sccoda.util.result_classes.CAResult.complete_beta_df

CAResult.complete_beta_df(intercept_df, effect_df, target_fdr=0.05)

Evaluation of MCMC results for effect parameters. This function is only used within self.summary_prepare. This function also calculates the posterior inclusion probability for each effect and decides whether effects are significant.

Parameters
intercept_df : DataFrameDataFrame

Intercept summary, see self.summary_prepare

effect_df : DataFrameDataFrame

Effect summary, see self.summary_prepare

target_fdr : floatfloat (default: 0.05)

Desired FDR value

Return type

DataFrameDataFrame

Returns

  • effect DataFrame

  • effect_df – DataFrame with inclusion probability, final parameters, expected sample