def getTriglycerides(replaced_missing, replaced_branching, input_filename,
data_field1, date_time_var, directory_for_output):
'''Function to generate QC ,statistics and phenotype specific data for the column 'triglycerides' in the input spreadsheet.
The phenotype specific data is classified based on 1 condition'''
desired_var = 'triglycerides'
output_table_QC_tri = str(directory_for_output) + str(
desired_var) + "_" + "QC-tables_" + str(
input_filename) + "_" + date_time_var + ".xls"
output_values_QC_tri = directory_for_output + desired_var + "_" + "QC-values_" + input_filename + "_" + date_time_var + ".xls"
output_value_phen_tri = str(directory_for_output) + str(
desired_var) + "_" + "Phen-table_" + str(
input_filename) + "_" + date_time_var + ".xls"
writer_tri = pd.ExcelWriter(output_table_QC_tri)
llq_tri = 0.13
ulq_tri = 5.60
con1_tri = 1.7
stat_and_QC(llq_tri, ulq_tri, desired_var, data_field1,
output_values_QC_tri, writer_tri, replaced_missing,
replaced_branching)
Phenotype_1conditions(con1_tri, desired_var, data_field1, writer_tri,
output_value_phen_tri)
writer_tri.save()
def getHDL (replaced_missing,replaced_branching,input_filename,data_field1,date_time_var,directory_for_output):
'''Function to generate QC ,statistics and phenotype specific data for the column 'hdl in the input spreadsheet.
This phenotype data is sex specific and is classified in both casses into 2 classes.'''
desired_var = 'hdl'
output_table_QC_hdl = str(directory_for_output) + str(desired_var) + "_" + "QC-tables_" + str(input_filename) + "_" + date_time_var + ".xls"
output_values_QC_hdl = directory_for_output + desired_var + "_" + "QC-values_" + input_filename + "_" + date_time_var + ".xls"
output_value_phen_hdl = str(directory_for_output) + str(desired_var) + "_" + "Phen-table_" + str(input_filename) + "_" + date_time_var + ".xls"
writer_hdl = pd.ExcelWriter(output_table_QC_hdl)
llq_hdl = 0.05
ulq_hdl = 3.80
con_m = 1.0
con_f = 1.3
stat_and_QC(llq_hdl, ulq_hdl ,desired_var ,data_field1 , output_values_QC_hdl , writer_hdl ,
replaced_missing, replaced_branching )
Phenotype_1condition_sex_2func( desired_var ,data_field1 ,writer_hdl, output_value_phen_hdl,con_m,con_f)
writer_hdl.save()
def getGlucose(replaced_missing, replaced_branching, input_filename,
data_field1, date_time_var, directory_for_output):
'''Function to generate QC ,statistics and phenotype specific data for the column 'glucose'' in the input spreadsheet.
The phenotype specific data is classified into 5 different classes'''
desired_var = 'glucose'
output_table_QC_glucose = str(directory_for_output) + str(
desired_var) + "_" + "QC-tables_" + str(
input_filename) + "_" + date_time_var + ".xls"
output_values_QC_glucose = directory_for_output + desired_var + "_" + "QC-values_" + input_filename + "_" + date_time_var + ".xls"
output_value_phen_glucose = str(directory_for_output) + str(
desired_var) + "_" + "Phen-table_" + str(
input_filename) + "_" + date_time_var + ".xls"
writer_glucose = pd.ExcelWriter(output_table_QC_glucose)
llq_glucose = 0.36
ulq_glucose = 35
con1_glucose = 5.60
con2_glucose = 7.00
con3_glucose = 11.10
stat_and_QC(llq_glucose, ulq_glucose, desired_var, data_field1,
output_values_QC_glucose, writer_glucose, replaced_missing,
replaced_branching)
Phenotype_5conditions(llq_glucose, con1_glucose, con2_glucose,
con3_glucose, desired_var, data_field1,
writer_glucose, output_value_phen_glucose)
writer_glucose.save()
def getTotCholesterol (replaced_missing,replaced_branching,input_filename,data_field1,date_time_var,directory_for_output):
'''Function to generate QC ,statistics and phenotype specific data for the column 'cholesterol_1' in the input spreadsheet.
The phenotype specific data is classified based on 1 condition'''
desired_var = 'cholesterol_1'
output_table_QC_tot_chol = str(directory_for_output) + str(desired_var) + "_" + "QC-tables_" + str(input_filename) + "_" + date_time_var + ".xls"
output_values_QC_tot_chol = directory_for_output + desired_var + "_" + "QC-values_" + input_filename + "_" + date_time_var + ".xls"
output_value_phen_tot_chol = str(directory_for_output) + str(desired_var) + "_" + "Phen-table_" + str(input_filename) + "_" + date_time_var + ".xls"
writer_tot_chol = pd.ExcelWriter(output_table_QC_tot_chol)
llq_tot_chol = 0.30
ulq_tot_chol = 17.20
con1_tot_chol = 5.0
stat_and_QC(llq_tot_chol, ulq_tot_chol ,desired_var ,data_field1 , output_values_QC_tot_chol , writer_tot_chol ,
replaced_missing, replaced_branching )
Phenotype_1conditions( con1_tot_chol, desired_var ,data_field1 , writer_tot_chol ,
output_value_phen_tot_chol)
writer_tot_chol.save()
def getTotProtein_urine(replaced_missing, replaced_branching, input_filename,
data_field1, date_time_var, directory_for_output):
'''Function to generate QC and statistics specific data for the column 'ur_protein' in the input spreadsheet.'''
desired_var = 'ur_protein'
output_table_QC_TotProtein = str(directory_for_output) + str(
desired_var) + "_" + "QC-tables_" + str(
input_filename) + "_" + date_time_var + ".xls"
output_values_QC_TotProtein = directory_for_output + desired_var + "_" + "QC-values_" + input_filename + "_" + date_time_var + ".xls"
writer_TotProtein = pd.ExcelWriter(output_table_QC_TotProtein)
llq_TotProtein = 40
ulq_TotProtein = 2000
stat_and_QC(llq_TotProtein, ulq_TotProtein, desired_var, data_field1,
output_values_QC_TotProtein, writer_TotProtein,
replaced_missing, replaced_branching)
writer_TotProtein.save()
def getCreatinine_serum(replaced_missing, replaced_branching, input_filename,
data_field1, date_time_var, directory_for_output):
'''Function to generate QC and statistics specific data for the column 's_creatinine' in the input spreadsheet.'''
desired_var = 's_creatinine'
output_table_QC_creatinine_s = str(directory_for_output) + str(
desired_var) + "_" + "QC-tables_" + str(
input_filename) + "_" + date_time_var + ".xls"
output_values_QC_creatinine_s = directory_for_output + desired_var + "_" + "QC-values_" + input_filename + "_" + date_time_var + ".xls"
writer_creatinine_s = pd.ExcelWriter(output_table_QC_creatinine_s)
llq_creatinine_s = 11.80
ulq_creatinine_s = 2448
stat_and_QC(llq_creatinine_s, ulq_creatinine_s, desired_var, data_field1,
output_values_QC_creatinine_s, writer_creatinine_s,
replaced_missing, replaced_branching)
writer_creatinine_s.save()