sccoda.util.result_classes.CAResult

class sccoda.util.result_classes.CAResult(sampling_stats, model_specs, **kwargs)

Result class for scCODA, extends the arviz framework for inference data.

The CAResult class is an extension of az.InferenceData, that adds some information about the compositional model and is able to print humanly readable results. It supports all functionality from az.InferenceData.

Attributes

attrs

Attributes of InferenceData object.

Methods

compare_parameters_to_truth(b_true, w_true, …)	Extends data frames from summary_prepare by a comparison to some ground truth slope and intercept values that are assumed to be from the same generative model (e.g.
complete_alpha_df(intercept_df)	Evaluation of MCMC results for intercepts.
complete_beta_df(intercept_df, effect_df[, …])	Evaluation of MCMC results for effect parameters.
credible_effects([est_fdr])	Decides which effects of the scCODA model are credible based on an adjustable inclusion probability threshold.
distance_to_truth()	Compares real cell count matrix to the posterior mode cell count matrix that arises from the calculated parameters
save(path_to_file)	Function to save scCODA results to disk via pickle.
set_fdr(est_fdr, *args, **kwargs)	Direct posterior probability approach to calculate credible effects while keeping the expected FDR at a certain level
summary(*args, **kwargs)	Printing method for scCODA’s summary.
summary_extended(*args, **kwargs)	Extended (diagnostic) printing function that shows more info about the sampling result
summary_prepare([est_fdr])	Generates summary dataframes for intercepts and slopes.