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| import ssl | |
| import requests as r | |
| from decimal import * | |
| import numpy as np | |
| def add_annotations(dataframe): | |
| print('Downloading UniProt sequence annotations...\n') | |
| ssl._create_default_https_context = ssl._create_unverified_context | |
| original_annot_name = ['DISULFID', 'INIT_MET', 'INTRAMEM', 'VARIANT', 'DNA_BIND', 'ACT_SITE', 'NP_BIND', 'LIPID', | |
| 'SITE', | |
| 'TRANSMEM', 'CROSSLNK', 'MUTAGEN', 'STRAND', 'HELIX', 'TURN', 'METAL', 'REPEAT', 'TOPO_DOM', | |
| 'CA_BIND', 'BINDING', 'REGION', 'SIGNAL', 'MOD_RES', 'ZN_FING', 'MOTIF', 'COILED', 'PEPTIDE', | |
| 'TRANSIT', 'CARBOHYD', 'PROPEP'] | |
| annotation_list = ['disulfide', 'intMet', 'intramembrane', 'naturalVariant', 'dnaBinding', 'activeSite', | |
| 'nucleotideBinding', 'lipidation', 'site', 'transmembrane', 'crosslink', 'mutagenesis', 'strand', | |
| 'helix', 'turn', 'metalBinding', 'repeat', 'topologicalDomain', 'caBinding', 'bindingSite', | |
| 'region', | |
| 'signalPeptide', 'modifiedResidue', 'zincFinger', 'motif', 'coiledCoil', 'peptide', | |
| 'transitPeptide', 'glycosylation', 'propeptide'] | |
| dataframe = dataframe.reset_index().drop(['index'], axis=1) | |
| for annot in original_annot_name: | |
| dataframe[annot] = '' | |
| for protein in list(set(dataframe.uniprotID.to_list())): | |
| print('Downloading annotations for ' + protein) | |
| uniprot_entry = r.get("http://www.uniprot.org/uniprot/" + protein + ".txt") | |
| uniprot_entry = uniprot_entry.text.split('\n') | |
| annot_for_protein = [] | |
| for annotation in original_annot_name: | |
| for line in uniprot_entry: | |
| if annotation.strip() in line and line.startswith( | |
| 'FT') and 'evidence' not in line and 'ECO' not in line and 'note' not in line: | |
| annot_for_protein.append(list(filter(None, line.split(' ')))[1:]) | |
| for select in annot_for_protein: | |
| if select[0] not in dataframe.columns: | |
| dataframe.loc[dataframe.uniprotID == protein, select[0]] = str((select[1] + '; ')) | |
| else: | |
| dataframe.loc[dataframe.uniprotID == protein, select[0]] += str((select[1] + '; ')) | |
| for i in range(len(original_annot_name)): | |
| dataframe = dataframe.rename(columns={original_annot_name[i]: annotation_list[i]}) | |
| # Fix annotation positions | |
| print('Processing positions...\n') | |
| for i in dataframe.index: | |
| for annot in dataframe.columns[-30:]: | |
| if annot != 'disulfide': | |
| if dataframe.at[i, annot] != 'nan': | |
| dataframe.at[i, annot] = ([x for x in [k.strip() for k in dataframe.at[i, annot].split(';')] if x]) | |
| if '..' not in str(dataframe.at[i, annot]): | |
| pass | |
| elif '..' in str(dataframe.at[i, annot]): | |
| dataframe.at[i, annot] = str(dataframe.at[i, annot]).replace('..', '-') | |
| else: | |
| disulfide_annot = [] | |
| if dataframe.at[i, annot] != 'nan': | |
| dataframe.at[i, annot]= dataframe.at[i, annot].split(';') | |
| dataframe.at[i, annot] = [i.split('..') for i in dataframe.at[i, annot]] | |
| dataframe.at[i, annot] =[e for v in dataframe.at[i, annot] for e in v] | |
| dataframe.at[i, annot] = [i for i in dataframe.at[i, annot] if i != ' '] | |
| # Add binary annotations | |
| print('Adding binary annotations...\n') | |
| dataframe = dataframe.astype('str') | |
| for i in dataframe.index: | |
| for k in annotation_list: # get the positions of each attribute as a list | |
| txt = k + 'Binary' | |
| dataframe.at[i, txt] = Decimal('nan') | |
| try: | |
| for positions in dataframe.at[i, k].split(','): | |
| position = positions.strip('[').strip(']').replace("'", "") | |
| if position != 'nan' and position != '' and '-' not in position and int( | |
| dataframe.at[i, 'pos']) == int(position): | |
| dataframe.at[i, txt] = '1' | |
| break | |
| elif position != 'nan' and position != '' and '-' not in position and int( | |
| dataframe.at[i, 'pos']) != int(position): | |
| dataframe.at[i, txt] = '0' | |
| elif position != 'nan' and position != '' and '-' in position: | |
| if int(position.split('-')[0]) < int(dataframe.at[i, 'pos']) < int(position.split('-')[1]): | |
| dataframe.at[i, txt] = '1' | |
| break | |
| else: | |
| dataframe.at[i, txt] = '0' | |
| except: | |
| ValueError | |
| # Final corrections | |
| dataframe = dataframe.replace({'[\'?\']': 'nan'}) | |
| dataframe = dataframe.replace({'[]': 'nan'}) | |
| return dataframe | |