Exprs.survtype: Sample subtype identification via survival information and...

In survtype: Subtype Identification with Survival Data

Description

For discovery of subtypes of samples that are both clinically relevant and biologically meaningful, the Cox regession model and hierarchical clustering are combined.

Usage

Exprs.survtype(surv.data, time, status, exprs.data, K = 2, num.genes = 100,
               gene.sel = FALSE, gene.sel.opt = list(verbose = FALSE), ...)

Arguments

surv.data	survival data
time	survival time
status	status indicator
exprs.data	expression data
K	the number of clusters (default: 2)
num.genes	the number of top genes based on the Cox score, before variable selection (default: 100)
gene.sel	a logical value indicating whether or not gene selection for clustring is applied (default: FALSE)
gene.sel.opt	a list of options for the gene selection function "clustvarsel". "verbose" is set to FALSE as default.
...	additional parameters for the "pheatmap"

Value

n	the number of subjects in each group
obs	the weighted observed number of events in each group
exp	the weighted expected number of events in each group
chisq	the chi-squared statistic for a test of equality
call	the matched call
fit	fitted survival curves
cluster	a vector of integers indicating the cluster to which each sample is assigned
time	survival time
status	status indicator
surv.data	survival data
exprs.data	expression data

Author(s)

Dongmin Jung

References

Bair, E., & Tibshirani, R. (2004). Semi-supervised methods to predict patient survival from gene expression data. PLoS biology, 2(4), e108.

See Also

survival::Surv, survival::survfit, survival::survdiff, survival::coxph, clustvarsel::clustvarsel, pheatmap::pheatmap

Examples

set.seed(1)
nrows <- 5
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 = "")
SE <- SummarizedExperiment(assays = SimpleList(counts = counts))
ovarian.survtype <- Exprs.survtype(ovarian, time = "futime", status = "fustat",
                                 assay(SE), num.genes = 2, scale = "row",
                                 clustering_method = "ward.D2")
plot(ovarian.survtype, pval = TRUE)

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