Constructs the correlation matrix between the features weight of the latent dimensions obtained with different integration methods.
Arguments
- output_list
List of integration methods output, each generated via the
get_output()function. If named, the names will be added at the beginning of each latent dimension' label. If unnamed, the name of the integration method will be used instead.- include_missing_features
Logical, whether features missing in some of the output should be included in the calculation (see Details). Default value is
FALSE.
Details
If include_missing_features is FALSE (default behaviour), and some
features are present in the output of one integration method but not
the other (e.g. because a different pre-filtering was applied to the input
data of the two methods), these features will be ignored. This does not mean
that features that were selected by one method but not the other are discarded;
in that case the feature will be assigned a weight of 0 for the method that did
not select it. This is the recommended behaviour, should only be changed in
specific scenarios (e.g. to check whether using all features in a dataset vs
doing a variance-based preselection affect which features are deemed most important).
If include_missing_features is TRUE, missing features will
be assigned a weight of 0.