I use microarray data. I'm using "oligo" R package for background correction and normalisation of expression values. After normalisation I want to calculate Z-score to generate a heatmap.
As they are around 25,000 genes with expression values in the matrix, I want to create a heatmap with only top 10% highly variable genes.
Looking for a best statistical way to select top 10% highly variable genes with which I can plot a heatmap.
With some google search I found the following one:
"normdata" is a matrix with 25,000 genes after background correction and normalisation.
x <- apply(normdata, 1, IQR) #Calculate IQR
y <- normdata[x > quantile(x, 0.9), ] #selecting top 10% highly variable genes
Do you think the above code is the right way to select top 10% highly variable genes?