featureselection: Apply a feature selection

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

Description

Apply univariate Cox regression and rank the genes based on the Cox p-value.

Usage

featureselection(gnExpMat, survivaltime, censor, method = "none",gn.nb)

Arguments

gnExpMat	Matrix of gene expression data.
survivaltime	Vector of survival time.
censor	Vector of censoring status. In the censoring status vector, 1 = event occurred, 0 = censored.
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".

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-gn.nb 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

A list of two vectors, the Cox coefficients and Cox p-values.

Warning

This function is not called by the user directly.

Author(s)

Haleh Yasrebi

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.

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