fitness.AUC: Calculate AUC in classifying data for using as fitness...

In SCBIT-YYLab/DysRegSig: Gene dysregulation analysis and construction of mechanistic signature in cancer

Description

Calculate AUC with cross-validation in classifying data for using as fitness function.

Usage

fitness.Cindex(combine.dysreg, dysreg, exp.data, pheno.data, train.rate)

Arguments

combine.dysreg	The combination of genes.
dysreg	The dysregulations output from DysReg.
exp.data	Expression matrix. Columns correspond to genes, rows correspond to experiments. The matrix is expected to be already normalized.
pheno.data	The phenotype data corresponding to objective function. At here, it is classifying data.
train.rate	The rate of sample for training model in cross-validation.

Value

The fitness, AUC, for each individual.

See Also

combineDysreg

SCBIT-YYLab/DysRegSig documentation built on July 19, 2021, 4:38 a.m.