Get biomarkers from average data differences matrix (per type)

Use this function to find either positive or negative biomarkers across multiple performance classification group matchings based on a given threshold between 0 and 1.

get_biomarkers_per_type(diff.mat, threshold, type)

Arguments

diff.mat	a matrix whose rows are vectors of average node data differences between two groups of models based on some kind of classification (e.g. number of TP predictions) and whose names are set in the rownames attribute of the matrix (usually denoting the different classification groups, e.g. (1,2) means the models that predicted 1 TP synergy vs the models that predicted 2 TP synergies, if the classification is done by number of TP predictions). The columns represent the network's node names.
threshold	numeric. A number in the [0,1] interval, above which (or below its negative value) a biomarker will be registered in the returned result. Values closer to 1 translate to a more strict threshold and thus less biomarkers are found.
type	character. Accepted values are positive or negative.

Value

a character vector that includes the node names that were found either as positive or negative.

Details

The logic behind the biomarker selection is that if there is at least one value in a column of the diff.mat matrix that surpasses the threshold given, then the corresponding node (name of the column) is return as a biomarker. This means that for a single node, if at least one value that represents an average data difference (for example, the average activity state difference) between any of the given classification group comparisons is above the given threshold (or below the negative symmetric threshold), then a positive (negative) biomarker is reported.

See also

Other biomarker functions: get_biomarkers()