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
189
190
191
192
193
194
195
196
|
#!/usr/bin/python
"""
Convert .geno files to json
This file goes through all of the genofiles in the genofile directory (.geno)
and converts them to json files that are used when running the marker regression
code
"""
import sys
sys.path.append("..")
import os
import glob
import traceback
import gzip
#import numpy as np
#from pyLMM import lmm
import simplejson as json
from pprint import pformat as pf
#from utility.tools import flat_files
class EmptyConfigurations(Exception): pass
class Marker(object):
def __init__(self):
self.name = None
self.chr = None
self.cM = None
self.Mb = None
self.genotypes = []
class ConvertGenoFile(object):
def __init__(self, input_file, output_file):
self.input_file = input_file
self.output_file = output_file
self.mb_exists = False
self.cm_exists = False
self.markers = []
self.latest_row_pos = None
self.latest_col_pos = None
self.latest_row_value = None
self.latest_col_value = None
def convert(self):
self.haplotype_notation = {
'@mat': "1",
'@pat': "0",
'@het': "0.5",
'@unk': "NA"
}
self.configurations = {}
#self.skipped_cols = 3
#if self.input_file.endswith(".geno.gz"):
# print("self.input_file: ", self.input_file)
# self.input_fh = gzip.open(self.input_file)
#else:
self.input_fh = open(self.input_file)
with open(self.output_file, "w") as self.output_fh:
#if self.file_type == "geno":
self.process_csv()
#elif self.file_type == "snps":
# self.process_snps_file()
def process_csv(self):
for row_count, row in enumerate(self.process_rows()):
row_items = row.split("\t")
this_marker = Marker()
this_marker.name = row_items[1]
this_marker.chr = row_items[0]
if self.cm_exists and self.mb_exists:
this_marker.cM = row_items[2]
this_marker.Mb = row_items[3]
genotypes = row_items[4:]
elif self.cm_exists:
this_marker.cM = row_items[2]
genotypes = row_items[3:]
elif self.mb_exists:
this_marker.Mb = row_items[2]
genotypes = row_items[3:]
else:
genotypes = row_items[2:]
for item_count, genotype in enumerate(genotypes):
if genotype.upper() in self.configurations:
this_marker.genotypes.append(self.configurations[genotype.upper()])
else:
this_marker.genotypes.append("NA")
#print("this_marker is:", pf(this_marker.__dict__))
#if this_marker.chr == "14":
self.markers.append(this_marker.__dict__)
with open(self.output_file, 'w') as fh:
json.dump(self.markers, fh, indent=" ", sort_keys=True)
# print('configurations:', str(configurations))
#self.latest_col_pos = item_count + self.skipped_cols
#self.latest_col_value = item
#if item_count != 0:
# self.output_fh.write(" ")
#self.output_fh.write(self.configurations[item.upper()])
#self.output_fh.write("\n")
def process_rows(self):
for self.latest_row_pos, row in enumerate(self.input_fh):
#if self.input_file.endswith(".geno.gz"):
# print("row: ", row)
self.latest_row_value = row
# Take care of headers
if not row.strip():
continue
if row.startswith('#'):
continue
if row.startswith('Chr'):
if 'Mb' in row.split():
self.mb_exists = True
if 'cM' in row.split():
self.cm_exists = True
continue
if row.startswith('@'):
key, _separater, value = row.partition(':')
key = key.strip()
value = value.strip()
if key in self.haplotype_notation:
self.configurations[value] = self.haplotype_notation[key]
continue
if not len(self.configurations):
raise EmptyConfigurations
yield row
@classmethod
def process_all(cls, old_directory, new_directory):
os.chdir(old_directory)
for input_file in glob.glob("*"):
if not input_file.endswith(('geno', '.geno.gz')):
continue
group_name = ".".join(input_file.split('.')[:-1])
output_file = os.path.join(new_directory, group_name + ".json")
print("%s -> %s" % (
os.path.join(old_directory, input_file), output_file))
convertob = ConvertGenoFile(input_file, output_file)
try:
convertob.convert()
except EmptyConfigurations as why:
print(" No config info? Continuing...")
#excepted = True
continue
except Exception as why:
print(" Exception:", why)
print(traceback.print_exc())
print(" Found in row %s at tabular column %s" % (convertob.latest_row_pos,
convertob.latest_col_pos))
print(" Column is:", convertob.latest_col_value)
print(" Row is:", convertob.latest_row_value)
break
#def process_snps_file(cls, snps_file, new_directory):
# output_file = os.path.join(new_directory, "mouse_families.json")
# print("%s -> %s" % (snps_file, output_file))
# convertob = ConvertGenoFile(input_file, output_file)
if __name__=="__main__":
Old_Geno_Directory = """/export/local/home/zas1024/gn2-zach/genotype_files/genotype"""
New_Geno_Directory = """/export/local/home/zas1024/gn2-zach/genotype_files/genotype/json"""
#Input_File = """/home/zas1024/gene/genotype_files/genotypes/BXD.geno"""
#Output_File = """/home/zas1024/gene/wqflask/wqflask/pylmm/data/bxd.snps"""
#convertob = ConvertGenoFile("/home/zas1024/gene/genotype_files/genotypes/SRxSHRSPF2.geno", "/home/zas1024/gene/genotype_files/new_genotypes/SRxSHRSPF2.json")
#convertob.convert()
ConvertGenoFile.process_all(Old_Geno_Directory, New_Geno_Directory)
#ConvertGenoFiles(Geno_Directory)
#process_csv(Input_File, Output_File)
|
