ceRNA.surv: survival analysis of ceRNA ternary relationship pairs

In CeRNASeek: Identification and Analysis of ceRNA Regulation

Description

It is used to predict the survival of ternary relationship pairs and to support the survival prognosis of training sets and test sets.

Usage

ceRNA.surv(ceRNA, exp.sur, train = NULL, test = NULL, index)

Arguments

ceRNA	a dataframe that the ceRNA relationship is the data, and the prediction result data obtained according to the ceRNA prediction algorithm.Such as ceRNA.cmi prediction result file.
exp.sur	dataframe specifying expression and survival information.Its rownames are sample names.Its colnames are names in triplets and survival information (see example data in details).
train	a character string vector specifying train sample names.
test	a character string vector specifying test sample names.
index	a numeric vector (default 1) reprsenting rowindex of triplets analyed.

Value

A list of identified miRNA sponge interactions containing following components:

• targetce represented target names,respectively.

• anotherce names of modulators that another target(modulators) constitutes a ceRNA interaction relation.

• coef_targetce the coxph coefficient of targetce;

• p_targetce the coxph significance of targetce;

• coef_anotherce the coxph coefficient of anotherce;

• p_anotherce the coxph significance of anotherce;

• N_low The genes were ranked according to expression, and the number of samples expressed in the bottom 25

• N_high The genes were ranked according to expression, and the number of samples expressed in the top 25

• HR Risk score of ceRNA ternary pair.

• p Survival significance of ceRNA ternary pairs.

Examples

##---- Should be DIRECTLY executable !! ----
##-- ==>  Define data, use random,
##--	or do  help(data=index)  for the standard data sets.

## The function is currently defined as
ceRNA.surv(ceRNA=dataset[["Pre.ceRNA"]],exp.sur=dataset[["exp.sur"]],train=NULL,test=NULL,index=5)

CeRNASeek documentation built on April 29, 2020, 9:37 a.m.