tutorial_pdz_v5.py

"""
Analysis of an alignment of the PDZ domain family
Calculate SVD of a matrix using numpy functions
e.g.
A = floor(random.rand(4,4)*20-10)
linalg.svd(A)
for sparse matrices, there are methods in SciPy
"""

from sca import *
from sca.tutorial_helpers import truncate
from sca.sca_read import *
from sca.msa_search import *

PDB_FILE = './Inputs/1BE9.pdb'
FREE_FILE = './Inputs/al_pdz.free'
CHAINID = 'A'
FRAC_ALPHA_CUTOFF = 0.8


def tutorial():
    """
    Analysis of an alignment of the PDZ domain family
    """
    pdb_res_list = read_pdb(PDB_FILE, CHAINID)
    alignments = read_free(FREE_FILE)
    # n_alignments = len(alignments)
    # len_alignment = len(alignments[0])

    # truncate alignments to sequence positions with
    # gap frequency no greater than 20% - to avoid over-representation of gaps
    alignments = truncate(alignments, FRAC_ALPHA_CUTOFF)

    return msa_search(pdb_res_list, alignments)


OUTPUT = tutorial()
print 'output: '
print OUTPUT