
  -h, --help            show this help message and exit
  -i INPUT, --input INPUT
                        Input: protein or peptide sequence in FASTA format or single sequence per line in single letter code
  -a {G0101,G0103,G0104,E0101,E0103}, --allele {G0101,G0103,G0104,E0101,E0103}
                        Please provide the name of allele for the prediction of binder peptides
  -o OUTPUT, --output OUTPUT
                        Output: File for saving results by default outfile.csv
  -j {1,2}, --job {1,2}
                        Job Type: 1:predict, and 2:scan, by default 1
  -w {8,9,10,11,12,13,14,15}, --winleng {8,9,10,11,12,13,14,15}
                        Window Length: 8 to 35 (scan mode only), by default 9
  -d {1,2}, --display {1,2}
                        Display: 1:Only binders, 2: All peptides, by default 1

Input File: It allow users to provide input in two format; i) FASTA format (standard) and ii) Simple Format. In case of simple format, file should have one peptide sequence in a single line in single letter code (eg. peptide.seq). Note: 1: In case of predict and design module (job), the length of peptide should be upto 15 amino acids. If a sequence with length more than 15 will be provided, the program will take first 15 residues, and ignore the rest. In case of scan module, minimum length of protein/peptide sequence should be equal to window length (pattern), see peptide.fa. 2: Program will ignore peptides having length less than 8 residues (e.g., protein.fa).

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".

Allele: The program needs the name of the allele as shown in the usage, it could be G0101, G0103, G0104, E0101, and E0103.

Project details


Release history Release notifications | RSS feed

This version

1.0

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

hlancpred-1.0.tar.gz (19.7 MB view details)

Uploaded Source

Built Distribution

hlancpred-1.0-py3-none-any.whl (20.5 MB view details)

Uploaded Python 3

File details

Details for the file hlancpred-1.0.tar.gz.

File metadata

  • Download URL: hlancpred-1.0.tar.gz
  • Upload date:
  • Size: 19.7 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.9.17

File hashes

Hashes for hlancpred-1.0.tar.gz
Algorithm Hash digest
SHA256 60ab523dd1e07fcbad49123386458bc5241dbdb2e318c3bb958421f5762b74d9
MD5 166440a18ae25e89dc24d4d02d663715
BLAKE2b-256 d4759f1e084bc090d90ca5d667d541e289c730e974d50f9ace94cbca5b336fd1

See more details on using hashes here.

File details

Details for the file hlancpred-1.0-py3-none-any.whl.

File metadata

  • Download URL: hlancpred-1.0-py3-none-any.whl
  • Upload date:
  • Size: 20.5 MB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.9.17

File hashes

Hashes for hlancpred-1.0-py3-none-any.whl
Algorithm Hash digest
SHA256 030896252d965a512980af0b6a8c866788dcb69e8400c07b8a9da137f8391a78
MD5 c5945d1116d3c468671f9325f215abc9
BLAKE2b-256 a3b6c80a6b8a4b75a567f4a76feac4200900abe7458d158469ed91234dfee2d0

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page