Status| <https://coveralls.io/r/hammerlab/mhctools?branch=master>`_
`|DOI| <https://zenodo.org/badge/latestdoi/18834/hammerlab/mhctools>`_
mhctools
========
Python interface to running command-line and web-based MHC binding
predictors.
Example
-------
\`\`\`python from mhctools import NetMHCpan # Run NetMHCpan for alleles
HLA-A*01:01 and HLA-A*02:01 predictor = NetMHCpan(alleles=["A\*02:01",
"hla-a0101"])
scan the short proteins 1L2Y and 1L3Y for epitopes
==================================================
protein\_sequences = { "1L2Y": "NLYIQWLKDGGPSSGRPPPS", "1L3Y":
"ECDTINCERYNGQVCGGPGRGLCFCGKCRCHPGFEGSACQA" }
binding\_predictions =
predictor.predict\_subsequences(protein\_sequences,
peptide\_lengths=[9])
flatten binding predictions into a Pandas DataFrame
===================================================
df = binding\_predictions.to\_dataframe()
epitope collection is sorted by percentile rank
===============================================
of binding predictions
======================
for binding\_prediction in binding\_predictions: if
binding\_prediction.affinity < 100: print("Strong binder: %s" %
(binding\_prediction,)) \`\`\` ## API
The following MHC binding predictors are available in ``mhctools``: \*
``MHCflurry``: open source predictor installed by default with
``mhctools``, requires the user run ``mhcflurry-downloads fetch`` first
to download MHCflurry models \* ``NetMHC3``: requires locally installed
version of `NetMHC 3.x <http://www.cbs.dtu.dk/services/NetMHC-3.4/>`_ \*
``NetMHC4``: requires locally installed version of `NetMHC
4.x <http://www.cbs.dtu.dk/services/NetMHC/>`_ \* ``NetMHC``: a wrapper
function to automatically use ``NetMHC3`` or ``NetMHC4`` depending on
what's installed. \* ``NetMHCpan``: requires locally installed version
of `NetMHCpan <http://www.cbs.dtu.dk/services/NetMHCpan/>`_ \*
``NetMHCIIpan``: requires locally installed version of
`NetMHCIIpan <http://www.cbs.dtu.dk/services/NetMHCIIpan/>`_ \*
``NetMHCcons``: requires locally installed version of
`NetMHCcons <http://www.cbs.dtu.dk/services/NetMHCcons/>`_ \*
``IedbMhcClass1``: Uses IEDB's REST API for class I binding predictions.
\* ``IedbMhcClass2``: Uses IEDB's REST API for class II binding
predictions. \* ``RandomBindingPredictor``: Creates binding predictions
with random IC50 and percentile rank values.
Every binding predictor is constructed with an ``alleles`` argument
specifying the HLA type for which to make predictions. Predictions are
generated by calling the ``predict`` method with a dictionary mapping
sequence IDs or names to amino acid sequences.
Additionally there is a module for running the
`NetChop <http://www.cbs.dtu.dk/services/NetChop>`_ proteosomal cleavage
predictor: \* ``NetChop``: requires locally installed version of
`NetChop-3.1 <http://www.cbs.dtu.dk/services/NetChop/>`_
.. |Build
Status| image:: https://travis-ci.org/hammerlab/mhctools.svg?branch=master
.. |Coverage
Status| image:: https://coveralls.io/repos/hammerlab/mhctools/badge.svg?branch=master
.. |DOI| image:: https://zenodo.org/badge/18834/hammerlab/mhctools.svg
Metadata
Release files for mhctools 1.6.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | Actions |
|---|---|---|---|---|
| mhctools-1.6.1.tar.gz | 32.7 kB | Without provenance | Details for mhctools-1.6.1.tar.gz |
Release files / mhctools-1.6.1.tar.gz
| Download URL | mhctools-1.6.1.tar.gz |
|---|---|
| Size | 32.7 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
78c1a38b20b0692450b16a8d720ef021bd1bab7735fc14a264d4f56df28230ce
|
|
BLAKE2b-256 checksum How to use checksums |
58e56f67462520af53e0380ffa4df4b11bc8743e41d4caa28fcf4b08f1484c2e
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
Security for mhctools 1.6.1
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
No provenance found
None of the files in this release were uploaded with provenance metadata.
A note on package security
PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.
To learn more about protecting yourself from malicious actors, visit our package security documentation.