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"""
Command line object for CCMpred contact prediction application
"""
__author__ = "Felix Simkovic"
__date__ = "04 Aug 2016"
__version__ = "0.1"
from Bio.Application import _Argument
from Bio.Application import _Option
from Bio.Application import _Switch
from Bio.Application import AbstractCommandline
[docs]class CCMpredCommandline(AbstractCommandline):
"""
Command line object for CCMpred [#]_ contact prediction application
https://github.com/soedinglab/CCMpred
The CCMpred program is a very fast pseudo-likelihood maximisation
implementation of covariance detection in a Multiple Sequence
Alignment. This wrapper allows for easy-to-use Python implementation.
.. [#] Seemayer S, Gruber M, Söding J (2014). CCMpred--fast and precise
prediction of protein residue-residue contacts from correlated mutations.
Bioinformatics 30(21), 3128-3130.
Examples
--------
To predict a contact map using a Multiple Sequence Alignment in
JONES format, use:
>>> from conkit.applications import CCMpredCommandline
>>> ccmpred_cline = CCMpredCommandline(
... alnfile="test.aln", matfile="output.mat"
... )
>>> print(ccmpred_cline)
ccmpred test.aln output.mat
You would typically run the command line with :func:`ccmpred_cline` or via
the Python subprocess module.
"""
def __init__(self, cmd="ccmpred", **kwargs):
self.parameters = [
_Option(['-n', "numiter"],
'Compute a maximum of NUMITER operations [default: 50]',
equate=False),
_Option(['-e', 'epsilon'],
"Set convergence criterion for minimum decrease in the "
"last K iterations to EPSILON [default: 0.01]",
equate=False),
_Option(['-k', 'lastk'],
"Set K parameter for convergence criterion to LASTK [default: 5]",
equate=False),
_Option(['-i', 'inifile'],
"Read initial weights from INIFILE",
filename=True,
equate=False),
_Option(['-r', 'rawfile'],
"Store raw prediction matrix in RAWFILE",
filename=True,
equate=False),
_Option(['-t', 'threads'],
'Calculate using THREADS threads on the CPU (automatically disables CUDA if available) [default: 1]',
equate=False),
_Option(['-w', 'idthres'],
"Set sequence reweighting identity threshold to IDTHRES [default: 0.8]",
equate=False),
_Option(['-l', 'lfactor'],
"Set pairwise regularization coefficients to LFACTOR * (L-1) [default: 0.2]",
equate=False),
_Switch(['-A', 'apc'],
"Disable average product correction (APC)"),
_Switch(['-R', 'renormalize'],
"Re-normalize output matrix to [0,1]"),
_Argument(['alnfile'],
"Input alignment file [JONES format]",
filename=True,
is_required=True),
_Argument(['matfile'],
"Output matrix file",
filename=True,
is_required=True),
]
AbstractCommandline.__init__(self, cmd, **kwargs)
