pheno level accumulated top n ORA

Function

crisgi_obj.pheno_level_accumulated_top_n_ORA(
    target_group, 
    n_top_interactions=None, 
    n_space=10, 
    method='prod', 
    test_type='TER', 
    gene_sets=[
        'KEGG_2021_Human',
        'GO_Molecular_Function_2023',
        'GO_Cellular_Component_2023',
        'GO_Biological_Process_2023',
        'MSigDB_Hallmark_2020'
    ],
    background=None, 
    organism='human', 
    plot=True,
)

Performs an accumulated over-representation analysis (ORA) for the top-N interactions at the phenotype level. This function iteratively evaluates enrichment for increasing numbers of top interactions, aggregates the results, and saves the enrichment statistics to a CSV file. The results are also stored in the object's attributes for further analysis.

Parameters

Name	Type	Description
`target_group`	str	The group or phenotype to analyze.
`n_top_interactions`	int, optional	The maximum number of top interactions to consider. If `None`, uses all available interactions.
`n_space`	int, optional	Step size for the number of top interactions to include in each enrichment analysis. Default is `10`.
`method`	str, optional	Correlation or interaction method used to select interactions. Default is `'prod'`.
`test_type`	str, optional	Type of statistical test applied (e.g., `'TER'`). Default is `'TER'`.
`gene_sets`	list of str	List of gene set databases to use for enrichment analysis.
`background`	list or None	Background gene set for enrichment. If `None`, uses default background.
`organism`	str, optional	Organism name for gene set enrichment (e.g., `'human'`). Default is `'human'`.
`plot`	bool, optional	Whether to generate plots for the enrichment results. Default is `True`.

Return type

None

Returns

This function does not return a value. It saves the enrichment results as a CSV file and updates the object's attributes with the enrichment results and dataframes.

Attributes Set

self.edata.uns[f'{method}_{self.groupby}_{target_group}_{test_type}_enrich_res']:
Dictionary mapping top-N values to enrichment results.
self.edata.uns[f'{method}_{self.groupby}_{target_group}_{test_type}_enrich_df']:
DataFrame containing concatenated enrichment results for all top-N values.

Example

# Assume `obj` is an instance of the class containing this method

# Perform accumulated ORA for the 'disease' group using default parameters
obj.pheno_level_accumulated_top_n_ORA(target_group='disease')

# Specify custom parameters, such as using only the top 50 interactions and a different gene set
obj.pheno_level_accumulated_top_n_ORA(
    target_group='tissue',
    n_top_interactions=50,
    n_space=5,
    method='prod',
    test_type='TER',
    gene_sets=['KEGG_2021_Human'],
    organism='human',
    plot=False
)

# After execution, results are saved to a CSV file and stored in:
# obj.edata.uns['prod_<groupby>_disease_TER_enrich_res']
# obj.edata.uns['prod_<groupby>_disease_TER_enrich_df']