omicverse.pp.preprocess

omicverse.pp.preprocess(adata, mode='shiftlog|pearson', target_sum=500000.0, n_HVGs=2000, organism='human', no_cc=False, batch_key=None, identify_robust=True)

Preprocesses the AnnData object adata using either a scanpy or a pearson residuals workflow for size normalization and highly variable genes (HVGs) selection, and calculates signature scores if necessary.

Parameters:

• adata – The data matrix.

• mode (default: 'shiftlog|pearson') – The mode for size normalization and HVGs selection.

• 'scanpy' (It can be either 'scanpy' or 'pearson'. If)

:param : :param performs size normalization using scanpy’s normalize_total() function and selects HVGs: :param using pegasus’ highly_variable_features() function with batch correction.: :param If ‘pearson’: :param selects HVGs sing scanpy’s experimental.pp.highly_variable_genes() function: :param with pearson residuals method and performs: :param size normalization using scanpy’s experimental.pp.normalize_pearson_residuals() function.: :type target_sum: default: 500000.0 :param target_sum: The target total count after normalization. :type n_HVGs: default: 2000 :param n_HVGs: the number of HVGs to select. :type organism: default: 'human' :param organism: The organism of the data. It can be either ‘human’ or ‘mouse’. :type no_cc: default: False :param no_cc: Whether to remove cc-correlated genes from HVGs.

Returns:

The preprocessed data matrix.

Return type:

adata