only_from: Recreate interaction data frame based on certain datasets and...

In saezlab/OmnipathR: OmniPath web service client and more

Recreate interaction data frame based on certain datasets and resources

Description

Recreate interaction data frame based on certain datasets and resources

Usage

only_from(
  data,
  datasets = NULL,
  resources = NULL,
  exclude = NULL,
  .keep = FALSE
)

Arguments

data	An interaction data frame from the OmniPath web service with evidences column.
datasets	Character: a vector of dataset labels. Only evidences from these datasets will be used.
resources	Character: a vector of resource labels. Only evidences from these resources will be used.
exclude	Character vector of resource names to be excluded.
.keep	Logical: keep the "evidences" column.

Details

The OmniPath interactions database fully integrates all attributes from all resources for each interaction. This comes with the advantage that interaction data frames are ready for use in most of the applications; however, it makes it impossible to know which of the resources and references support the direction or effect sign of the interaction. This information can be recovered from the "evidences" column. The "evidences" column preserves all the details about interaction provenances. In cases when you want to use a faithful copy of a certain resource or dataset, this function will help you do so. Still, in most of the applications the best is to use the interaction data as it is returned by the web service.

Note: This function is automatically applied if the 'strict_evidences' argument is passed to any function querying interactions (e.g. omnipath-interactions).

Value

A copy of the interaction data frame restricted to the given datasets and resources.

See Also

• omnipath-interactions

• filter_evidences

• unnest_evidences

• from_evidences

Examples

## Not run: 
ci <- collectri(evidences = TRUE)
ci <- only_from(ci, datasets = 'collectri')

## End(Not run)

saezlab/OmnipathR documentation built on Nov. 10, 2024, 11:02 p.m.