Analysis

Differential Analysis

class moonstone.analysis.differential_analysis.DifferentialAnalysis(metadata_dataframe, read_count_dataframe)

Perform differential analysis using chosen method.

__init__(metadata_dataframe, read_count_dataframe)

Initialize self. See help(type(self)) for accurate signature.

available_tests = {'dichotomic': ['t_test', 'wilcoxon_rank_test'], 'multiple': ['one_way_anova', 'kruskal_test']}

corrected_p_values(p_value_serie, correction_method_used)

Some available methods are: - ‘bonferroni’ : one-step correction - ‘fdr_bh’ : Benjamini/Hochberg (non-negative)

differential_analysis_by_feature(features, type_of_features, test_to_use, correction_method_used)

Features should be provided in a list splited by dichotomic or multiple option features. example: dicotomic_features = [‘SEX’, ‘GRIPPE’] multiple_option_features = [‘Season’, Age_Group’]

property number_columns_to_skip

test_default(*args, **kwargs)

test_dichotomic_features(feature, test_to_use)

test_multiple_features(feature, test_to_use)

tests_functions_used = {'kruskal_test': <function kruskal>, 'one_way_anova': <function f_oneway>, 't_test': <function ttest_ind>, 'wilcoxon_rank_test': <function ranksums>}

Diversity

Alpha-Diversity

Alpha-diversity corresponds to the intra-sample diversity

Phylogenetic alpha-diversity includes the phylogenetic closeness of species in the computation of the diversity indexes

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Beta-Diversity

Beta-diversity corresponds to the inter-samples diversity

Phylogenetic beta-diversity includes the phylogenetic closeness of species in the computation of the diversity indexes