BI_FastCoxlasso: Penalized Cox regression model via lasso algrithm

In shijianasdf/BasicBioinformaticsAnalysisFromZhongShan: Launch Usual Clinical tool for Kind Yield

Description

FastCoxlasso help do a plot-based penalized Cox regression model via lasso algrithm.

Usage

FastCoxlasso(
  expr.matrix,
  design,
  select,
  event.status=c("TTR.status","DFS.status","OS.status")[2],
  event.time=c("TTR.time","DFS.time","OS.time")[2],
  event.lower =c(89,89,89),
  lambda.n = 3,ln.lambda = 0,label=F,
  digits = 5,
  names = "love"
)

Arguments

expr.matrix	expression matrix
design	design object
select	selected markers or genes
event.status	colnames of event status
event.time	colnames of event time
event.lower	the lower limit of event time
lambda.n	the counts of genes with parameters you want
ln.lambda	ln(lambda)
label	whether to show the genes label on the plot.Default is F
digits	the digits of model coefficient
names	part of saved files name

Value

a list containing gene-based survival data and model data

Author(s)

Weibin Huang<[e-mail]>

Examples

## This is a simulative process and NOT RUN
expr.matrix = train.fpkm
design = design.train
select = rocgenes
event.status="DFS.status"
event.time="DFS.time"
event.lower = 89
label = T
label=TRUE
digits = 5
names = "love"
CO1 <- FastCoxlasso(expr.matrix,
                    design,
                    select,
                    event.status,
                    event.time,
                    event.lower,
                    lambda.n = 5,
                    ln.lambda= -3.55,
                    label,digits,names)
View(CO1$DFS$modeldata)

## Common Use
FC1 <- FastCoxlasso(expr.matrix = train.fpkm,
                    design= design.train,
                    select = rocgenes,
                    event.status="DFS.status",
                    event.time="DFS.time",
                    event.lower= 89,
                    lambda.n = 5,
                    ln.lambda= -3.55,
                    names = "train")

shijianasdf/BasicBioinformaticsAnalysisFromZhongShan documentation built on Jan. 3, 2020, 10:08 p.m.