#!/usr/bin/env python
# -*- coding: utf-8 -*-
#
# This file is part of the `pypath` python module
#
# Copyright 2014-2023
# EMBL, EMBL-EBI, Uniklinik RWTH Aachen, Heidelberg University
#
# Authors: see the file `README.rst`
# Contact: Dénes Türei (turei.denes@gmail.com)
#
# Distributed under the GPLv3 License.
# See accompanying file LICENSE.txt or copy at
# https://www.gnu.org/licenses/gpl-3.0.html
#
# Website: https://pypath.omnipathdb.org/
#
from future.utils import iteritems
import pypath.share.curl as curl
import pypath.resources.urls as urls
import pypath.share.common as common
import pypath.inputs.common as inputs_common
import pypath.utils.mapping as mapping
import pypath.internals.intera as intera
import pypath.utils.seq as seq
[docs]
def get_li2012():
"""
Reads supplementary data of Li 2012 from local file.
Returns table (list of lists).
"""
url = urls.urls['li2012']['url']
c = curl.Curl(url, silent = False, large = True, slow = True)
xls = c.fileobj
xlsfile = xls.name
xls.close()
tbl = inputs_common.read_xls(xlsfile, sheet = 'File S1')
return filter(lambda l: len(l[-1]) > 0, map(lambda l: l[:7], tbl[2:]))
[docs]
def li2012_interactions():
"""
Converts table read by ``pypath.inputs.li2012.get_li2012`` to
list of interactions.
"""
result = []
data = get_li2012()
for l in data:
subs_protein = l[1].split('/')[0]
tk_protein = l[2].split()[0]
reader_protein = l[3].split()[0]
route = l[4]
result.append((
tk_protein,
subs_protein,
route,
'phosphorylation'
))
result.append((
subs_protein,
reader_protein,
route,
'phosphomotif_binding'
))
return [list(l) for l in common.unique_list(result)]
[docs]
def li2012_enzyme_substrate():
"""
Converts table read by ``pypath.inputs.li2012.get_li2012`` to
list of dicts of kinase-substrate interactions.
"""
result = []
data = get_li2012()
for l in data:
subs_protein = l[1].split('/')[0]
tk_protein = l[2].split()[0]
subs_resnum = int(common.non_digit.sub('', l[1].split('/')[1]))
result.append(
(
subs_protein, # substrate
tk_protein, # kinase
None, # instance
None, # start
None, # end
'Y', # residue letter
subs_resnum, # residue offset
)
)
result = [
dict(
zip(
[
'substrate', 'kinase', 'instance',
'start', 'end', 'resaa',
'resnum',
],
list(l)
)
)
for l in common.unique_list(result)
]
return result
[docs]
def li2012_dmi():
"""
Converts table read by ``pypath.inputs.li2012.get_li2012`` to
list of ``pypath.internals.intera.DomainMotif`` objects.
Translates GeneSymbols to UniProt IDs.
"""
result = []
se = seq.swissprot_seq(isoforms = True)
data = get_li2012()
for l in data:
subs_protein = l[1].split('/')[0]
tk_protein = l[2].split()[0]
reader_protein = l[3].split()[0]
subs_uniprots = mapping.map_name(
subs_protein,
'genesymbol',
'uniprot',
)
tk_uniprots = mapping.map_name(tk_protein, 'genesymbol', 'uniprot')
reader_uniprots = mapping.map_name(reader_protein, 'genesymbol',
'uniprot')
subs_resnum = int(common.non_digit.sub('', l[1].split('/')[1]))
for su in subs_uniprots:
if su in se:
subs_iso = None
for iso, s in iteritems(se[su].isof):
if se[su].get(subs_resnum, isoform = iso) == 'Y':
subs_iso = iso
break
if subs_iso:
start = min(1, subs_resnum - 7)
end = max(subs_resnum + 7, len(se[su].isof[subs_iso]))
for ku in tk_uniprots:
res = intera.Residue(
subs_resnum,
'Y',
su,
isoform = subs_iso,
)
mot = intera.Motif(
su,
start,
end,
isoform = subs_iso,
instance = se[su].get(
start,
end,
isoform = subs_iso
),
)
ptm = intera.Ptm(
su,
motif = mot,
residue = res,
isoform = subs_iso,
typ = 'phosphorylation',
evidences = 'Li2012'
)
dom = intera.Domain(ku)
dommot = intera.DomainMotif(
domain = dom,
ptm = ptm,
evidences = 'Li2012',
)
result.append(dommot)
return result
