plotCorr: Basic correlation plot function for normalized or...

In metagenomeSeq: Statistical analysis for sparse high-throughput sequencing

Description

This function plots a heatmap of the "n" features with greatest variance across rows.

Usage

plotCorr(obj, n, norm = TRUE, log = TRUE, fun = cor, ...)

Arguments

obj	A MRexperiment object with count data.
n	The number of features to plot. This chooses the "n" features with greatest variance.
norm	Whether or not to normalize the counts - if MRexperiment object.
log	Whether or not to log2 transform the counts - if MRexperiment object.
fun	Function to calculate pair-wise relationships. Default is pearson correlation
...	Additional plot arguments.

Value

plotted correlation matrix

See Also

cumNormMat

Examples

data(mouseData)
plotCorr(obj=mouseData,n=200,cexRow = 0.4,cexCol = 0.4,trace="none",dendrogram="none",
         col = colorRampPalette(brewer.pal(9, "RdBu"))(50))

metagenomeSeq documentation built on Nov. 8, 2020, 5:34 p.m.