survJamda (version 1.1.4)

calPerformance.meta: Meta analysis of survival data

Description

Analyze jointly the data set by the inverse normal method (Hedges and Olkin, 1985).

Usage

calPerformance.meta(common.gene, zstat, i, j, geno.files, surv.data, method)

Arguments

common.gene

A vector of character strings containing the names of the genes common to all data sets.

zstat

A list containing the combined Z-scores of the data sets composing the training set.

i

A vector of character strings containing the names of the data sets composing the training set.

j

A character string specifying the name the data set used as the testing set.

geno.files

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

surv.data

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

method

A character string specifying the feature selection method: "none" for top-100 ranking or one of the adjusting methods specified by the p.adjust function.

Value

AUC, HR(CI) and p-value.

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-value not greater than 0.05 are retained if method != "none".

References

L. V. Hedges and I. Olkin. Statistical Methods for Meta-Analysis. Academic Press,January 1985. ISBN 0123363802.