예제 #1
0
def betas_table_aggregator_linreg(data,
                                  annotations,
                                  attributes,
                                  observables_list,
                                  data_params=None,
                                  method_params=None):
    """
        Producing table with information about observable-specificity of target data type
        and target observable for each CpG.

        Columns:

        * item: CpG id.
        * aux: gene, on which CpG is mapped.
        * area_intersection_rel: relative intersection area of polygons
          which is equals area of polygon(s) intersection to area of polygons union ratio.
        * slope_intersection_rel: relative intersection area of allowed regions for slopes of linear regression.
        * max_abs_slope: maximal absolute slope between all provided subjects subsets
        * ...
        * z_value: number of standard deviations by which data point is above the mean value.
        * The considered data point is the difference between two linear regressions slopes.
        * abs_z_value: absolute z_value
        * p_value: probability of rejecting the null hypothesis that the difference in slopes is zero.
        * ...

        For each subjects subset the next columns are added to the resulting table:

        * 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.
        * ...

        Where *** is the name of subjects subset.

        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 observables_list: list of subjects subsets. Each element in list is dict,
         where ``key`` is observable name and ``value`` is possible values for this observable.
        :param method_params: parameters of experiment.
    """

    table_aggregator_linreg(
        DataType.betas,
        data,
        annotations,
        attributes,
        observables_list,
        data_params,
        method_params,
    )
예제 #2
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def entropy_table_aggregator_linreg(data,
                                    annotations,
                                    attributes,
                                    observables_list,
                                    data_params=None,
                                    method_params=None):
    table_aggregator_linreg(
        DataType.entropy,
        data,
        annotations,
        attributes,
        observables_list,
        data_params,
        method_params,
    )
예제 #3
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def betas_adj_table_aggregator_linreg(
    data,
    annotations,
    attributes,
    observables_list,
    data_params,
):
    table_aggregator_linreg(
        DataType.betas_adj,
        data,
        annotations,
        attributes,
        observables_list,
        data_params=data_params,
    )
예제 #4
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def residuals_table_aggregator_linreg(
    data,
    annotations,
    attributes,
    observables_list,
    data_params,
):
    table_aggregator_linreg(
        DataType.residuals,
        data,
        annotations,
        attributes,
        observables_list,
        data_params=data_params,
    )