stackedBarplot: A plotting function for each sample proportion

In GISPA: GISPA: Method for Gene Integrated Set Profile Analysis

Description

Given a gene, this function will plot the proportion of each sample over all the samples for each gene or row within each data type

Usage

stackedBarplot(gispa.output,feature,cpt,type,input.cex,input.cex.lab,input.gap,samp.col,strip.col)

Arguments

gispa.output	: A data frame containing genes as rows followed by between gene feature profile statistics for each sample.
feature	: Analysis type i.e., one ('1d'), two ('2d') or three ('3d') dimensional feature analysis.
cpt	: Changepoint gene set to be plotted.
type	: Type of data, e.g., EXP (default) for expression, VAR of variants, CNV for copy number change.
input.cex	: character (or symbol expansion): x- and y-axis labels
input.cex.lab	: character (or symbol expansion) for the horizontal and vertial strip labels
input.gap	: gap or distance between each data type plot
samp.col	: a vector of colors of the bar for the three sample groups, reference followed by other two samples
strip.col	: color to be used for the vertial strip

Details

This function expects the output from GISPA function of GISPA package, and highlights the gene set in the selected changepoints and their proportion in each of the three sample groups.

Value

Barplot illustrating each sample proportion for each gene in the selected change point

Author(s)

Bhakti Dwivedi & Jeanne Kowalski

Examples

id <- 20 ## number of rows
s <- 4 ## number of columns
dm <- matrix(runif(id*s,min=0,max=100), nrow=id, ncol=s, 
                 dimnames=list(paste("gene", 1:id, sep=""), 
                 paste("sample", 1:s, sep="")))
changepoints <- sort(sample(1:2, id, replace=TRUE))
dm <- cbind(dm,changepoints)
stackedBarplot(gispa.output=dm, feature=1, cpt=1, type="EXP",
              input.cex=1.5, input.cex.lab=1.5, input.gap=0.5,
              samp.col=c("red", "green", "blue"), strip.col="yellow")

GISPA documentation built on Nov. 8, 2020, 8:11 p.m.