emba (version 0.1.1)

update_biomarker_files: Update biomarker files for a specific synergy

Description

This function gets the (previously-found or 'old') synergy biomarkers from their respective files and if any of these files are empty (no 'old' biomarkers found) or non-existent, the 'new' biomarkers (given as input vector parameters) are automatically saved. When the 'new' biomarkers share common nodes with the 'old' biomarkers, there exist 3 possible ways to combine the results, given by the method parameter. If no common nodes exist, no matter the method selected, the 'new' biomarkers are added to the 'old' ones.

Usage

update_biomarker_files(biomarkers.dir, drug.comb, biomarkers.active.new,
  biomarkers.inhibited.new, method = "replace")

Arguments

biomarkers.dir

string. It specifies the full path name of the directory which holds the biomarker files for the synergistic drug combination specified in the parameter drug.comb. The biomarker files must be formatted as: %drug.comb%_biomarkers_active or %drug.comb%_biomarkers_inhibited, where %drug.comb% is the value of the drug.comb parameter.

drug.comb

string. The drug combination (e.g. "A-B") that will be used to identify the related biomarker files.

biomarkers.active.new

a numeric vector whose names attribute includes the node names of the (newly found) active biomarkers for the specified synergy. The values of the vector are the average activity difference of each node, derived from a comparison between 2 different groups of models.

biomarkers.inhibited.new

a numeric vector whose names attribute includes the node names of the (newly found) inhibited biomarkers for the specified synergy. The values of the vector are the average activity difference of each node, derived from a comparison between 2 different groups of models.

method

string. It specifies the method to use to update the biomarker files when there are common nodes between the 'old' and 'new' biomarkers:

  1. replace(DEFAULT): we discard the 'old' biomarkers and keep only the 'new' ones

  2. prune.to.common: we keep only the common biomarkers

  3. extend: we add to the 'old' set of biomarkers the extra ones from the 'new' set that are not non-common to the 'old' ones, extending thus the 'old' biomarker set