scimap.hl.classify

Short description

The function allows users to classify cells based on positivity/negativity of given markers. Users can classify the entire data or a subset of data that has been previously phenotyped or clustered using the subclassify_phenotype parameter.

Parameters

adata : AnnData object

pos: list (The default is None)
Pass a list of markers that should be expressed in the resultant cells.

neg : list, optional (The default is None)
Pass a list of markers that should not be expressed in the resultant cells.

classify_label : string, optional (The default is 'passed_classify'.)
Provide a name for the calssified cells.

phenotype : string, optional (The default is 'phenotype'.)
Column name of the column containing the phenotype information. This is important if subclassify_phenotype or collapse_failed arguments are used.

subclassify_phenotype : list, optional (The default is None.)
If only a subset of phenotypes require to classified, pass the name of those phenotypes as a list through this argument.

threshold : float, optional (The default is 0.5)
Above or below the given value will be considered for positive and negative classification. If the data was scaled using the sm.pp.rescale function, 0.5 is the classification threshold.

collapse_failed : bool, optional (The default is True)
If set to true, the cells that were not classified based on the given criteria will be binned into a single category named 'failed_classify'. When False, the phenotype inforamation for other cells will be borrowed from the phenotype argument.

label : string, optional (The default is "classify")
Key for the returned data, stored in adata.obs.

Returns

adata : AnnData
Updated AnnData Object.

Example

# Classify all cells with both pos and neg markers (Identify cytotoxic T-cells)
adata = sm.hl.classify(adata, pos=['CD3D','CD8A'], neg=['ASMA'])

# Classify specific sub-types of cells
adata = sm.hl.classify(adata, pos=['CD3D','FOXP3'], neg=['ASMA'], subclassify_phenotype=['T cells','Regulatory T cells'])

# Classify specific sub-types of cells and borrow labels from another column
adata = sm.hl.classify(adata, pos=['CD3D'], neg=['ASMA'], subclassify_phenotype=['T cells'], collapse_failed=False, phenotype='phenotype')