moduleSurvival: Survival analysis of modules

In zhangjunpeng411/miRspongeR: Identification and analysis of miRNA sponge regulation

Survival analysis of modules

Description

Survival analysis of modules.

Usage

moduleSurvival(Modulelist, ExpData, SurvData,
devidePercentage=.5, plot = FALSE)

Arguments

Modulelist	A list of miRNA sponge modules.
ExpData	An input expression data, the columns are genes and the rows are samples.
SurvData	An input survival data, three columns contain the information of sample, time (Months) and status, respectively.
devidePercentage	A percentage value, the percentage of high risk group.
plot	A logical value, plot or not.

Value

Survival analysis result of modules.

Author(s)

Junpeng Zhang (https://www.researchgate.net/profile/Junpeng_Zhang3)

References

Terry M. Therneau and Patricia M. Grambsch. Modeling Survival Data: Extending the Cox Model. Springer, New York. ISBN 0-387-98784-3, 2000.

Examples

# Obtain expression data file "ExpData.csv" in csv format
ExpDatacsv <- system.file("extdata","ExpData.csv",package="miRspongeR")
ExpData <- read.csv(ExpDatacsv, header=TRUE, sep=",")

# Obtain miRNA-target interaction data file "miR2Target.csv" in csv format
miR2Target <- system.file("extdata", "miR2Target.csv", package="miRspongeR")
miRTarget <- read.csv(miR2Target, header=TRUE, sep=",")

# Obtain survival data file "SurvData.csv" in csv format
SurvDatacsv <- system.file("extdata", "SurvData.csv", package="miRspongeR")
SurvData <- read.csv(SurvDatacsv, header=TRUE, sep=",")
pcceRInt <- spongeMethod(miRTarget, ExpData, method = "pc")
spongenetwork_Cluster <- netModule(pcceRInt[, 1:2])
sponge_Module_Survival <- moduleSurvival(spongenetwork_Cluster,
ExpData, SurvData)

zhangjunpeng411/miRspongeR documentation built on Sept. 28, 2022, 2:34 p.m.