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# CTL analysis for GN2
# Author / Maintainer: Danny Arends <Danny.Arends@gmail.com>
from __future__ import print_function, division, absolute_import
import sys
import os
import glob
import traceback
import gzip
import simplejson as json
from pprint import pformat as pf
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):
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
self.input_fh = open(input_file)
print("!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!")
self.haplotype_notation = {
'@mat': "3",
'@pat': "1",
'@het': "2",
'@unk': "NA"
}
self.configurations = {}
def process_rows(self):
for self.latest_row_pos, row in enumerate(self.input_fh):
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
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")
self.markers.append(this_marker.__dict__)
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