-
Notifications
You must be signed in to change notification settings - Fork 0
/
Copy pathAnnotateMutations.py
188 lines (166 loc) · 9.52 KB
/
AnnotateMutations.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
'''
Created on Mar 31, 2017
@author: husensofteng
'''
'''
Annotates a list of genomic coordinates using overlapping_tracks of cell lines corresponding to the tumor type given in each line
'''
import os, sys, shutil
from pybedtools import BedTool, set_tempdir
from collections import Counter
temp_dir = 'tmp_pybedtoos'
if not os.path.exists(temp_dir):
os.mkdir(temp_dir)
set_tempdir(temp_dir)
def get_muts_tracks_info(muts_input_file, tracks_dir, muts_dir_out, split_muts_file_by_chr=False):
muts_tracks_files = []
tracks_files = [x for x in os.listdir(tracks_dir) if x.endswith('.bed')]
if split_muts_file_by_chr:
muts_files = []
chr_ext = "." + tracks_files[0].split('.')[-1]
if os.path.exists(muts_dir_out):
muts_tracks_files = [muts_dir_out+'/'+x for x in os.listdir(muts_dir_out) if x.endswith('_overlapping_tracks.bed10')]
if len(muts_tracks_files)>0:
return muts_tracks_files
else:
os.mkdir(muts_dir_out)
muts_files = [muts_dir_out+'/'+x for x in os.listdir(muts_dir_out) if x.endswith(chr_ext)]
if len(muts_files)<=0:
os.system("""awk '{{print $0 >> "{muts_dir}/"$1"{chr_ext}"}}' {muts_file} """.format(muts_dir=muts_dir_out, chr_ext=chr_ext, muts_file=muts_input_file))
muts_files = [muts_dir_out+'/'+x for x in os.listdir(muts_dir_out) if x.endswith(chr_ext)]
print('muts_files: ', muts_files)
print('tracks_files: ', tracks_files)
for muts_file in muts_files:
if muts_file.split('/')[-1] in tracks_files:
muts_tracks_file = muts_file+"_overlapping_tracks.bed10"
if not os.path.exists(muts_tracks_file):
print("Intersecting and Grouping: ", muts_tracks_file)
BedTool(muts_file).intersect(BedTool(tracks_dir+'/'+tracks_files[tracks_files.index(muts_file.split('/')[-1])]), wo=True, loj=True).groupby(g=[1,2,3,4,5,6,7,8,9], c=13, o=['collapse']).saveas(muts_tracks_file)
muts_tracks_files.append(muts_tracks_file)
else:
for tracks_file in tracks_files:
if not os.path.exists(muts_dir_out):
os.mkdir(muts_dir_out)
muts_tracks_file = muts_dir_out+'/'+tracks_file+"_overlapping_tracks.bed10"
if not os.path.exists(muts_tracks_file):
print("Intersecting and Grouping: ", muts_tracks_file)
BedTool(muts_input_file).intersect(BedTool(tracks_dir+'/'+tracks_file), wo=True, loj=True).groupby(g=[1,2,3,4,5,6,7,8,9], c=13, o=['collapse']).saveas(muts_tracks_file)
muts_tracks_files.append(muts_tracks_file)
print('muts_tracks_files: ', muts_tracks_files)
return muts_tracks_files
def annotate_muts(muts_tracks_file, muts_tracks_ouput_file, tissue_cell_assays, matching_cell_name_representative_dict, cancer_type_index = 9, tracks_info_index = 3):
with open(muts_tracks_file, 'r') as mut_tracks_ifile, open(muts_tracks_ouput_file, 'w') as mut_tracks_ofile:
l = mut_tracks_ifile.readline().strip().split('\t')
while len(l)>cancer_type_index:
annotations = {}
tracks = l[tracks_info_index].split(',')
for track in tracks:
#print(track, l[cancer_type_index])
cellname = track.split('#')[0]
try:
cellname = matching_cell_name_representative_dict[cellname][0]
except KeyError:
continue
try:
if cellname in tissue_cell_assays[l[cancer_type_index]]:
try:
annotations[track.split('#')[1]].append(float(track.split('#')[2]))#annotations[track.split('#')[1]].append(cellname+"#"+'#'.join(track.split('#')[1:]))
except ValueError:
annotations[track.split('#')[1]].append(track.split('#')[2])
except KeyError:
try:
annotations[track.split('#')[1]] = [float(track.split('#')[2])]
except ValueError:
annotations[track.split('#')[1]] = [track.split('#')[2]]
except IndexError:
annotations[track.split('#')[1]] = [1.0]
except IndexError:
annotations[track.split('#')[1]] = [1.0]
except KeyError:
print("Cancer type not found: ", l[cancer_type_index])
print(track)
print(cellname)
print(l[cancer_type_index])
print(tissue_cell_assays[l[cancer_type_index]])
break
for anno in sorted(annotations.keys()):
if anno=='TFBinding':
annotations[anno] = ';'.join(set(annotations[anno]))
continue
try:
annotations[anno] = str(sum(annotations[anno])/(len(annotations[anno])*1.0))
except (ValueError, TypeError):
annotations[anno] = Counter(annotations[anno]).most_common(1)[0][0]
annotations_combined = [x+":"+annotations[x] for x in sorted(annotations.keys())]
if len(annotations_combined)==0:
annotations_combined = ['NaN']
mut_tracks_ofile.write('\t'.join(l[0:9]) + '\t' + '|'.join(annotations_combined) + '\n')
l = mut_tracks_ifile.readline().strip().split('\t')
return muts_tracks_ouput_file
def retreive_key_values_from_dict_file(dict_input_file, key_value_sep='=', values_sep=','):#TFFamilyName TF_name
"Retrieves the key and its values"
key_values_dict = {}
value_key_dict = {}
with open(dict_input_file, 'r') as dict_input_file_infile:
lines = dict_input_file_infile.readlines()
for line in lines:
if line.startswith('//') or line.startswith('#'):# or '=' not in line:
continue
sl = line.strip().split(key_value_sep)
key_value = sl[0].strip()
if key_value not in key_values_dict.keys():
key_values_dict[key_value] = []
if key_value not in value_key_dict:
value_key_dict[key_value]=[key_value]
if len(sl)>1:
for s in sl[1].split(values_sep):
if s.strip()!="" and s.strip() not in key_values_dict[key_value]:
key_values_dict[key_value].append(s.strip())
if s.strip()!="":
if s.strip() not in value_key_dict:
value_key_dict[s.strip()]=[]
value_key_dict[s.strip()].append(key_value)
return key_values_dict, value_key_dict
def get_tissue_cell_mappings(tissue_cell_mappings_file, matching_cell_name_representative_dict, key_value_sep='=', values_sep=',', cell_assay_sepe=':'):
tissue_cell_assays = {}
with open(tissue_cell_mappings_file, 'r') as ifile:
lines = ifile.readlines()
for line in lines:
if line.startswith('//') or line.startswith('#') or '=' not in line:
continue
sl = line.strip().split(key_value_sep)
key_value = sl[0]
if key_value not in tissue_cell_assays.keys():
tissue_cell_assays[key_value] = []
for s in sl[1].split(values_sep):
try:
cell = matching_cell_name_representative_dict[s.split(':')[0]][0]#get the rep name of the cell
if cell not in tissue_cell_assays[key_value]:
tissue_cell_assays[key_value].append(cell)
except KeyError:
continue
return tissue_cell_assays
def get_annotated_muts(muts_input_file, tracks_dir, muts_out):
cell_names_to_use = 'CellNamesDict'
tissue_cell_mappings_file='TissueCellMatches'
representative_cell_name_matchings_dict, matching_cell_name_representative_dict = retreive_key_values_from_dict_file(cell_names_to_use)
tissue_cell_assays = get_tissue_cell_mappings(tissue_cell_mappings_file=tissue_cell_mappings_file,
matching_cell_name_representative_dict=matching_cell_name_representative_dict,
key_value_sep='=', values_sep=',', cell_assay_sepe=':')
if not os.path.exists(muts_out):
muts_tracks_files = get_muts_tracks_info(muts_input_file=muts_input_file, tracks_dir=tracks_dir, muts_dir_out=muts_out+'_tmp')
with open(muts_out, 'w') as muts_ofile:
for muts_tracks_file in muts_tracks_files:
muts_tracks_ouput_file = muts_tracks_file+"_annotated"
print("Annotating: ", muts_tracks_ouput_file)
annotate_muts(muts_tracks_file, muts_tracks_ouput_file, tissue_cell_assays, matching_cell_name_representative_dict, cancer_type_index = 5, tracks_info_index = 9)
with open(muts_tracks_ouput_file, 'r') as muts_tracks_ouput_ifile:
muts_ofile.write(muts_tracks_ouput_ifile.read())
#if os.path.exists(muts_out+'_tmp'):
# shutil.rmtree(muts_out+'_tmp')
return muts_out
if __name__ == '__main__':
muts_input_file = sys.argv[1]
tracks_dir = sys.argv[2]
muts_out = sys.argv[3]#muts_input_file+'_annotations'
get_annotated_muts(muts_input_file, tracks_dir, muts_out)