from paper.routines.infrastructure.save.table import save_table_dict_xlsx
import pandas as pd
save_path = 'E:/YandexDisk/Work/pydnameth/unn_epic'
data = pdm.Data(path='', base='unn_epic')
annotations = pdm.Annotations(name='annotations',
type='850k',
exclude='bad_cpgs_from_ChAMP',
select_dict={'CHR': ['-X', '-Y']})
target = 'Age'
observables_unn_epic = pdm.Observables(name='observables_part(final)',
types={})
cells = pdm.Cells(name='cell_counts', types='any')
attributes = pdm.Attributes(target=target,
observables=observables_unn_epic,
cells=cells)
data_params_unn_epic = {
'norm': 'BMIQ',
'part': 'final',
'cells': ['Bcell', 'CD4T', 'CD8T', 'Neu', 'NK']
}
config = pdm.load_residuals_config(data,
annotations,
attributes,
data_params=data_params_unn_epic)
keys = ['X' + elem for elem in config.observables_dict['Sample_Name']]
res_dict = {}
for x_id, x in enumerate(keys):
target = get_target(data.base)
data_params = get_data_params(data.base)
data_params['cells'] = ['CD8T', 'CD4T', 'NK', 'Bcell', 'Gran']
if data.base == 'GSE55763':
observables_list = [
{
'gender': 'any',
'is_duplicate': '0',
'age': (35, 100)
},
]
else:
observables_list = [
{
'gender': 'any'
},
]
for obs in observables_list:
observables = pdm.Observables(name='observables', types=obs)
attributes = pdm.Attributes(target=target,
observables=observables,
cells=cells)
pdm.residuals_table_linreg(data=data,
annotations=annotations,
attributes=attributes,
data_params=data_params)
select_dict={
'CHR': ['-X', '-Y']
}
)
target_unn_epic = 'Age'
observables_unn_epic = pdm.Observables(
name='observables',
types={}
)
cells_unn_epic = pdm.Cells(
name='cell_counts_horvath_filtered_normalized',
types='any'
)
attributes_unn_epic = pdm.Attributes(
target=target_unn_epic,
observables=observables_unn_epic,
cells=cells_unn_epic
)
data_params_unn_epic = get_data_params(data_unn_epic.base)
# data_params_unn_epic = {
# 'norm': 'BMIQ',
# 'part': 'raw',
# }
config_unn = pdm.load_beta_config(
data_unn_epic,
annotations_unn_epic,
attributes_unn_epic,
data_params=data_params_unn_epic
)