Skip to main content

MHC Binding Predictor

Project description

Build Status

mhcflurry

MHC I ligand prediction package with competitive accuracy and a fast and documented implementation.

MHCflurry supports Class I peptide/MHC binding affinity prediction using ensembles of allele-specific models. It runs on Python 2.7 and 3.4+ using the keras neural network library. It exposes command-line and Python library interfaces.

If you find MHCflurry useful in your research please cite:

O’Donnell, T. et al., 2017. MHCflurry: open-source class I MHC binding affinity prediction. bioRxiv. Available at: http://www.biorxiv.org/content/early/2017/08/09/174243.

Installation (pip)

Install the package:

$ pip install mhcflurry

Then download our datasets and trained models:

$ mhcflurry-downloads fetch

You can now generate predictions:

$ mhcflurry-predict \
       --alleles HLA-A0201 HLA-A0301 \
       --peptides SIINFEKL SIINFEKD SIINFEKQ \
       --out /tmp/predictions.csv

Wrote: /tmp/predictions.csv

See the documentation for more details.

Project details


Download files

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

Source Distribution

mhcflurry-1.2.0.tar.gz (54.7 kB view details)

Uploaded Source

File details

Details for the file mhcflurry-1.2.0.tar.gz.

File metadata

  • Download URL: mhcflurry-1.2.0.tar.gz
  • Upload date:
  • Size: 54.7 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No

File hashes

Hashes for mhcflurry-1.2.0.tar.gz
Algorithm Hash digest
SHA256 3c8b2f73bc12602a7678f4097c8a26f457dfc85fb4ab1d47c309e79f7d290fce
MD5 baecc721047642b7b9b8063b3e27edda
BLAKE2b-256 7baa99060352dd42dd916ff4c01907ddc8f962de3670f4c6ce0da0d107a721a9

See more details on using hashes here.

Supported by

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