scanpy.pp.combat#
- scanpy.pp.combat(adata, key='batch', *, covariates=None, inplace=True)[source]#
ComBat function for batch effect correction [Johnson et al., 2006, Leek et al., 2017, Pedersen, 2012].
Corrects for batch effects by fitting linear models, gains statistical power via an EB framework where information is borrowed across genes. This uses the implementation combat.py [Pedersen, 2012].
- Parameters:
- adata
AnnData
Annotated data matrix
- key
str
(default:'batch'
) Key to a categorical annotation from
obs
that will be used for batch effect removal.- covariates
Collection
[str
] |None
(default:None
) Additional covariates besides the batch variable such as adjustment variables or biological condition. This parameter refers to the design matrix
X
in Equation 2.1 in Johnson et al. [2006] and to themod
argument in the original combat function in the sva R package. Note that not including covariates may introduce bias or lead to the removal of biological signal in unbalanced designs.- inplace
bool
(default:True
) Whether to replace adata.X or to return the corrected data
- adata
- Return type:
- Returns:
Returns
numpy.ndarray
ifinplace=True
, else returnsNone
and sets the following field in theadata
object:adata.X
numpy.ndarray
(dtypefloat
)Corrected data matrix.