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#!/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
"""
from __future__ import print_function, division, absolute_import
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
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_files):
self.input_file = input_file
self.output_files = output_files
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_files[0], "w") as self.geno_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().strip() in self.configurations:
this_marker.genotypes.append(self.configurations[genotype.upper().strip()])
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__)
self.write_to_bimbam()
# 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 write_to_bimbam(self):
with open(self.output_files[0], "w") as geno_fh:
# geno_fh.write(str(len(self.sample_list)) + "\n")
# geno_fh.write("2\n")
# geno_fh.write("IND")
# for sample in self.sample_list:
# geno_fh.write(" " + sample)
# geno_fh.write("\n")
for marker in self.markers:
geno_fh.write(marker['name'])
geno_fh.write(", X, Y")
geno_fh.write(", " + ", ".join(marker['genotypes']))
geno_fh.write("\n")
#pheno_fh = open(self.output_files[1], 'w')
with open(self.output_files[1], "w") as pheno_fh:
for sample in self.sample_list:
pheno_fh.write("1\n")
with open(self.output_files[2], "w") as snp_fh:
for marker in self.markers:
if self.mb_exists:
snp_fh.write(marker['name'] +", " + str(int(float(marker['Mb'])*1000000)) + ", " + marker['chr'] + "\n")
else:
snp_fh.write(marker['name'] +", " + str(int(float(marker['cM'])*1000000)) + ", " + marker['chr'] + "\n")
def get_sample_list(self, row_contents):
self.sample_list = []
if self.mb_exists:
if self.cm_exists:
self.sample_list = row_contents[4:]
else:
self.sample_list = row_contents[3:]
else:
if self.cm_exists:
self.sample_list = row_contents[3:]
else:
self.sample_list = row_contents[2:]
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
self.get_sample_list(row.split())
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])
geno_output_file = os.path.join(new_directory, group_name + "_geno.txt")
pheno_output_file = os.path.join(new_directory, group_name + "_pheno.txt")
snp_output_file = os.path.join(new_directory, group_name + "_snps.txt")
output_files = [geno_output_file, pheno_output_file, snp_output_file]
print("%s -> %s" % (
os.path.join(old_directory, input_file), geno_output_file))
convertob = ConvertGenoFile(input_file, output_files)
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 = """/home/zas1024/genotype_files/genotype/"""
New_Geno_Directory = """/home/zas1024/genotype_files/genotype/bimbam/"""
#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)
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