liana.method.MistyData

class liana.method.MistyData(data: dict | MuData, obs: DataFrame | None = None, spatial_key: str = 'spatial', enforce_obs: bool = True, **kwargs)

MistyData Class used to construct multi-view objects

Attributes:

axis

MuData axis

filename

Filename of the MuData object.

isbacked

Whether the MuData object is backed.

mod_names

Names of modalities (alias for list(mdata.mod.keys()))

n_mod

Number of modalities in the MuData object.

n_obs

Total number of observations

n_var

Total number of variables

n_vars

Total number of variables

obs

Annotation of observation

obs_names

Names of variables (alias for .obs.index)

obsm

Multi-dimensional annotation of observation

obsmap

Mapping of observation index in the MuData to indices in individual modalities.

obsp

Pairwise annotatation of observations

shape

Shape of data, all variables and observations combined (n_obs, n_var).

uns

Unstructured annotation (ordered dictionary).

var

Annotation of variables

var_names

Names of variables (alias for .var.index)

varm

Multi-dimensional annotation of variables

varmap

Mapping of feature index in the MuData to indices in individual modalities.

varp

Pairwise annotatation of variables

Methods

__call__(model[, bypass_intra, ...])	A Multi-view Learning for dissecting Spatial Transcriptomics data (MISTy) model.
copy([filename])	Make a copy.
obs_keys()	List keys of observation annotation obs.
obs_names_make_unique()	Call .obs_names_make_unique() method on each AnnData object.
obs_vector(key[, layer])	Return an array of values for the requested key of length n_obs
obsm_keys()	List keys of observation annotation obsm.
pull_obs([columns, mods, common, ...])	Copy the data from the modalities to the global .obs, existing columns to be overwritten or updated
pull_var([columns, mods, common, ...])	Copy the data from the modalities to the global .var, existing columns to be overwritten or updated
push_obs([columns, mods, common, prefixed, ...])	Copy the data from the mdata.obs to the modalities, existing columns to be overwritten
push_var([columns, mods, common, prefixed, ...])	Copy the data from the mdata.var to the modalities, existing columns to be overwritten
strings_to_categoricals([df])	Transform string columns in .var and .obs slots of MuData to categorical as well as of .var and .obs slots in each AnnData object
to_anndata(**kwargs)	Convert MuData to AnnData
uns_keys()	List keys of unstructured annotation.
update()	Update both .obs and .var indices of MuData with the data from all the modalities
update_obs()	Update global .obs_names according to the .obs_names of all the modalities.
update_var()	Update global .var_names according to the .var_names of all the modalities.
var_keys()	List keys of variable annotation var.
var_names_make_unique()	Call .var_names_make_unique() method on each AnnData object.
var_vector(key[, layer])	Return an array of values for the requested key of length n_var
varm_keys()	List keys of variable annotation varm.
write([filename])	Write MuData object to an HDF5 file
write_h5mu([filename])	Write MuData object to an HDF5 file
write_zarr(store, **kwargs)	Write MuData object to a Zarr store

get_weighted_matrix
getdoc

__init__(data: dict | MuData, obs: DataFrame | None = None, spatial_key: str = 'spatial', enforce_obs: bool = True, **kwargs)

Construct a MistyData object from a dictionary of views (anndatas).

Parameters:

datadict

Dictionary of views (anndatas) or a MuData object. Note that only the .X attribute is used. An intra-view called “intra” is required.

obspd.DataFrame

DataFrame of observations. If None, the obs of the intra-view is used.

spatial_key

Key in adata.obsm that contains the spatial coordinates. Default is ‘spatial’.

enforce_obsbool, optional (default: True)

If True, the number of observations in each extra-view must match the intra-view. Then the connectivities are stored in the .obsp attribute, while the weighted matrix is stored in .layers[‘weighted’].

If False, the connectivities are stored in the .obsm attribute, while the weighted matrix is transposed and stored in .varm[‘weighted’].

**kwargs

Keyword arguments passed to the MuData Super class

Methods

__init__(data[, obs, spatial_key, enforce_obs])	Construct a MistyData object from a dictionary of views (anndatas).
copy([filename])	Make a copy.
get_weighted_matrix(view_name[, predictors])
getdoc()
obs_keys()	List keys of observation annotation obs.
obs_names_make_unique()	Call .obs_names_make_unique() method on each AnnData object.
obs_vector(key[, layer])	Return an array of values for the requested key of length n_obs
obsm_keys()	List keys of observation annotation obsm.
pull_obs([columns, mods, common, ...])	Copy the data from the modalities to the global .obs, existing columns to be overwritten or updated
pull_var([columns, mods, common, ...])	Copy the data from the modalities to the global .var, existing columns to be overwritten or updated
push_obs([columns, mods, common, prefixed, ...])	Copy the data from the mdata.obs to the modalities, existing columns to be overwritten
push_var([columns, mods, common, prefixed, ...])	Copy the data from the mdata.var to the modalities, existing columns to be overwritten
strings_to_categoricals([df])	Transform string columns in .var and .obs slots of MuData to categorical as well as of .var and .obs slots in each AnnData object
to_anndata(**kwargs)	Convert MuData to AnnData
uns_keys()	List keys of unstructured annotation.
update()	Update both .obs and .var indices of MuData with the data from all the modalities
update_obs()	Update global .obs_names according to the .obs_names of all the modalities.
update_var()	Update global .var_names according to the .var_names of all the modalities.
var_keys()	List keys of variable annotation var.
var_names_make_unique()	Call .var_names_make_unique() method on each AnnData object.
var_vector(key[, layer])	Return an array of values for the requested key of length n_var
varm_keys()	List keys of variable annotation varm.
write([filename])	Write MuData object to an HDF5 file
write_h5mu([filename])	Write MuData object to an HDF5 file
write_zarr(store, **kwargs)	Write MuData object to a Zarr store

Attributes

axis	MuData axis
filename	Filename of the MuData object.
isbacked	Whether the MuData object is backed.
mod_names	Names of modalities (alias for list(mdata.mod.keys()))
n_mod	Number of modalities in the MuData object.
n_obs	Total number of observations
n_var	Total number of variables
n_vars	Total number of variables
obs	Annotation of observation
obs_names	Names of variables (alias for .obs.index)
obsm	Multi-dimensional annotation of observation
obsmap	Mapping of observation index in the MuData to indices in individual modalities.
obsp	Pairwise annotatation of observations
shape	Shape of data, all variables and observations combined (n_obs, n_var).
uns	Unstructured annotation (ordered dictionary).
var	Annotation of variables
var_names	Names of variables (alias for .var.index)
varm	Multi-dimensional annotation of variables
varmap	Mapping of feature index in the MuData to indices in individual modalities.
varp	Pairwise annotatation of variables