import pandas as pd
import numpy as np
#base python packages
import os
from ptm_pose import database_interfacing as di
#identify package directory
package_dir = os.path.dirname(os.path.abspath(__file__))
resource_dir = package_dir + '/Resource_Files/'
#download modification conversion file (allows for conversion between modificaiton subtypes and clases)
modification_conversion = pd.read_csv(resource_dir + 'modification_conversion.csv')
#load ptm_coordinates dataframe, if present
if os.path.isfile(resource_dir + 'ptm_coordinates.csv.gz'):
ptm_coordinates = pd.read_csv(resource_dir + 'ptm_coordinates.csv.gz', dtype = {'Chromosome/scaffold name': str, 'PTM Position in Isoform': int, 'experimental evidence':str}, compression='gzip')
else:
print('ptm coordinates file not found, please make sure you did not delete this file')
ptm_coordinates = None
[docs]
def download_translator(save = False):
"""
Using rest API from UniProt, download mapping information between UniProt IDs, Gene names, and Ensembl Gene IDs. This information is used to convert between different gene identifiers and UniProt IDs
Parameters
----------
save : bool, optional
Whether to save the translator file locally. The default is False.
"""
uniprot_to_genename, uniprot_to_geneid = di.get_uniprot_to_gene()
translator = pd.DataFrame({'Gene stable ID': uniprot_to_geneid, 'Gene name':uniprot_to_genename})
if save:
translator.to_csv(resource_dir + 'translator.csv')
#replace empty strings with np.nan
translator = translator.replace('', np.nan)
#get uniprot to gene name and gene id dictionaries
uniprot_to_genename = translator['Gene name'].dropna().to_dict()
uniprot_to_geneid = translator['Gene stable ID'].dropna().to_dict()
return translator, uniprot_to_genename, uniprot_to_geneid
#load uniprot translator dataframe, process if need be
if os.path.isfile(resource_dir + 'translator.csv'):
translator = pd.read_csv(resource_dir + 'translator.csv', index_col=0)
#replace empty strings with np.nan
translator = translator.replace('', np.nan)
#get uniprot to gene name and gene id dictionaries
uniprot_to_genename = translator['Gene name'].dropna().to_dict()
uniprot_to_geneid = translator['Gene stable ID'].dropna().to_dict()
else:
print('Downloading mapping information between UniProt and Gene Names from UniProt. To permanently save the translator file, run pose_config.download_translator(save = True)')
translator, uniprot_to_genename, uniprot_to_geneid = download_translator()
#additional information
#annotation_function_dict = {'PhosphoSitePlus': {'Function':'add_PSP_regulatory_site_data', 'Process':'add_PSP_regulatory_site_data', 'Disease':'add_PSP_disease_association', 'Kinase':'add_PSP_kinase_substrate_data', 'Interactions': 'add_PSP_regulatory_site_data()', 'Perturbation':'add_PTMsigDB_data'}, 'ELM': {'Interactions':'add_ELM_interactions()', 'Motif Match':'add_ELM_motif_matches'},'PTMcode': {'Intraprotein': 'add_PTMcode_intraprotein', 'Interactions':'add_PTMcode_interprotein'},'PTMInt': {'Interactions':'add_PTMInt_data'},'RegPhos': {'Kinase': 'add_RegPhos_data'},'DEPOD': {'Phosphatase':'add_DEPOD_data'},'PTMsigDB':{'WikiPathway':'add_PTMsigDB_data', 'NetPath':'add_PTMsigDB_data','mSigDB':'add_PTMsigDB_data', 'Perturbation (DIA2)':'add_PTMsigDB_data', 'Perturbation (DIA)': 'add_PTMsigDB_data', 'Perturbation (PRM)':'add_PTMsigDB_data','Kinase':'add_PTMsigDB_data'}}
#manually curated dictionary to convert phosphositeplus names that are not standard gene names to UniProt IDs
psp_name_dict = {'Actinfilin':'Q6TDP4','14-3-3 zeta':'P63104','14-3-3 epsilon':'P62258','14-3-3 sigma':'P31947','P130Cas':'P56945','ENaC-beta':'P51168','ENaC-alpha':'P37088','14-3-3 eta':'Q04917','14-3-3 beta':'P31946', '14-3-3 gamma':'P61981', '14-3-3 theta':'P27348','Securin':'O95997','GPIbA':'P07359','occludin':'Q16625','ER-beta':'Q92731','53BP1': 'Q12888','4E-T':'Q9NRA8','53BP2':'Q13625','AP-2 beta':'Q92481','APAF':'O14727','Bcl-xL':'Q07817','C/EBP-epsilon':'Q15744','CREB':'P16220','Calmodulin':'P0DP23','Cortactin':'Q14247','DNAPK':'P78527', 'Diaphanous-1':'O60610', 'ER-alpha':'P03372', 'Exportin-1':'O14980', 'Ezrin':'P15311', 'H3':'Q6NXT2','HSP70':'P0DMV8;P0DMV9','IKKG':'Q9Y6K9', 'Ig-beta':'P40259','Ku80':'P13010','LC8':'Q96FJ2', 'MRLC2V':'P10916', 'Merlin':'P35240','NFkB-p105':'P19838', 'Rb':'P06400', 'RhoGDI alpha':'P52565', 'Rhodopsin':'P08100', 'SHP-1':'P29350', 'SHP-2':'Q06124','SLP76':'Q13094','SMRT':'Q9Y618','SRC-3':'Q9Y6Q9','STI1':'Q9BPY8','Vinculin':'P18206','beclin 1':'Q14457','claspin':'Q9HAW4', 'gp130':'P40189','leupaxin':'O60711','p14ARF':'Q8N726','rubicon':'Q92622','snRNP A':'P09661','snRNP B1':'P08579','snRNP C':'P09234','syntenin':'O00560;Q9H190','talin 1':'Q9Y490', 'ubiquitin':'P0CG47', '4E-BP1':'Q13541', 'ALK2':'Q04771', 'AMPKA1':'Q13131','AurA':'O14965','AurB':'Q96GD4', 'AurC':'Q9UQB9', 'C/EBP-beta':'P17676', 'CAMK1A':'Q14012', 'CHD-3 iso3':'Q12873', 'CK1A':'P48729', 'CK2B':'P67870', 'DAT':'Q01959', 'DJ-1':'Q99497', 'DOR-1':'P41143', 'DYN1':'Q05193','Desmoplakin':'P15924', 'Exportin-4':'Q9C0E2', 'FBPase':'P09467', 'FBPase 2':'O60825', 'G-alpha':'P63096', 'G-alpha 13':'Q14344', 'G-alpha i1':'P63096', 'G-beta 1':'P62873', 'G-beta 2':'P62879', 'G6PI':'P06744', 'GM130':'Q08379', 'GR':'P04150', 'H4':'P62805', 'HP1 alpha':'P45973', 'IkB-alpha':'P25963', 'IkB-beta':'Q15653', 'PPAR-gamma':'P37231', 'Claudin-1':'O95832', 'Claudin-2':'P57739', 'Cofilin-1':'P23528', 'K14':'P02533', 'K18':'P05783', 'K5':'P13647','K8':'P05787','Ku70':'P12956', 'Moesin':'P26038','N-WASP':'O00401','Nur77':'P22736','P38A':'Q16539','P38B':'Q15759', 'P70S6KB':'P23443','PGC-1 alpha':'Q9UBK2','PKHF1':'Q96S99','P38G':'P53778','PKCI':'P41743','PKCZ':'Q05513', 'PKG1':'Q13976', 'PTP-PEST':'Q05209','Plectin-1':'Q15149','RFA2':'P15927','SERCA2':'P16615','SH2-B-beta':'Q9NRF2', 'SNAP-alpha':'P54920', 'SPT16':'Q9BXB7', 'SPT6':'Q7KZ85','STEP':'P54829','STLK3':'Q9UEW8', 'Snail1':'O95863', 'Snail2':'O43623', 'Stargazin':'P62955','Survivin':'O15392','TARP':'P09693','TK':'P04183','TOM20':'Q15388','TR-alpha':'P10827','Titin':'Q8WZ42','Vimentin':'P08670','WASP':'P42768','ZAP':'Q7Z2W4', 'Zyxin':'Q15942', 'cIAP1':'Q13490','caveolin-1':'Q03135', 'coronin 2A':'Q92828', 'desmin':'P17661','eIF2-alpha':'Q9BY44', 'eIF2-beta':'P20042', 'eIF3-alpha':'O75822', 'eIF3-eta':'P55884', 'eIF3-zeta':'O15371', 'eNOS':'P29474', 'emerin':'P50402', 'epsin 1':'Q9Y6I3', 'glutaminase':'O94925','hnRNP A1':'P09651', 'hnRNP A2/B1':'P22626', 'hnRNP A3':'P51991','hnRNP D0':'Q14103', 'hnRNP E2':'Q15366','hnRNP P2':'P35637','hnRNP U':'Q00839', 'kindlin-2':'Q96AC1', 'kindlin-3':'Q86UX7','lamin A/C':'P02545', 'mucolipin 1':'Q9GZU1','nNOS':'Q8WY41','p21Cip1':'P38936', 'p27Kip1':'P46527','p47phox':'P14598','p90RSK':'Q15418','palladin':'Q8WX93','polybromo 1':'Q86U86', 'syndecan-4':'P31431', 'tensin 1 iso1':'Q9HBL0', 'utrophin':'P46939','DKFZp686L1814':'Q6MZP7', 'EB1':'Q15691', 'EB2':'Q15555', 'G-alpha i3':'P08754','HSP20':'O14558','HSP40':'P25685', 'Hic-5':'O43294', 'Ig-alpha':'P11912', 'LC3A':'Q9H492', 'LC3B':'Q9GZQ8', 'LC3C':'Q9BXW4','NFkB-p100':'Q00653','NFkB-p65':'Q04206','Pnk1':'Q96T60', 'RPT2':'P62191','EB3':'Q9UPY8'}
def flip_uniprot_dict(uniprot_dict):
"""
Given one of the uniprot id to gene name or gene id dictionaries, flip the dictionary so that the gene name or id is the key and the uniprot id is the value
"""
uniprot_dict = pd.DataFrame(uniprot_dict, index = ['Gene']).T.reset_index()
uniprot_dict['Gene'] = uniprot_dict['Gene'].str.split(' ')
uniprot_dict = uniprot_dict.explode('Gene')
uniprot_dict = uniprot_dict.set_index('Gene')['index'].to_dict()
return uniprot_dict