meta.main: Meta analysis of survival data.

In survJamda: Survival Prediction by Joint Analysis of Microarray Gene Expression Data

Description

Meta analysis of microarray gene expression data for survival prediction.

Usage

meta.main(geno.files, surv.data, method = "none")

Arguments

geno.files	A vector of character strings containing the names of expression files.
surv.data	The 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

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".

Value

AUC, HR(CI) and p-value.

Author(s)

Haleh Yasrebi

Examples

require(survJamda.data)

data(gse4335)
data(gse3143)
data(gse1992)

data(gse4335pheno)
data(gse3143pheno)
data(gse1992pheno)

geno.files = c("gse4335", "gse3143","gse1992")
surv.data = list(c(gse4335pheno[,6],gse3143pheno[,4],gse1992pheno[,19]),
c(gse4335pheno[,5],gse3143pheno[,3],gse1992pheno[,18]))

#The following script might take some time
#meta.main(geno.files, surv.data)

## The function is currently defined as
function(geno.files,surv.data, method = "none")
{	
        options(warn=-1) 
        curr_set = 1:length(geno.files)
        for (y in curr_set){
                x = setdiff(curr_set, y)
                data.set.meta (x, y, geno.files,surv.data, method)
        }
}

Example output

Loading required package: survival
Loading required package: survivalROC
Loading required package: ecodist
Loading required package: survcomp
Loading required package: prodlim
Loading required package: survJamda.data
function (geno.files, surv.data, method = "none") 
{
    options(warn = -1)
    curr_set = 1:length(geno.files)
    for (y in curr_set) {
        x = setdiff(curr_set, y)
        data.set.meta(x, y, geno.files, surv.data, method)
    }
}

survJamda documentation built on May 1, 2019, 8:50 p.m.