splitMerged.indep: Merge the data sets by ComBat or Z-score1 normalization and apply independent validation.

Description

The data sets are either adjusted by Z-score1 normalization or ComBat. In Z-score1 normalization, all data sets are first Z-score normalized and then, merged together. The selection of data sets for the training and testing sets is performed before the application of independent validation.

Usage

splitMerged.indep(geno.files,lst, i, j, method,gn.nb,perf.eval,normalization)

Arguments

geno.files

a vector of character containing the names of gene expression data files.

lst

A list of two objects, (i) gene expression data and (ii) list of two vectors, survival time and censoring status. In the censoring status vector, 1 = event occurred, 0 = censored.

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 method specifying 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

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.

References

Yasrebi H, Sperisen P, Praz V, Bucher P, 2009 Can Survival Prediction Be Improved By Merging Gene Expression Data Sets?. PLoS ONE 4(10): e7431. doi:10.1371/journal.pone.0007431.