Metadata-Version: 1.1
Name: mhcflurry
Version: 2.0.0
Summary: MHC Binding Predictor
Home-page: https://github.com/hammerlab/mhcflurry
Author: Tim O'Donnell and Alex Rubinsteyn
Author-email: timodonnell@gmail.com
License: http://www.apache.org/licenses/LICENSE-2.0.html
Description: |Build Status|
        
        mhcflurry
        =========
        
        `MHC I <https://en.wikipedia.org/wiki/MHC_class_I>`__ ligand prediction
        package with competitive accuracy and a fast and
        `documented <http://openvax.github.io/mhcflurry/>`__ implementation.
        
        MHCflurry implements class I peptide/MHC binding affinity prediction.
        The current version provides pan-MHC I predictors supporting any MHC
        allele of known sequence. MHCflurry runs on Python 3.4+ using the
        `tensorflow <https://www.tensorflow.org/>`__ neural network library. It
        exposes
        `command-line <http://openvax.github.io/mhcflurry/commandline_tutorial.html>`__
        and `Python
        library <http://openvax.github.io/mhcflurry/python_tutorial.html>`__
        interfaces.
        
        Starting in version 1.6.0, MHCflurry also includes two expermental
        predictors, an “antigen processing” predictor that attempts to model MHC
        allele-independent effects such as proteosomal cleavage and a
        “presentation” predictor that integrates processing predictions with
        binding affinity predictions to give a composite “presentation score.”
        Both models are trained on mass spec-identified MHC ligands. These
        models were updated to incorporate minor improvements for the MHCflurry
        2.0 release.
        
        If you find MHCflurry useful in your research please cite:
        
           T. O’Donnell, A. Rubinsteyn, U. Laserson. “MHCflurry 2.0: Improved
           pan-allele prediction of MHC I-presented peptides by incorporating
           antigen processing,” *Cell Systems*, 2020.
           https://doi.org/10.1016/j.cels.2020.06.010
        
        ..
        
           T. O’Donnell, A. Rubinsteyn, M. Bonsack, A. B. Riemer, U. Laserson,
           and J. Hammerbacher, “MHCflurry: Open-Source Class I MHC Binding
           Affinity Prediction,” *Cell Systems*, 2018.
           https://doi.org/10.1016/j.cels.2018.05.014
        
        Please file an issue if you have questions or encounter problems.
        
        Have a bugfix or other contribution? We would love your help. See our
        `contributing guidelines <CONTRIBUTING.md>`__.
        
        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
        
        Or scan protein sequences for potential epitopes:
        
        ::
        
           $ mhcflurry-predict-scan \
                   --sequences MFVFLVLLPLVSSQCVNLTTRTQLPPAYTNSFTRGVYYPDKVFRSSVLHS \
                   --alleles HLA-A*02:01 \
                   --out /tmp/predictions.csv
                   
           Wrote: /tmp/predictions.csv  
        
        See the `documentation <http://openvax.github.io/mhcflurry/>`__ for more
        details.
        
        Docker
        ------
        
        You can also try the latest (GitHub master) version of MHCflurry using
        the Docker image hosted on
        `Dockerhub <https://hub.docker.com/r/openvax/mhcflurry>`__ by running:
        
        ::
        
           $ docker run -p 9999:9999 --rm openvax/mhcflurry:latest
        
        This will start a `jupyter <https://jupyter.org/>`__ notebook server in
        an environment that has MHCflurry installed. Go to
        ``http://localhost:9999`` in a browser to use it.
        
        To build the Docker image yourself, from a checkout run:
        
        ::
        
           $ docker build -t mhcflurry:latest .
           $ docker run -p 9999:9999 --rm mhcflurry:latest
        
        Common issues and fixes
        -----------------------
        
        Problems downloading data and models
        ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
        
        Some users have reported HTTP connection issues when using
        ``mhcflurry-downloads fetch``. As a workaround, you can download the
        data manually (e.g. using ``wget``) and then use ``mhcflurry-downloads``
        just to copy the data to the right place.
        
        To do this, first get the URL(s) of the downloads you need using
        ``mhcflurry-downloads url``:
        
        ::
        
           $ mhcflurry-downloads url models_class1_presentation
           https://github.com/openvax/mhcflurry/releases/download/1.6.0/models_class1_presentation.20200205.tar.bz2```
        
        Then make a directory and download the needed files to this directory:
        
        ::
        
           $ mkdir downloads
           $ wget  --directory-prefix downloads https://github.com/openvax/mhcflurry/releases/download/1.6.0/models_class1_presentation.20200205.tar.bz2```
        
           HTTP request sent, awaiting response... 200 OK
           Length: 72616448 (69M) [application/octet-stream]
           Saving to: 'downloads/models_class1_presentation.20200205.tar.bz2'
        
        Now call ``mhcflurry-downloads fetch`` with the
        ``--already-downloaded-dir`` option to indicate that the downloads
        should be retrived from the specified directory:
        
        ::
        
           $ mhcflurry-downloads fetch models_class1_presentation --already-downloaded-dir downloads
        
        .. |Build Status| image:: https://travis-ci.org/openvax/mhcflurry.svg?branch=master
           :target: https://travis-ci.org/openvax/mhcflurry
        
Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
Classifier: Environment :: Console
Classifier: Operating System :: OS Independent
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Programming Language :: Python
Classifier: Topic :: Scientific/Engineering :: Bio-Informatics
