Single.survgroup: Patient group identification via survival information and...

In survtype: Subtype Identification with Survival Data

Description

All midpoints of the expression level or real-valued statistic are investigated to find the best threshold giving the most significant difference between two groups. Any patients having the value greater than the best cutoff are assigned as the "high-score" class. Otherwise, the others belong to the "low-score" class.

Usage

Single.survgroup(surv.data, time, status, single.gene, intermediate = FALSE,
                 group.names = c("High", "Intermediate", "Low"))

Arguments

surv.data	survival data
time	survival time
status	status indicator
single.gene	expression level of a single gene
intermediate	a logical value indicating whether or not the intermediate class is considered (default: FALSE)
group.names	the name of clusters for "high-score", "intermediate-score", and "low-score" classes (defult: "High", "Intermediate", "Low")

Value

time	survival time
status	status indicator
surv.data	survival data
score	a vector of scores
summary	a list of thresholds, chi-squared statistics and p-values
cluster	a vector of clusters to which samples are assigned
fit	fitted survival curves

Author(s)

Dongmin Jung

See Also

survival::Surv, survival::survfit, survival::survdiff

Examples

set.seed(1)
nrows <- 1
ncols <- nrow(ovarian)
counts <- matrix(runif(nrows * ncols, 1, 1e4), nrows)
colnames(counts) <- paste("X", 1:ncols, sep = "")
rownames(ovarian) <- paste("X", 1:ncols, sep = "")
Single.ovarian <- Single.survgroup(ovarian, time = "futime", status = "fustat", counts[1,])
plot(Single.ovarian, pval = TRUE)

survtype documentation built on Nov. 8, 2020, 7:24 p.m.