#!/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/
#
import re
import itertools
import collections
import pypath.share.curl as curl
import pypath.resources.urls as urls
import pypath.inputs.common as inputs_common
import pypath.utils.mapping as mapping
[docs]
def ramilowski_interactions(putative = False):
"""
Downloads and processes ligand-receptor interactions from
Supplementary Table 2 of Ramilowski 2015.
Returns list of lists with ligand and receptor gene symbols, reference
and resources as elements.
"""
c = curl.Curl(urls.urls['rami']['url'], silent = False, large = True)
xlsname = c.fname
del(c)
raw = inputs_common.read_xls(xlsname, 'All.Pairs')[1:]
Ramilowski2015Interaction = collections.namedtuple(
'Ramilowski2015Interaction',
(
'ligand',
'receptor',
'references',
'resources',
),
)
return [
Ramilowski2015Interaction(
ligand = r[1],
receptor = r[3],
references = r[13].replace(' ', ''), # references
resources = ';'.join(
filter(len, itertools.chain(r[5:11], [r[15]]))
),
)
for r in raw
if not r[15].startswith('EXCLUDED') and (
putative or r[15] != 'putative'
)
]
return raw
[docs]
def ramilowski_locations(long_notes = False):
"""
Subcellular location annotations from Ramilowski 2015.
"""
reloc = re.compile(
r'([^\(]+[^\s^\(])'
r'\s?\('
r'?(?:(.*[^\)])?)'
r'\)?'
)
resep = re.compile(r'[\.;,]')
renote = re.compile(r'Note=([- \w\(\),\s\+\./%\'":;]*)')
sources = (
(4, 'UniProt'),
(5, 'HPRD'),
(7, 'LocTree3'),
(10, 'Consensus'),
(11, 'Consensus6'),
)
RamilowskiLocation = collections.namedtuple(
'RamilowskiLocation',
[
'location',
'source',
'tmh',
'note',
'long_note',
],
)
url = urls.urls['rami']['loc']
c = curl.Curl(url, silent = False, large = True)
_ = next(c.result)
result = collections.defaultdict(set)
for l in c.result:
l = l.strip('\n\r').split('\t')
for idx, source in sources:
locs = l[idx]
long_note = None
mnote = renote.search(locs)
if mnote:
long_note = mnote.groups()[0]
locs = renote.sub('', locs)
for loc in resep.split(locs):
if ':' in loc and 'GO:' not in loc:
loc = loc.split(':')[-1]
loc = loc.strip().replace('- ', '-').lower()
if (
not loc or
len(loc.split()) > 3 or
re.search(r'\d', loc) or
loc == 'n/a' or
any(
w in loc for w in
('tumor',)
)
):
continue
m = reloc.match(loc)
if not m:
continue
location, note = m.groups()
tmh = l[9].strip()
uniprots = mapping.map_name(l[3], 'uniprot', 'uniprot')
for uniprot in uniprots:
result[uniprot].add(
RamilowskiLocation(
location = (
location.lower().replace('=', '').strip()
),
source = source,
tmh = int(tmh) if tmh.isdigit() else None,
note = note,
long_note = long_note if long_notes else None,
)
)
return dict(result)
