cptSamples: Sample profile identifier analysis
In BhaktiDwivedi/SISPA: SISPA: Method for Sample Integrated Set Profile Analysis

Description Usage Arguments Details Value See Also Examples

Generate sample profile identifiers from sample zscores using change point model.

1	cptSamples(x, cpt_data, cpt_method, cpt_max)

`x`	A matrix or data frame of sample GSVA enrichment zscores within which you wish to find a changepoint.
`cpt_data`	Identify changepoints for data using variance (cpt.var), mean (cpt.mean) or both (cpt.meanvar). Default is cpt.var.
`cpt_method`	Choice of single or multiple changepoint model. Default is "BinSeg".
`cpt_max`	The maximum number of changepoints to search for using "BinSeg" method. Default is 60.

This function assigns samples identified in the first changepoint with the active profile ("1") while the remaining samples are grouped under inactive profile ("0").

The input data frame with added sample identifiers and estimated changepoints. A plot showing the changepoint locations estimated on the data

changepoint

g <- 10 ## number of genes
s <- 60 ## number of samples
## sample data matrix with values ranging from 1 to 10
rnames <- paste("g", 1:g, sep="")
cnames <- paste("s", 1:s, sep="")
expr <- matrix(sample.int(10, size = g*s, replace = TRUE), nrow=g, ncol=s, dimnames=list(rnames, cnames))
## genes of interest
genes <- paste("g", 1:g, sep="")
## Estimates GSVA enrichment zscores.
gsva_results <- callGSVA(expr,genes)
cptSamples(gsva_results,cpt_data="var",cpt_method="BinSeg",cpt_max=60)