The meta-features table is useful anytime there are metadata variables that cannot be mapped 1:1 to your features. For example, a peptide may be associated with multiple proteins.
addMetaFeatures(study, metaFeatures, reset = FALSE)Returns the original onStudy object passed to the argument
study, but modified to include the newly added data
An OmicNavigator study created with createStudy
The metadata variables that describe the meta-features in
the study. The input object is a list of data frames (one per model). The
first column of each data frame is used as the featureID, so it must
contain the same IDs as the corresponding features data frame
(addFeatures). The second column of each data frame is used
as the metaFeatureID, and thus should match the row names of any metaAssays
added via addMetaAssays. To share a data frame across
multiple models, use the modelID "default". All columns will be coerced to
character strings.
Reset the data prior to adding the new data (default:
FALSE). The default is to add to or modify any previously added data
(if it exists). Setting reset = TRUE enables you to remove existing
data you no longer want to include in the study.
getMetaFeatures