#!/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.session as session_mod
_logger = session_mod.Logger(name = 'db_categories')
_log = _logger._log
categories = {
'Vidal HI-III': 'i',
'CancerCellMap': 'p',
'InnateDB': 'i',
'SPIKE': 'p',
'LMPID': 'm',
'DIP': 'i',
'HPRD': 'i',
'HPRD-phos': 'm',
'PDZBase': 'p',
'dbPTM': 'm',
'MatrixDB': 'i',
'DOMINO': 'm',
'SIGNOR': 'p',
'Macrophage': 'p',
'Adhesome': 'p',
'NetPath': 'r',
'ELM': 'm',
'SignaLink2': 'p',
'SignaLink3': 'p',
'NRF2ome': 'p',
'DEPOD': 'm',
'phosphoELM': 'm',
'MPPI': 'i',
'Guide2Pharma': 'l',
'Guide2Pharma_CP': 'l',
'TRIP': 'p',
'AlzPathway': 'r',
'PhosphoSite': 'm',
'CA1': 'p',
'NCI-PID': 'r',
'DeathDomain': 'p',
'ARN': 'p',
'BioGRID': 'i',
'IntAct': 'i',
'Reactome': 'r',
'ACSN': 'r',
'WikiPathways': 'r',
'TRIP': 'p',
'PANTHER': 'r',
'ABS': 't',
'MIMP': 'm',
'PhosphoNetworks': 'm',
'Li2012': 'm',
'PhosphoPoint': 'm',
'PhosphoSite_noref': 'm',
'Ramilowski2015': 'l',
'Kirouac2010': 'l',
'HPMR': 'l',
'CellPhoneDB': 'l',
'Guide2Pharma': 'l',
'GO_lig_rec': 'l',
'guidetopharmacology.org': 'l',
'UniProt': 'l',
'InnateDB-All': 'i',
'MINT': 'i',
'HIPPIE': 'i',
'Wang': 'p',
'KEGG': 'p',
'ProtMapper': 'm',
'RLIMS-P': 'm',
'REACH': 'm',
# TF-target
'ENCODE-distal': 't',
'PAZAR': 't',
'ENCODE-proximal': 't',
'ORegAnno': 't',
'HTRI': 't',
'ARACNe-GTEx': 't',
'DoRothEA_reviews': 't',
'FANTOM4': 't',
'HOCOMOCO-v11': 't',
'HTRIdb': 't',
'JASPAR-v2018': 't',
'NFIRegulomeDB': 't',
'ReMap': 't',
'RegNetwork': 't',
'TFactS': 't',
'TFe': 't',
'TRED': 't',
'TRRD': 't',
'TRRUST': 't',
'DoRothEA': 't',
# miRNA-mRNA
'miR2Disease': 'n',
'miRDeathDB': 'n',
'miRecords': 'n',
'miRTarBase': 'n',
'ncRDeathDB': 'nw',
# TF-miRNA
'TransmiR': 'u',
'ENCODE_tf-mirna': 'u',
# lncRNA-mRNA
'LncRNADisease': 'w',
'lncrnadb': 'w',
}
p = set()
i = set()
r = set()
m = set()
t = set()
l = set()
n = set() # miRNA-target
u = set() # TF-mirna
w = set() # lncRNA-target
for db, cats in iteritems(categories):
for c in cats:
locals()[c].add(db)
catnames = {
'm': 'Enzyme-substrate',
'p': 'Activity flow',
'i': 'Undirected PPI',
'r': 'Process description',
't': 'Transcription',
'l': 'Ligand-receptor',
'n': 'miRNA-mRNA',
'u': 'TF-miRNA',
'w': 'lncRNA-mRNA',
'': 'No category',
None: 'No category',
}
catletters = dict(map(reversed, iteritems(catnames)))
pathway_resources = p
interaction_resources = i
ptm_resources = m
reaction_resources = r
transctiption_resources = t
ligand_receptor_resources = l
[docs]
def get_categories(database, names = False, top = True):
result = (
{letter for letter in categories[database]}
if database in categories else
(
(
get_categories(
'_'.join(
reversed(tuple(reversed(database.split('_')))[:-1])
),
top = False,
)
) or (
get_categories(
'_'.join(database.split('_')[:-1]),
top = False,
)
)
)
if '_' in database else
set()
)
if not result and top:
_log(
'Could not find database `%s` in any '
'of the categories.' % database
)
if names:
result = {catnames[cat] for cat in result}
return result
[docs]
def get_category(database):
db_categories = get_categories(database)
return list(db_categories)[0] if db_categories else None
