plot_up: Function to plot the results of expression_up

In KANT: Package to identify and sort genes overexpressed

Description

Generates a graphic of the 50 best probesets of the algorithm. Every probeset is plotted in function of the number of samples in the subpopulation that overexpressed it and delta (difference of expression between max of normal samples and median of the subpopulation). They are represented by a circle, with a size proportional to 1/(standard deviation of expression in the subpopulation)

Usage

plot_up(N, eset_up, cells_type, fontsize)

Arguments

N	Number of probesets to plot
eset_up	Result of expression_up
cells_type	Name of the type of cells tested (just for title of the graph)
fontsize	For legends

Author(s)

Noemie Robil

See Also

See Also link{expression_up}

Examples

## The function is currently defined as
function (N, eset_up, cells_type, fontsize) 
{
    probes <- 1:N
    plot(as.numeric(as.character(pData(featureData(eset_up))[probes, 
        "Numbre_up"])), as.numeric(as.character(pData(featureData(eset_up))[probes, 
        "Delta_median_up"])), 
        cex = (1/(0.1 + as.numeric(as.character(pData(featureData(eset_up))[probes, 
        "IQR_up"])))), pch = 21, main = c("Over-expression in  :", 
        cells_type), xlab = "Number of samples in the sub-population over-expressing the gene", 
        ylab = "Delta")
    text(as.numeric(as.character(pData(featureData(eset_up))[probes, 
        "Numbre_up"])), as.numeric(as.character(pData(featureData(eset_up))[probes, 
        "Delta_median_up"])), as.character(pData(featureData(eset_up))[probes, 
        "Gene.Symbol"]), pos = 2, cex = fontsize)
  }

KANT documentation built on May 2, 2019, 2:13 p.m.