"""
SHEPHARD:
Sequence-based Hierarchical and Extendable Platform for High-throughput Analysis of Region of Disorder
Authors: Garrett M. Ginell & Alex S. Holehouse
Contact: (g.ginell@wustl.edu)
Holehouse Lab - Washington University in St. Louis
"""
import re
## ------------------------------------------------------------------------
##
[docs]def build_mega_string(object_list, return_as_list=False):
"""
This takes a list of protein or domain SHEPHARD objects
and builds a single long str object that concatinates all
object.sequence elements together (i.e. a "megastring").
Allowed types for the object_list are Protein and Domain
objects.
This string can be used for simple statistical analysis
of composition.
Parameters
----------
object_list : list
List of SHEPHARD objects with object.sequence variable,
for example, a list of Domains or a list of Proteins
return_as_list : bool
If provided, rather than a single megastring, the
function returns a list of sequences from the objects
in question.
Returns
----------
str or list
Returns either a concatinated str object of the amino
acid sequences associated with the passed object
"""
megastring = ''
for obj in object_list:
megastring = megastring + obj.sequence
return megastring
## ------------------------------------------------------------------------
##
[docs]def find_string_positions(query, target, protein_indexing=True):
"""
Returns list of start positions where
stringA is in stringB - including overlaps.
Note that by default the indices use 1-indexing so that this works
directly with protein sequence numbering. However, for manipulating
Python strings this may be undesirable and 0 indexing may be better,
in which case setting protein_indexing = False will address this.
Practically, this uses the re regex expression under the hood
and searches left-to-right across the target, so if you want
to get fancier with your searching you can always pass in a
regular expression.
Examples
----------------
Conveninet regular expression syntax includes:
1. ``'.'`` for wildcards (e.g. ``'L.P'`` would match an L and P around any other character
2. ``[A|C]`` for requiring matching of a subset of residues (e.g. residue A and C).
But the python re module has a fairly complex pattern matching
ability
Parameters
--------------
query : str
The search query.
target : str
The string that we'll search for 1 or more entries
of the query
protein_indexing : bool
Flag which, if set to True, means the first residue in
a string indexes at '1' instead of '0' (as would be normal
in Python. If set to False, then indexing is done from 0.
Returns
----------
list
Returns a list with the start positions
"""
if protein_indexing is True:
offset = 1
else:
offset = 0
return [s.start() + offset for s in re.finditer('(?=%s)' % (query), target)]