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"Base Class: Markers - "
import math
from utility.tools import locate, flat_files
class Markers:
"""Todo: Build in cacheing so it saves us reading the same file more than once"""
def __init__(self, name):
json_data_fh = open(locate(name + ".json", 'genotype/json'))
markers = []
with open("%s/%s_snps.txt" % (flat_files('genotype/bimbam'), name), 'r') as bimbam_fh:
if len(bimbam_fh.readline().split(", ")) > 2:
delimiter = ", "
elif len(bimbam_fh.readline().split(",")) > 2:
delimiter = ","
elif len(bimbam_fh.readline().split("\t")) > 2:
delimiter = "\t"
else:
delimiter = " "
for line in bimbam_fh:
marker = {}
marker['name'] = line.split(delimiter)[0].rstrip()
marker['Mb'] = float(line.split(delimiter)[
1].rstrip()) / 1000000
marker['chr'] = line.split(delimiter)[2].rstrip()
markers.append(marker)
for marker in markers:
if (marker['chr'] != "X") and (marker['chr'] != "Y") and (marker['chr'] != "M"):
marker['chr'] = int(marker['chr'])
marker['Mb'] = float(marker['Mb'])
self.markers = markers
def add_pvalues(self, p_values):
if isinstance(p_values, list):
# THIS IS only needed for the case when we are limiting the number of p-values calculated
# if len(self.markers) > len(p_values):
# self.markers = self.markers[:len(p_values)]
for marker, p_value in zip(self.markers, p_values):
if not p_value:
continue
marker['p_value'] = float(p_value)
if math.isnan(marker['p_value']) or marker['p_value'] <= 0:
marker['lod_score'] = 0
marker['lrs_value'] = 0
else:
marker['lod_score'] = -math.log10(marker['p_value'])
# Using -log(p) for the LRS; need to ask Rob how he wants to get LRS from p-values
marker['lrs_value'] = -math.log10(marker['p_value']) * 4.61
elif isinstance(p_values, dict):
filtered_markers = []
for marker in self.markers:
if marker['name'] in p_values:
marker['p_value'] = p_values[marker['name']]
if math.isnan(marker['p_value']) or (marker['p_value'] <= 0):
marker['lod_score'] = 0
marker['lrs_value'] = 0
else:
marker['lod_score'] = -math.log10(marker['p_value'])
# Using -log(p) for the LRS; need to ask Rob how he wants to get LRS from p-values
marker['lrs_value'] = - \
math.log10(marker['p_value']) * 4.61
filtered_markers.append(marker)
self.markers = filtered_markers
class HumanMarkers(Markers):
"Markers for humans ..."
def __init__(self, name, specified_markers=[]):
marker_data_fh = open(flat_files('mapping') + '/' + name + '.bim')
self.markers = []
for line in marker_data_fh:
splat = line.strip().split()
if len(specified_markers) > 0:
if splat[1] in specified_markers:
marker = {}
marker['chr'] = int(splat[0])
marker['name'] = splat[1]
marker['Mb'] = float(splat[3]) / 1000000
else:
continue
else:
marker = {}
marker['chr'] = int(splat[0])
marker['name'] = splat[1]
marker['Mb'] = float(splat[3]) / 1000000
self.markers.append(marker)
def add_pvalues(self, p_values):
super(HumanMarkers, self).add_pvalues(p_values)
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