Producing Gene Masks.
GMask produces the masks of features (genes). Each gene mask reports the samples that can unambiguously be assigned to their correct target classes by this gene.
GMask(ES, Core, Y)
gene (feature) matrix: P, number of genes, by N, number of samples(observations).
a vector of length N for samples' class label.
GMask gives the gene masks that can represent the capability of genes to correctly classify each sample. Such a mask represents a gene's classification power. Each element of a mask is set either to 1 or 0 based on whether the corresponding sample (observation) could be unambiguously assign to its correct target class by the considered gene or not respectively.
It returns a P by N matrix with elements of zeros and ones.
Osama Mahmoud firstname.lastname@example.org
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.
CI.emprical for the core interval boundaries.
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