pegasus.select_features¶
-
pegasus.
select_features
(data, features='highly_variable_features', standardize=True, max_value=10.0)[source]¶ Subset the features and store the resulting matrix in dense format in data.uns with ‘fmat_’ prefix, with the option of standardization and truncating based on max_value. ‘fmat_*’ will be removed before writing out the disk.
- Parameters
data (
pegasusio.MultimodalData
) – Annotated data matrix with rows for cells and columns for genes.features (
str
, optional, default:None
.) – a keyword indata.var
, which refers to a boolean array. IfNone
, all features will be selected.standardize (
bool
, optional, default:True
.) – Whether to scale the data to unit variance and zero mean.max_value (
float
, optional, default:10
.) – The threshold to truncate data after scaling. IfNone
, do not truncate.
- Return type
str
- Returns
keyword (
str
) – The keyword indata.uns
referring to the features selected.Update
data.uns
–data.uns[keyword]
: A submatrix of the data containing features selected.
Examples
>>> pg.select_features(data)