mmcci.CCIData

Class to store and manage Cell-Cell Interaction (CCI) data

metadata

Metadata for sample

Type:: Dict

n_spots

Number of spots in the sample

Type:: int

cci_scores

CCI score dataframe for each LR pair

Type:: Dict

p_values

P-values dataframe for each LR pair

Type:: Dict

adata

AnnData object

Type:: AnnData

networks

Calculated CCI networks

Type:: Dict

other_metadata

Other metadata

Type:: Dict

assays

Assays for the sample

Type:: Dict

__init__(cci_scores: Dict | None = None, p_values: Dict | None = None, n_spots: int | None = None, platform: str | None = None, network: DataFrame | None = None, network_p_values: DataFrame | None = None, adata: AnnData | None = None, other_metadata: Dict | None = None, assays: Dict | None = None)[source]

Methods

`__init__`([cci_scores, p_values, n_spots, ...])
`calc_overall`([assay, name, normalize])	Calculates the overall CCI scores in a CCIData object.
`copy`()	Create a copy of the CCIData object
`create_pathway_assay`([assay, gsea_results, ...])	Creates a pathway assay from GSEA results.
`filter_by_p_vals`([cutoff, assay, new_assay])	Filters the CCI scores in a CCIData object by p-value.
`get_adata`()	Get AnnData object
`get_cell_types`([assay])	Get cell types in a sample
`get_lr_proportions`([sender, reciever, ...])	Calculates the proportion of each LR pair in a sample for a specific cell type sender and receiver.
`get_p_vals`([assay, key, sender, reciever])	Returns the p-values for each LR pair in a sample for a specific sender and receiver cell type.
`get_sample_cci_scores`(sample_id)	Get CCI scores for a sample
`get_sample_metadata`(sample_id)	Get metadata for a sample
`get_sample_n_spots`(sample_id)	Get number of spots for a sample
`get_sample_p_values`(sample_id)	Get p-values for a sample
`merge_cell_types`(cell_types, new_cell_type)	Merges cell types in a CCIData.
`rename_cell_types`(replacements[, assay])	Renames cell types in a CCIData.
`save`(path)	Saves CCIData object to JSON or pkl file.
`scale`(scale_factor[, assay, new_assay])	Scales the CCI scores in a CCIData object.
`scale_by_nspots`([assay, new_assay])	Scales the CCI scores in a CCIData object by the number of spots.
`subset_lrs`(lr_pairs[, assay, new_assay])	Subsets the LR pairs in a CCIData object.
`to_dict`()	Convert CCIData object to a JSON-serializable dictionary.