plotCtHeatmap {HTqPCR} | R Documentation |
Function for drawing a heatmap of Ct values from high-throughput qPCR experiments such as using TaqMan Low Density Arrays.
plotCtHeatmap(q, main = NULL, col, col.range, dist = "pearson", zero.center, mar, gene.names, sample.names, ...)
q |
object of class qPCRset. |
main |
character string, plot title. |
col |
the colours to use. See details. |
col.range |
vector, the range of colours to use. |
dist |
character string, specifying whether to use "pearson" correlation (default) or "euclidean" distance for the clustering. |
zero.center |
logical, should the colours be shifted to be zero-centered. See details. |
mar |
vector, the size of the borrom and right hand side margins. |
gene.names |
character vector, names to replace the genes (rows) with. See details. |
sample.names |
character vector, names to replace the samples (columns) with. See details. |
... |
any other arguments will be passed to the |
This function may be used to cluster the raw or normalized Ct values, and present the result in a heatmap.
The color range is used to represent the range of values for the statistic. If col==NULL
the colour will be set to a spectrum from red to blue/purple, unless there are negative values in which case it goes red-yellow-green to reflect up and down regulation of genes. If zero.center=NULL
then zero.center will automatically be set to TRUE to make the colour scale symmetric around 0.
Especially gene names will often not be readable in a standard size plotting device, and might therefore be removed. If gene.names
or sample.names
is set to a single character (such as "" for no naming), then this character will be repeated for all rows or columns.
A standard heatmap is drawn, but this can be modified extensively using the arguments available in the heatmap.2
function.
A plot is created on the current graphics device.
Heidi Dvinge
# Load example data data(qPCRraw) # Some standard heatmaps plotCtHeatmap(qPCRraw, gene.names="") plotCtHeatmap(qPCRraw, gene.names="", dist="euclidean", col.range=c(10,35)) plotCtHeatmap(qPCRraw, gene.names="", dist="euclidean", col=colorRampPalette(rev(brewer.pal(9, "YlGnBu")))(20))