splitZscore2.merge.indep: Merge data sets by Z-score2 normalization and assess the performance by independent validation.

Description

Z-score2 normalization is performed as follows: First, the data sets are selected for the training and testing sets. Suppose there are S data set. Then, in S iteration, S-1 data sets selected as the training set and the remaining set as the testing set until all data sets are used in the training and testing sets. The data sets composing the training set are merged together and the merged data set is then Z-score normalized. The testing set is independently adjusted by Z-score normalization.

Usage

splitZscore2.merge.indep(common.gene, geno.files, surv.data, lst, i, j, 
method,gn.nb,perf.eval, normalization)

Arguments

common.gene

A vector of character strings containing the names of the genes common to the datasets composing the training set.

geno.files

A vector of character strings containing the names of the expression files.

surv.data

A list of two vectors, survival time and censoring status. In the censoring status vector, 1 = event occurred, 0 = censored.

lst

The list of two objects, the gene expression data and surv.data.

Index of the names of the expression files composing the training set.

Index of the name of the expression file used as the testing set.

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

Number of genes to select for gene signature when method="none".

perf.eval

A string taking one the values, "auc", "cindex", "bsc".

normalization

A character string specifying the normalization method, "zscore1", "zscore2" or "combat".

Value

None.

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 are ranked based on their likelihood ratio P-value and the top-100 ranked genes with the smallest P-values are 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".

If perf.eval == "auc", time-dependent AUC and hazard ratio are used as the measure of performance, perf.eval == "cindex", concordance index defined in the survcomp package or perf.eval == "bsc", brier score defined in the survcomp package is used.