PlotForest {IDMIR}

PlotForest

Description

Function "PlotForest" can visualize the result of Cox regression analysis through forest plot.

Usage

PlotForest(MiRNA_CRData,g.pos = 2,b.size = 3,col = c("#FE0101", "#1C61B6", "#A4A4A4"),
lwd.zero = 2,lwd.ci = 3,x.lab = "Hazard Ratio Plot")

Arguments

MiRNA_CRData

A list includes a data frame with seven parts those are "sample", "status", "time", "target genes expression", "risk score", "group", and a data frame with five columns those are "Gene", "HR", "HR.95L", "HR.95H", "beta", and "P-value".

g.pos

The position of the graph element within the table of text. The position can be 1-(ncol(labeltext) + 1). You can also choose set the position to "left" or "right".

b.size

Override the default box size based on precision.

col

Set the colors for all the elements in the plot.

lwd.zero

lwd for the vertical line that gives the no-effect line, see gpar.

lwd.ci

lwd for the confidence bands, see gpar.

x.lab

x-axis label.

Value

Forest maps associated with the Cox risk model.

Examples

# Obtain the example data
GEP<-GetData_Mirna("GEP")
survival<-GetData_Mirna("survival")
MiRNAs<-c("hsa-miR-21-5p","hsa-miR-26a-5p","hsa-miR-369-5p","hsa-miR-1238-3p","hsa-miR-10b-5p")
# Run the function
SingleMiRNA_CRData<-SingleMiRNA_CRModel(GEP,
"hsa-miR-21-5p",survival,cutoff.point=NULL)
PlotForest(SingleMiRNA_CRData)
MutiMiRNA_CRData<-MutiMiRNA_CRModel(GEP,
MiRNAs,survival,cutoff.point=NULL)
PlotForest(MutiMiRNA_CRData)