mofaflex.DataOptions#
- class mofaflex.DataOptions(*, group_by=None, layer=None, scale_per_group=True, annotations_varm_key=None, covariates_obs_key=None, covariates_obsm_key=None, guiding_vars_obs_keys=None, use_obs='union', use_var='union', subset_var='highly_variable', plot_data_overview=True, remove_constant_features=True)#
Options for the data.
Attributes table#
Key of .varm attribute of each AnnData object that contains annotation values. |
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Key of .obs attribute of each |
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Key of .obsm attribute of each |
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Columns of |
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Keys of .obs attribute of each |
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Which layer to use. |
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Plot data overview. |
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Remove constant features from the data. |
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Scale Normal likelihood data per group, otherwise across all groups. |
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How to align observations across views. |
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How to align variables across groups. |
Methods table#
Attributes#
- DataOptions.annotations_varm_key: Mapping[str, str] | str | None = None#
Key of .varm attribute of each AnnData object that contains annotation values.
- DataOptions.covariates_obs_key: Mapping[str, str] | str | None = None#
Key of .obs attribute of each
AnnDataobject that contains covariate values.
- DataOptions.covariates_obsm_key: Mapping[str, str] | str | None = None#
Key of .obsm attribute of each
AnnDataobject that contains covariate values.
- DataOptions.group_by: str | Sequence[str] | None = None#
Columns of
.obsinMuDataobjects to group data by. Ignored if the input data is not aMuDataobject.
- DataOptions.guiding_vars_obs_keys: str | Sequence[str] | Mapping[str, Mapping[str, str]] | None = None#
Keys of .obs attribute of each
AnnDataobject that contains guiding variable values.
- DataOptions.layer: Mapping[str, str | None] | Mapping[str, Mapping[str, str | None]] | str | None = None#
Which layer to use. If
None, the.Xelement will be used. Ifstr, the same layer will be used for all groups and views. If a dict of strings, the keys must correspond to view names and the values to layers. If a nested dict, different layers can be used for each combination of group and view. The last format is only accepted if the data is a nested dictionary ofAnnDataobjects.
- DataOptions.scale_per_group: bool = True#
Scale Normal likelihood data per group, otherwise across all groups.
- DataOptions.subset_var: str | None = 'highly_variable'#
.varcolumn with boolean values to select features.