RDC: Assiging the Relative Dominant Class.

In propOverlap: Feature (gene) selection based on the Proportional Overlapping Scores

Description

RDC associates genes (features) with the class which it is more able to distingish. For each gene, a class that has the highest proportion, relative to classes' size, of correctly assigned samples (observations) is reported as the relative dominant class for the considered gene.

Usage

RDC(GMask, Y)

Arguments

GMask	gene (feature) mask matrix: P, number of genes, by N, number of samples(observations) with elements of zeros and ones. See the returned value of the GMask.
Y	a vector of length N for samples' class label.

Value

RDC returns a vector of length P. Each element's value is either 1 or 2 indicating which class label is reported as the relative dominant class for the corresponding gene (feature).

Author(s)

Osama Mahmoud [e-mail]

References

Mahmoud O., Harrison A., Perperoglou A., Gul A., Khan Z., Metodiev M. and Lausen B. (2014) A feature selection method for classification within functional genomics experiments based on the proportional overlapping score. BMC Bioinformatics, 2014, 15:274.

See Also

GMask for gene (feature) mask matrix.

Examples

data(lung)
Class           <- lung[12534,]   #define the observations' class labels
Gene.Masks      <- GMask(lung[1:12533,], CI.emprical(lung[1:12533,], Class), Class)
RelativeDC      <- RDC(Gene.Masks, Class)
RelativeDC[1:10]                  #show the relative dominant classes for the first 10 features
table(RelativeDC)                 #show the number of assignments for each class

propOverlap documentation built on May 1, 2019, 10:55 p.m.