#!/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 itertools
import collections
import pypath.inputs.common as inputs_common
import pypath.resources.urls as urls
import pypath.utils.mapping as mapping
import pypath.utils.orthology as orthology
import pypath.share.common as common
import pypath.inputs.cell as cell_input
[docs]
def embrace_raw():
"""
Returns Supplementary Table S11 from 10.1016/j.isci.2019.10.026
(Sheikh et al. 2019) as a list of tuples.
"""
path = cell_input.cell_supplementary(
supp_url = urls.urls['embrace']['url'],
article_url = urls.urls['embrace']['article'],
)
content = inputs_common.read_xls(path)
EmbraceRawRecord = collections.namedtuple(
'EmbraceRawRecord',
content[0]
)
return [
EmbraceRawRecord(*(line[:2] + [int(float(n)) for n in line[2:]]))
for line in
content[1:]
]
def _embrace_id_translation(mouse_genesymbol, organism = 9606):
uniprots = mapping.map_name(
mouse_genesymbol,
'genesymbol',
'uniprot',
ncbi_tax_id = 10090,
)
if organism != 10090:
uniprots = orthology.translate(
uniprots,
target = organism,
source = 10090,
)
return uniprots or [None]
[docs]
def embrace_translated(organism = 9606):
"""
Returns Supplementary Table S11 from 10.1016/j.isci.2019.10.026
(Sheikh et al. 2019) translated to UniProt IDs of the requested organism.
"""
raw = embrace_raw()
record = raw[0].__class__
result = []
for row in raw:
ligands = _embrace_id_translation(
row.ligand_symbol,
organism = organism,
)
receptors = _embrace_id_translation(
row.receptor_symbol,
organism = organism,
)
for ligand, receptor in itertools.product(ligands, receptors):
result.append(
record(*((ligand, receptor) + row[2:]))
)
return result
[docs]
def embrace_interactions(organism = 9606):
"""
Returns ligand-receptor interactions from Supplementary Table S11 of
10.1016/j.isci.2019.10.026 (Sheikh et al. 2019) translated to UniProt IDs
of the requested organism.
"""
EmbraceInteraction = collections.namedtuple(
'EmbraceInteraction',
[
'ligand',
'receptor',
]
)
return [
EmbraceInteraction(*rec[:2])
for rec in embrace_translated(organism = organism)
if rec[0] and rec[1]
]
[docs]
def embrace_annotations(organism = 9606, ncbi_tax_id = None):
"""
Returns protein annotations from Supplementary Table S11 of
10.1016/j.isci.2019.10.026 (Sheikh et al. 2019) translated to UniProt IDs
of the requested organism.
Returns dict with UniProt IDs as keys and sets of annotation tuples as
values.
"""
def _get_value(rec, mainclass, celltype):
return bool(getattr(rec, '%s_%s' % (celltype, mainclass)))
EmbraceAnnotation = collections.namedtuple(
'EmbraceAnnotation',
[
'mainclass',
'neuron',
'mural_cell',
'microglia',
'endothelial_cell',
]
)
organism = ncbi_tax_id or organism
result = collections.defaultdict(set)
for rec in embrace_translated(organism = organism):
for mainclass in ('ligand', 'receptor'):
identifier = getattr(rec, '%s_symbol' % mainclass)
if not identifier:
continue
result[identifier].add(
EmbraceAnnotation(
mainclass = mainclass,
neuron = _get_value(rec, mainclass, 'N'),
mural_cell = _get_value(rec, mainclass, 'P'),
microglia = _get_value(rec, mainclass, 'M'),
endothelial_cell = _get_value(rec, mainclass, 'EC'),
)
)
return dict(result)
