scvelo.pp.normalize_per_cell¶
-
scvelo.pp.
normalize_per_cell
(data, counts_per_cell_after=None, counts_per_cell=None, key_n_counts=None, max_proportion_per_cell=None, use_initial_size=True, layers=None, enforce=None, copy=False)¶ Normalize each cell by total counts over all genes.
- Parameters
- data :
AnnData
, np.ndarray, sp.sparse The (annotated) data matrix of shape n_obs × n_vars. Rows correspond to cells and columns to genes.
- counts_per_cell_after : float or None, optional (default: None)
If None, after normalization, each cell has a total count equal to the median of the counts_per_cell before normalization.
- counts_per_cell : np.array, optional (default: None)
Precomputed counts per cell.
- key_n_counts : str, optional (default: ‘n_counts’)
Name of the field in adata.obs where the total counts per cell are stored.
- max_proportion_per_cell : int (default: None)
Exclude genes counts that account for more than a specific proportion of cell size, e.g. 0.05.
- use_initial_size : bool (default: True)
Whether to use initial cell sizes oder actual cell sizes.
- layers : str or list (default: [‘spliced’, ‘unspliced’])
Keys for layers to be also considered for normalization.
- copy : bool, optional (default: False)
If an
AnnData
is passed, determines whether a copy is returned.
- data :
- Returns
Returns or updates adata with normalized counts.