Create add_annotations.py

code/add_annotations.py

@@ -0,0 +1,211 @@
+import ssl
+import requests as r
+from decimal import *
+import numpy as np
+import pandas as pd
+import json
+import ast
+
+UNIPROT_ANNOTATION_COLS =  ['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', 'disulfideBinary',
+     'intMetBinary', 'intramembraneBinary',
+     'naturalVariantBinary', 'dnaBindingBinary', 'activeSiteBinary',
+     'nucleotideBindingBinary', 'lipidationBinary', 'siteBinary',
+     'transmembraneBinary', 'crosslinkBinary', 'mutagenesisBinary',
+     'strandBinary', 'helixBinary', 'turnBinary', 'metalBindingBinary',
+     'repeatBinary', 'topologicalDomainBinary', 'caBindingBinary',
+     'bindingSiteBinary', 'regionBinary', 'signalPeptideBinary',
+     'modifiedResidueBinary', 'zincFingerBinary', 'motifBinary',
+     'coiledCoilBinary', 'peptideBinary', 'transitPeptideBinary',
+     'glycosylationBinary', 'propeptideBinary']
+
+annotation_list = UNIPROT_ANNOTATION_COLS[0:30]
+
+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 protein in list(set(dataframe.uniprotID.to_list())):
+        print('Retieving 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:])
+        annotations_present = []
+        for select in annot_for_protein:
+            if select[0] not in annotations_present:
+                dataframe.loc[dataframe.uniprotID == protein, select[0]] = str((select[1].replace('..', '-') + '; '))
+                annotations_present.append(select[0])
+            else:
+                dataframe.loc[dataframe.uniprotID == protein, select[0]] += str((select[1].replace('..', '-') + '; '))
+        missingAnnotations = list(set(original_annot_name) - set(annotations_present))
+        for miss in missingAnnotations:
+            dataframe.loc[dataframe.uniprotID == protein, miss] = np.NaN
+
+    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:
+        all_positions = []
+        for annot in annotation_list:
+            if (annot != 'disulfide') & (pd.isna(dataframe.at[i, annot]) != True):
+                dataframe.at[i, annot] = [x for x in [k.strip() for k in dataframe.at[i, annot].split(';')] if x]
+                all_positions.append(dataframe.at[i, annot])
+            elif (annot == 'disulfide') & (pd.isna(dataframe.at[i, annot]) != True):
+                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 != ' ']
+                all_positions.append(dataframe.at[i, annot])
+            dataframe.at[i, annot] = str(dataframe.at[i, annot])
+        all_positions = [item for sublist in all_positions for item in sublist]
+        updated_allPos = []
+        for pos in all_positions:
+            if '-' in pos:
+                first = pos.split('-')[0]
+                second = pos.split('-')[1]
+                newPos = list(range(int(first), int(second)+1))
+                updated_allPos += newPos
+            else:
+                updated_allPos.append(int(pos))
+        updated_allPos.append(dataframe.at[i, 'pos'])
+        updated_allPos.append(dataframe.at[i, 'domEnd'])
+        updated_allPos.append(dataframe.at[i, 'domStart'])
+        updated_allPos = [int(i) for i in updated_allPos]
+        dataframe.loc[i, 'POSITIONS'] = str(list(set(updated_allPos)))
+
+    # Add binary annotations
+    print('Adding binary annotations...\n')
+    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] = np.NaN
+            try:
+                for positions in dataframe.at[i, k].split(','):
+                    position = positions.strip('[').strip(']').replace("'", "")
+                    if (position != np.NaN) and (position != '') and ('-' not in position) and (int(
+                            dataframe.at[i, 'pos']) == int(position)):
+                        dataframe.at[i, txt] = '1'
+                        break
+                    elif (position != np.NaN) and (position != '') and ('-' not in position) and (int(
+                            dataframe.at[i, 'pos']) != int(position)):
+                        dataframe.at[i, txt] = '0'
+                    elif (position != np.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({'[\'?\']': np.NaN})
+    dataframe = dataframe.replace({'[]': np.NaN})
+    dataframe = dataframe.replace({'': np.NaN})
+    dataframe = dataframe.fillna(np.NaN)
+    return dataframe
+
+def changeUPtoPDB(dataframe):
+    for i in dataframe.index:
+        for col in annotation_list:
+            newList = []
+            if dataframe.at[i, col] != np.NaN:
+                if type(dataframe.at[i, col]) == str:
+                    list_v = dataframe.at[i, col][1:-1].split(',')
+                    positionList = [i.strip().strip('\'') for i in list_v]
+                elif type(dataframe.at[i, col]) == list:
+                    positionList = dataframe.at[i, col]
+                else:
+                    positionList = []
+                for position in positionList:
+                    if '-' in position:
+                        all_annots = list(range(int(position.split('-')[0]), int(position.split('-')[1])+1))
+                        for annot in all_annots:
+                            try:
+                                newList.append(ast.literal_eval(dataframe.at[i, 'MATCHDICT'])[str(annot)])
+                            except KeyError:
+                                pass
+                            except TypeError:
+                                pass
+                    else:
+                        try:
+                            newList.append(ast.literal_eval(dataframe.at[i, 'MATCHDICT'])[str(position)])
+                        except KeyError:
+                            pass
+                        except TypeError:
+                            pass
+            dataframe.loc[i, col] = str(newList)
+    return dataframe
+
+
+def changeUPtoModels(dataframe):
+    dataframe.fillna(np.NaN, inplace=True)
+    for i in dataframe.index:
+        for col in annotation_list:
+            newList = []
+            if (dataframe.at[i, col] != np.NaN) or (type(dataframe.at[i, col]) != 'float'):
+                if (type(dataframe.at[i, col]) == str) and  (str(dataframe.at[i, col]) != 'nan') :
+                    list_v = dataframe.at[i, col][1:-1].split(',')
+                    positionList = [i.strip().strip('\'') for i in list_v]
+                elif type(dataframe.at[i, col]) == list:
+                    positionList = dataframe.at[i, col]
+                else:
+                    positionList = []
+
+                if positionList != []:
+                    for position in positionList:
+                        if '-' in position:
+                            all_annots = list(range(int(position.split('-')[0]), int(position.split('-')[1])+1))
+                            newList += all_annots
+                        else:
+                            newList.append(str(position))
+                            pass
+                else:
+                    all_annots = np.NaN
+            else:
+                all_annots = np.NaN
+            newList = [str(i) for i in newList]
+
+            dataframe.loc[i, col] = str(newList)
+
+    return dataframe
+
+
+def isZeroDistance(data):
+    data.fillna(np.NaN, inplace=True)
+    for i in data.index:
+
+        for col in UNIPROT_ANNOTATION_COLS[0:30]:
+            if data.at[i, col] != np.NaN:
+                if type(data.at[i, col]) != 'dict':
+                    annotList = ast.literal_eval(data.at[i, col])
+                else:
+                    annotList = data.at[i, col]
+                annotList = [int(i.strip()) for i in annotList if i != 'null']
+                if int(data.at[i, 'pos']) in annotList:
+                    data.at[i, col] = 'hit'
+    return data