bioalpha.singlecell.preprocessing.scale

bioalpha.singlecell.preprocessing.scale(X: H5ADMap | AnnData | spmatrix | ndarray, zero_center: bool = False, max_value: float | None = None, copy: bool = False, layer: str | None = None, obsm: str | None = None, key_added: str | None = None, obs_mask: str | None = None, var_mask: str | None = None, **kwargs)

Scale data to unit variance and zero mean.

Note

Variables (genes) that do not display any variation (are constant across all observations) are retained and (for zero_center==True) set to 0 during this operation. In the future, they might be set to NaNs.

Parameters:

  • X (Union[H5ADMap, AnnData, spmatrix, ndarray]) – The (annotated) data matrix of shape n_obs x n_vars. Rows correspond to cells and columns to genes.

  • zero_center (bool, default = False) – If False, omit zero-centering variables, which allows to handle sparse input efficiently. Incompatible with sparse data.

  • max_value (Optional[float], default = None,) – Clip (truncate) to this value after scaling. If None, do not clip.

  • copy (bool, default = False) – Whether this function should be performed inplace. If an AnnData object is passed, this also determines if a copy is returned.

  • layer (Optional[str], default = None) – If provided, which element of layers to scale.

  • obsm (Optional[str], default = None) – If provided, which element of obsm to scale.

  • obs_mask (Optional[str], default = None) – If obs_mask is not None, filter cells by adata.obs[obs_mask].

  • var_mask (Optional[str], default = None) – If obs_mask is not None, filter genes by adata.obs[obs_mask].

  • **kwargs – Other arguments passed to BatchReader

Returns:

  • Depending on copy returns or updates adata with a scaled adata.X,

  • annotated with 'mean' and 'std' in adata.var.