plotCtCor: Correlation between Ct values from qPCR data

In HTqPCR: Automated analysis of high-throughput qPCR data

Description

Function for plotting the correlation based on Ct values between samples containing high-throughput qPCR data.

Usage

plotCtCor(q, col, col.range = c(0, 1), main, mar, ...)

Arguments

q	object of class qPCRset.

col	vector of colours to use, defaults to a spectrum from red to blue/purple.
col.range	vector, the range of colours to use.
main	character string, plot title.
mar	vector, the size of the borrom and right hand side margins.
...	any other arguments will be passed to the heatmap.2 function.

Details

This function may be used to cluster the samples based on Ct values and present the result in a heatmap. Per default the colours are a rainbow scale from 0 to 1.

The correlation is calculated as 1 - the 'Pearson' method. Prior to version 1.9.1 the value plotted was the correlation directly, rather than 1-correlation.

A standard heatmap is drawn, but this can be modified extensively using the arguments available in the heatmap.2 function.

Value

A plot is created on the current graphics device.

Author(s)

Heidi Dvinge

See Also

heatmap.2

Examples

data(qPCRraw)
plotCtCor(qPCRraw)
plotCtCor(qPCRraw, col.range=c(0,0.6))

HTqPCR documentation built on Nov. 8, 2020, 6:51 p.m.