def betas_table_oma(data, annotations, attributes, method_params=None):
table(
data=data,
annotations=annotations,
attributes=attributes,
data_type=DataType.betas,
method=Method.oma,
method_params=method_params,
)
def betas_table_formula_new(data, annotations, attributes, data_params,
method_params):
table(
data=data,
annotations=annotations,
attributes=attributes,
data_type=DataType.betas,
method=Method.formula_new,
method_params=method_params,
data_params=data_params,
)
def residuals_table_formula(data, annotations, attributes, data_params,
method_params):
table(
data=data,
annotations=annotations,
attributes=attributes,
data_type=DataType.residuals,
method=Method.formula,
method_params=method_params,
data_params=data_params,
)
def betas_table_heteroscedasticity(data,
annotations,
attributes,
method_params=None):
table(
data=data,
annotations=annotations,
attributes=attributes,
data_type=DataType.betas,
method=Method.heteroskedasticity,
method_params=method_params,
)
def resid_old_table_linreg(
data,
annotations,
attributes,
data_params,
):
table(data=data,
annotations=annotations,
attributes=attributes,
data_type=DataType.resid_old,
method=Method.linreg,
data_params=data_params,
task_params=None,
method_params=None)
def residuals_table_pbc(
data,
annotations,
attributes,
data_params,
):
table(data=data,
annotations=annotations,
attributes=attributes,
data_type=DataType.residuals,
method=Method.pbc,
data_params=data_params,
task_params=None,
method_params=None)
def bop_table_manova(
data,
annotations,
attributes,
data_params,
method_params
):
table(
data=data,
annotations=annotations,
attributes=attributes,
data_type=DataType.bop,
method=Method.manova,
data_params=data_params,
task_params=None,
method_params=method_params
)
def betas_table_linreg(data,
annotations,
attributes,
method_params=None,
data_params=None):
"""
Producing table with information for linear regression between beta values
and methylation level for each CpG.
Each row corresponds to specific CpG.
Columns:
* item: CpG id.
* aux: gene, on which CpG is mapped.
* R2: determination coefficient. A statistical measure of how well the regression line approximates the data points.
* intercept: estimated value of the intercept of linear regression.
* slope: estimated value of the slope of linear regression.
* intercept_std: standard error of the estimate of the intercept of linear regression.
* slope_std: standard error of the estimate of the slope of linear regression.
* intercept_p_value: p-value for the intercept of linear regression.
* slope_p_pvalue: p-value for the slope of linear regression.
* ...
Possible parameters of experiment:
* None
:param data: pdm.Data instance, which specifies information about dataset.
:param annotations: pdm.Annotations instance, which specifies subset of CpGs.
:param attributes: pdm.Attributes instance, which specifies information about subjects.
:param method_params: parameters of experiment.
"""
table(data=data,
annotations=annotations,
attributes=attributes,
data_type=DataType.betas,
method=Method.linreg,
method_params=method_params,
data_params=data_params)
