eval.subset:
Performance evaluation derived from a subset of a data set
Description
Select a subset of a single data set and split it into the training and testing sets. Generate a gene signature from the training set and evaluate its performance on the testing set.
Usage
eval.subset(x, y, censor, iter, method, gn.nb, train.nb)
Arguments
x
Matrix of gene expression data.
y
Vector of survival time.
censor
Vector of censoring status. In the censoring status vector, 1 = event occurred, 0 = censored.
iter
An integer specifying the current iteration.
method
A character string specifying the feature selection method: "none" for top-ranking or one of the adjusting methods specified by the p.adjust function.
gn.nb
An integer specifying the number of genes to select.
train.nb
An integer specifying the sample size of the training set.
Warning
This function is not called by the user directly.Details
In top-ranking, genes are selected based on univariate Cox P-value ranking using the coxph function in the R survival package. In this feature selection method, the genes were ranked based on their likelihood ratio P-value and the top-gn.nb ranked genes with the smallest P-values were retained as the gene signature.The p.adjust function in the R stats package is used and all adjusted p-values not greater than 0.05 are retained if method != "none".