calPerformance.auc.plot: Assess the performance obtained from the merged data set by...

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

Description

Identify a gene signature and reduce the gene set in the training and testing sets accordingly.

Arguments

lst	List of two objects, the gene expression data matrix and a list of two vectors, survival time and censoring status. In the censoring status vector, 1 = event occurred, 0 = censored.
train.ind	Training set index.
test.ind	Testing set index.
file.name	The name of the expression file used as the testing set.
col	Color of ROC curve.
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.
normalization	The normalization method, Z-score2, Z-score1 or ComBat.
time.dep	An integer 0 or 1, 1 to plot time-dependent ROC curves for different time points and 0 for no plot

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

None.

Warning

This function is not called by the user directly.

Author(s)

Haleh Yasrebi

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