pheno_level_CT_rank

Function

crisgi_obj.pheno_level_CT_rank(
    ref_group,
    target_group,
    sortby='pvals_adj',
    n_top_interactions=None,
    gene_sets=[
        'KEGG_2021_Human',
        'GO_Molecular_Function_2023',
        'GO_Cellular_Component_2023',
        'GO_Biological_Process_2023',
        'MSigDB_Hallmark_2020'
    ],
    prefix='test',
    min_size=5,
    max_size=1000,
    permutation_num=1000,
    seed=0,
)

Performs gene set enrichment analysis (GSEA) on ranked gene interactions between a reference group and a comparison group, using multiple gene set libraries. The function ranks genes based on their adjusted p-values or another specified metric, aggregates scores for each gene, and runs GSEA using the gseapy package. Results are saved to disk and stored as an attribute for further analysis.

Parameters

Name	Type	Description
`ref_group`	`str`	Reference group name for comparison.
`target_group`	`str`	Comparison group name.
`sortby`	`str`	Column name to sort interactions by (default: `'pvals_adj'`).
`n_top_interactions`	`int or None`	Number of top interactions to include (default: all).
`gene_sets`	`list of str`	List of gene set libraries to use for enrichment analysis.
`prefix`	`str`	Prefix for output directory and files.
`min_size`	`int`	Minimum size of gene sets to include in analysis.
`max_size`	`int`	Maximum size of gene sets to include in analysis.
`permutation_num`	`int`	Number of permutations for GSEA.
`seed`	`int`	Random seed for reproducibility.

Return type

None

Returns

This function does not return a value. It saves GSEA results and ranked gene data to disk and sets an attribute for further access.

Attributes Set

self.gp_res: Stores the GSEA results object for further analysis.

Example

# Assume `obj` is an instance of the class containing pheno_level_CT_rank

obj.pheno_level_CT_rank(
    ref_group='Control',
    target_group='Treatment',
    sortby='pvals_adj',
    n_top_interactions=100,
    gene_sets=[
        'KEGG_2021_Human',
        'GO_Biological_Process_2023'
    ],
    prefix='experiment1',
    min_size=10,
    max_size=500,
    permutation_num=2000,
    seed=42
)

# After execution, results are saved in the specified output directory,
# and the GSEA results are accessible via obj.gp_res.